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RBI: Reddit Bureau of Investigation

2012.01.03 08:11 DecidingToBeBetter RBI: Reddit Bureau of Investigation

Using the power of the internet to solve real world problems.
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2020.12.02 20:53 JauneSiriusWhut Lamborghini Gallardo & Murcielago specials

Gallardo Superleggera
2008
Singapore - Grey
Frankfurt am Main - Yellow
2009
Singapore - White
2011
Sao Paulo - Orange
Hong Kong - Orange
2013
Dietikon - Black
2015
Hardenberg - White
2016
Brampton - White
2018
Burlingame - Grey
2019
Kitzbühel - Grey

Gallardo LP550-2 Valentino Balboni
2011
Beverly Hills - Silver
Naples - Yellow
Hong Kong - White
2015
Vancouver - White
2016
Tokyo - Orange
2019
Singapore - Orange

Gallardo LP570-4 Superleggera
2011
Singapore - Green
Hong Kong - Yellow
2012
Singapore - White
2013
Stafa - White
2014
Toronto - Black
2015
West Vancouver - Gold
2016
Toronto - Blue
Bournemouth - Green
Alexandria - Yellow
2018
Singapore - Orange
Singapore - Pink
Singapore - White
2019
Singapore - Green
Singapore - Orange
Singapore - White
Nice - White
Vancouver - Black

Gallardo LP570-4 Superleggera Edizione Tecnica
2019
Taipei - Black

Gallardo LP570-4 Spyder Performante
2012
Cannes - Orange
2014
Edinburgh - White
2015
Scottsdale - Orange
London - White
London - White
Kobe - White
2016
London - Black
London - Orange
Albuquerque - Orange
2017
North Bergen - Black
2018
Vancouver - Green

Gallardo LP570-4 Super Trofeo
2014
Dubai - Red
2016
Vancouver - Red

Murcielago LP670-4 Super Veloce
2011
Singapore - Orange
Richmond - White
2012
Singapore - Black
London - Blue
Paris - Grey
2014
Miami Beach - White
2017
Vancouver - Black
2018
Bellevue - Orange
2019
Singapore - Orange
Paris - White
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2020.12.02 20:52 JauneSiriusWhut Lamborghini Huracan, Aventador & Hypercar(s) special!

The previous special has been split up due to a limited amount of characters. It's still all here (and there)!

Aventador LP720-4 50 Anniversario
2014
Beverly Hills - Grey
Miami Beach - Yellow
2015
Beverly Hills - Yellow
2017
Toronto - Grey
2018
Singapore - Yellow

Aventador LP720-4 50 Anniversario Roadster
2015
Beverly Hills - White
2017
Paris - Yellow
London - Red
London - Red
London - White
2020
Stockholm - White

Aventador LP750-4 Super Veloce
2016
London - Red
Beverly Hills - Orange
London - Yellow
Cannes - White
2017
Vancouver - Black
London - Purple
Tokyo - Red
London - Covered
New York - White
Aventura - Yellow
2018
Los Angeles - Red
Boca Raton - Grey
Osaka - Yellow
Singapore - Yellow
2019
Alderley Edge - Black
Huntington Beach - Black
Verona - Red
London - Yellow
Hong Kong - Yellow
Singapore - Yellow
Los Angeles - Yellow
2020
Miami Beach - Blue
Tokyo - Green
Sutton Coldfield - Yellow

Aventador LP750-4 Roadster Super Veloce
2016
London - Black
London - Blue
Highway - Grey
2017
Cannes - Blue
Paris - White
Malibu - White
2018
Bromley - Black
Orpington (same as above) - Black
London - White
Los Angeles - White
2019
London - Black
London - Black
Tokyo - Blue
Soesterberg - White
Miami - Yellow

Aventador Miura Edition
2018
Toronto - Red

Aventador SVJ
2019
Marbella - Covered
Benhavis - Red
Bury - Blue
Tokyo - Green
Bologna - Purple
New York City - White
2020
Tokyo - Orange
Sydney - Yellow

Aventador SVJ Roadster
2020
England - Green
Mexico-City - Yellow

Huracan Avio
2016
Moscow - Grey
2017
Willowbrook - Blue
2018
Singapore - Blue
2019
Tokyo - Blue

Huracan Performante
2017
Atlanta - Grey
2018
Brighton - Black
Dallas - Black
Atlanta - Blue
Montreal - Green
Vaughan - Green
Desenzano del Garda - Green
Oud Gastel - Green
Gardone Riviera - Grey
Auckland - Orange
Millbrae - Orange
Miami Beach - Orange
Naples - Orange
Calabasas - White
2019
Wrotham - Black
Toronto - Black
Sydney - Blue
Pettnau - Green
Markham - Green
Toronto - Green
Los Angeles - Green
Sydney - Green
London - Grey
Sint Pete Beach - Grey
Cannes - Orange
Vancouver - Purple
Hong Kong - Purple
Milan - White
Beverly Hills - White
Barcelona - White
2020
Scottsdale - Wrapped

Huracan Performante Spyder
2018
Toronto - White
London - White
2019
Italy - Blue
London - Green
Roquebrune-Cap-Martin - Grey
Los Angeles - Grey
Los Gatos - Grey
Boca Raton - Grey
Mougins - Red
Milan - White
Italy - White
West Hollywood - White
Miami - White
2020
Gateshead - Blue
Tokyo - White

Bonus: Centenario!
2017
West Hollywood - Grey
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2020.12.02 12:03 remote-enthusiast I've collected 98 remote jobs

Hello friends! These are the open remote positions I've found that were published today. See you tomorrow! Bleep blop 🤖
submitted by remote-enthusiast to remotedaily [link] [comments]


2020.12.01 15:09 SPAC_Time OPES Acquisition Corp. Schedules Shareholder Meeting to Vote for Burger Fi Business Combination on December 15 - OPES OPESW

"Dear Stockholders:
You are cordially invited to attend a meeting of the stockholders (the “Meeting”) of OPES Acquisition Corp. (“OPES,” “we”, “our”, or “us”), which will be held at 10:00 a.m., Eastern time, on December 15, 2020."
" If you were a holder of record of OPES Common Stock on November 24, 2020, the Record Date for the Meeting, you may vote with respect to the Proposals at the Meeting, or by submitting a proxy by mail so that it is received prior to 9:00 a.m., Eastern time, on December 15, 2020, in accordance with the instructions provided to you under the section titled “The Meeting.” "
" We encourage you to read this proxy statement carefully. In particular, you should review the matters discussed under the caption “Risk Factors” beginning on page 17.
OPES’s Board of Directors unanimously recommends that OPES stockholders vote “FOR” approval of each of the proposals.
Important Notice Regarding the Availability of Proxy Materials for the Special Meeting of Stockholders to be held on December 15, 2020: The notice of meeting, the accompanying proxy statement and proxy card are available at https://www.cstproxy.com/opesacquisitioncorp/smp2020.
For banks and brokers, the notice of meeting and the accompanying proxy statement are available at https://www.cstproxy.com/opesacquisitioncorp/smp2020/proxy. "
https://www.sec.gov/Archives/edgadata/1723580/000121390020040068/ea130561-defm14a_opesacqu.htm
Edit: OPES has also issued a press release for the shareholder meeting:
"Opes Acquisition Corp. Announces Special Stockholders Meeting to Approve Business Combination With BurgerFi on December 15, 2020
- Stockholders are Encouraged to Submit Their Vote Prior to the Special Meeting - - This Vote is Separate from the Previous Vote Relating to the Extension Amendment -
MIAMI, Dec. 01, 2020 (GLOBE NEWSWIRE) -- OPES Acquisition Corp. (Nasdaq: OPES OPESW) (“OPES” or the “Company”) is announcing that it has set December 15, 2020, as the date of its special meeting of stockholders (the “Special Meeting”) to approve the previously announced business combination (the “Business Combination”) with BurgerFi International, LLC. (“BurgerFi”).
Notice of the Special Meeting, together with the definitive proxy statement relating to the Special Meeting, is expected to be mailed on or about December 2, 2020, to stockholders of record as of the close of business on November 24, 2020 (the “Record Date”).
The Special Meeting will be conducted via teleconference. Stockholders will be able to attend the meeting by using the following dial-in information:
US/CANADA Toll-Free Dial-In Number: (833) 962-1457 US/CANADA International Dial-In Number: (956) 394-3594 Conference ID: 4768828
Your vote is important no matter how many shares you own. You are encouraged to submit your vote as soon as possible. If you hold your shares in an account at a brokerage firm, bank or other similar agent, you may vote prior to the meeting by using your voting control number and instructions provided by your brokerage firm, bank or other similar agent. If you are a stockholder of record, you may vote prior to the special meeting by signing, dating, and mailing your proxy card in the return envelope provided with your proxy material.
The closing of the Business Combination is subject to approval by OPES’s stockholders and the satisfaction of other customary closing conditions and is expected to close as soon as practicable following the Special Meeting. Following the closing, Opes Acquisition Corp. will change its name to BurgerFi International, Inc."
https://www.globenewswire.com/news-release/2020/12/01/2137569/0/en/Opes-Acquisition-Corp-Announces-Special-Stockholders-Meeting-to-Approve-Business-Combination-With-BurgerFi-on-December-15-2020.html
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2020.12.01 12:03 remote-enthusiast I've collected 83 remote jobs, enjoy!

Hello friends! These are the open remote positions I've found that were published today. See you tomorrow! Bleep blop 🤖
submitted by remote-enthusiast to remotedaily [link] [comments]


2020.11.24 22:31 Kal-El-SUPERMAN Top 10 GIANT Discoveries in North America

by Hugh Newman and Jim Vieira
January 18, 2016 from AncientOrigins Website


Jim Vieira and Hugh Newman have been working together investigating Native American stone and earthen constructions, Native oral history and the giant skeletons of North America for nearly ten years. They starred together on the History Channel TV show Search for the Lost Giants (2014) and have recently co-authored Giants On Record: America's Hidden History, Secrets in the Mounds and the Smithsonian Files (2015). Jim and his brother Bill also starred on the recently aired History Channel special Roanoke: Search for the Lost Colony (2015). Jim is a stonemason and lives in Ashfield, Massachusetts. Hugh is an explorer, antiquarian and author of Earth Grids: The Secret Patterns of Gaia's Sacred Sites (Wooden Books 2008). He has several articles published on Ancient Origins website and has been a regular guest on History Channel's Ancient Aliens. He lives in Glastonbury, England. His websites are www.megalithomania.co.uk and www.hughnewman.co.uk



https://preview.redd.it/zh3efp9badd41.jpg?width=500&format=pjpg&auto=webp&s=bbd4139f670c64a3259283fb5bff17287827da2f

The Iroquois, the Osage, the Tuscaroras, the Hurons, the Omahas, and many other North American Indians all speak of giant men who once lived and roamed in the territories of their forefathers. All over what is now the U.S. are traditions of these ancient giants. 1

Over 1000 accounts of seven-foot and taller skeletons have reportedly been unearthed from ancient burial sites over a two-hundred-year period in North America.
Newspaper accounts, town and county histories, letters, scientific journals, diaries, photos and Smithsonian ethnology reports have carefully documented this.
These skeletons have been reported from coast to coast with strange anatomic anomalies such as double rows of teeth, jawbones so large as to be fit over the face of the finder, and elongated skulls, documented in virtually every state.

Figure 1: Map of giant reports in North America. Created by Cee Hall.
Smithsonian scientists identified at least 17 skeletons that stood at over seven feet in their annual reports, including one example that was 8 feet tall, and a skull with a 36-inch circumference reported from Anna, Illinois in the Smithsonian Annual Report of 1873, (an average human skull is about 20 inches in circumference).
The Smithsonian Institution is mentioned dozens more times as the recipient of enormous skeletons from across the entire United States.
The skeletons mentioned no longer seem to exist regardless of their actual size, and the remaining ones that were on display were removed and repatriated by NAGPRA (Native American Graves Protection and Repatriation Act).
While the authors certainly support this law, it does present a moral and ethical conundrum in terms of trying to ascertain the proof everyone wants to see - physical evidence of giants.


Figure 2: Selection of news accounts featured in the book

In this unique Top Ten, we look at some examples of giant skeletons that were reported from across ancient North America (although we warn you now that Number 1 is so large, we admit it may not be authentic). Our countdown begins at one of the most important mound sites in America, and quite possibly the world.


Figure 3: Various sized skulls found at Potomac Creek, Stafford County, Virginia, 1937.

TOP TEN GIANTS
  1. Serpent Mound, Ohio, 1890s - 7 ft tall skeleton


Serpent Mound survey by Squire and Davis.

The Great Serpent Mound is a 1,370ft long prehistoric effigy mound located near Peebles that has been thoroughly researched by Ross Hamilton, who has written extensively about its mysteries and the giants discovered in the area.
Recent radiocarbon analysis dates it to around 321 BC. This puts it in the realm of the Adena civilization who were present in the area at this time.
In the 1890s, Professor Frederic Ward Putnam excavated some of the mounds next to Serpent Mound and found only 6ft tall skeletons, but a postcard showing one 7 feet in height was recently rediscovered by researcher Jeffrey Wilson.
It may have been one of those excavated by Putnam, as he was the only person to dig at the site.
Ross first published this in his book A Tradition of Giants, and it clearly states it was from Serpent Mound on the postcard, but there is still debate as to where this photo of a 7ft skeleton was actually taken.
Notice that the legs are cut off at the knees, so is "7ft" what we actually see, or is it an estimation if he had his lower legs and feet attached? Could it have been more like 8 feet tall if the shins and feet were intact?


The 7 ft skeleton from Serpent Mound cut off at the knees. Courtesy of Jeffrey Wilson.

  1. Cresap Mound, West Virginia, 1959 - 7ft 2in skeleton In 1959, Dr. Donald Dragoo, the curator for the Section of Man at the Carnegie Museum unearthed a 7 feet 2 inch skeleton during the complete excavation of the Cresap Mound in Northern West Virginia:
"This individual was of large proportions. When measured in the tomb his length was approximately 7.04 feet. All of the long bones were heavy."

7ft 2 inch skeleton with top part of skeleton burnt.


Ground Plan of Cresap Mound showing Clay floor level and below.The giant skeleton is on the middle right.

Dragoo published a photo of the actual skeleton in his book so there is no doubt it was authentic.
Dragoo joins many other university-trained anthropologists and archaeologists who reported discovering skeletons over seven feet in length in burial mounds, often with anatomical anomalies.
A few of the professionals reporting these skeletal finds were,


8. Mounds in Iowa, 1897 - 7ft 6in skeleton This account from The Worthington Advance (November 18, 1897) describes the ethnological work of the Smithsonian Institution's Division of Eastern Mounds, and quoted the Director of the Bureau of Ethnology at the time, John Wesley Powell.
The image below accompanied the news report.
"It is a matter of official record that in digging through a mound in Iowa the scientists found the skeleton of a giant, who, judging from actual measurement, must have stood seven feet six inches tall when alive.
The bones crumbled to dust when exposed to the air."


Illustration showing the excavation of a giant skeleton.

  1. Steelville, Missouri, 1933 - 8ft skeleton As part of the Search for the Lost Giants show, Jim and fellow researcher James Clary investigated the following account that had this heading:
"An Ancient Ozark Giant Dug Up Near Steelville: Strange discovery made by a boy looking for arrowheads, gives this Missouri Town an absorbing mystery to ponder."
From The Steelville Ledger (June 11, 1933):
"…he turned up the complete skeleton of an 8 foot giant.
The grisly find was brought to Dr. R. C. Parker here and stretched out to its enormous length in a hallway of his office where it has since remained the most startling exhibit Steelville has ever had on public view."
While reading through the microfilm at the Steelville library three reports of the find where uncovered including the photo that shows Les Eaton, a 6-foot man, laid out next to the 8-foot skeleton in Dr. Parkers office.


Les Eaton on the floor next to the 8-foot skeleton.
The Steelville Ledger reported that the skeleton was packed up and shipped to the Smithsonian, never to be heard of again.

6. Miamisburg, Montgomery County, Ohio - 8ft 1.5 inch skeleton Miamisburg Mound is believed to have been built by the Adena Culture, anywhere between 1000 to 200 BC.
It is the largest conical burial mound in Ohio, once nearly 70 feet tall (the height of a seven-story building) and 877 feet in circumference. Hugh investigated this site in September 2012 and after talking to some researchers at the local historical society, he found there were other skeletal remains reported in the nearby area.

Old illustration of Miamisburg Mound.
Numerous skeletal remains were uncovered from the mound, including a giant jawbone and " bones of unusual size," but it was the discovery half-a-mile away that became a national sensation and was reported in The Middletown Signal, January 17, 1899 with the headline: "Bones of Prehistoric Giant Found Near Miamisburg":
"The skeleton of a giant found near Miamisburg is the cause of much discussion not only among the curious and illiterate but among the learned scientists of the world.
The body of a man more gigantic than any ever recorded in human history, has been found in the Miami Valley, in Ohio. The skeleton it is calculated must have belonged to a man 8 feet 1.5 inches in height."
Professor Thomas Wilson curator of prehistoric anthropology at the Smithsonian Institution, said the following after examining the find:
"The authenticity of the skull is beyond any doubt.
Its antiquity unquestionably great, to my own personal knowledge several such crania were discovered in the Hopewell group of mounds in Ohio. The jaws were prognathus (projecting beyond the face) and the facial index remarkably low."

Illustration of over 8-foot skeleton discovered near Miamisburg.


5. The San Diego Giant, 1895 - 8ft 4 inch mummy This fascinating discovery reports on a giant mummy found in San Diego (that is currently believed to be a hoax).
However, let's take a closer look, as there is some intrigue and inconsistency with this popular story. This first report appeared in 1895 with the sub-headings "Nine Feet High and Probably a California Indian - Measurement Well Authenticated - Other Big Men and Women of Fact and Fable Who Are Famous Types if Gigantism."
When accurately measured it turned out to be 8ft 4 inches and was,
"carefully inspected and measured by Prof. Thomas Wilson, Curator of the Department of Prehistoric Anthropology in the Smithsonian Institution, and by other scientists."


The San Diego giant was purchased by the Smithsonian for $500 (over $14,000 in today's money) in 1895, although they later claimed it was a hoax.

Thirteen years later - in 1908 - when the mummy was being exhibited, the Smithsonian ran some tests and suddenly dismissed it as a hoax, saying it was made from "gelatin."
The fact that it took that long, and after spending $500 to acquire it, plus the fact that it was "carefully inspected" by experts thirteen years earlier does suggest there may be more to this story than meets the eye.
Interestingly, Aleš Hrdlička, joined the Smithsonian in 1903, right in between the discovery and the final debunking. He was not interested in giants and made a concerted effort to eradicate them from the historical record.
It is also interesting to note that the Director of Prehistoric Anthropology, Thomas Wilson, and the ethnologist in charge W.J. McGee, were both involved in this story, and were obviously keen to make sure the Smithsonian got it back to their headquarters at an immense cost ($500 in 1895 equates to $14,285 today).
But why would they bother doing that if it was simply a sideshow hoax?
The strange twists, and Smithsonian involvement, and the immense amount of money spent on this makes this worthy of inclusion in this Top Ten.
A similar mummified giant also turned up at Spiro Mounds, Oklahoma. It measured 8ft 5 in and was on display for a few months, where it was seen by several people before it disappeared. 4

4. Catalina Island, California - 9 ft 2 inch skeleton (and other 7ft - 8ft examples) The Channel Islands off the coast of California have turned up numerous oversized skeletons.
The story is intriguing and controversial, and it stars amateur archaeologist Ralph Glidden and his bizarre museum, but before the main act, a German naturalist got the story going in 1913.
Dr. A.W. Furstenan reported unearthing an 8 ft tall skeleton with artifacts such as mortar, pestles and arrowheads on Catalina. He was told of a legend while in Mexico of a giant and noble race that lived on the Island, who existed long before the white man and had since vanished. 5
Amateur archaeologist Ralph Glidden unearthed and collected a total of 3,781 skeletons on the Channel Islands between 1919 and 1930.
Working for the Heye Foundation of New York he unearthed a 9ft 2 in skeleton and several measuring over 7 feet:
"A skeleton of a young girl, evidently of high rank, within a large funeral urn, was surrounded by those of sixty-four children, and in various parts of the island more than three thousand other skeletons were found, practically all the males averaging around seven feet in height, one being seven feet eight inches from the top of his head to the ankle, and another being 9 feet 2 inches tall."


The skeleton in the picture is 7ft 8 in example.

As part of Search for the Lost Giants, Jim and Bill Vieira visited Catalina to investigate the contents of the box, and indeed there were photos of hundreds of skeletons and skulls, excavations, artifacts, and burials.
They also uncovered an account of a 28-inch femur unearthed by Glidden on San Nicolas Island reported by the judge of Avalon, Earnest Windle.
This would make the skeleton over 8 feet tall.


An over 7-foot skeleton found on Catalina Island.

3. Beaver Lake, Ozark Caves, Arkansas, 1913 - Nearly 10 ft skeleton and huge skulls This account from an Ozark cave in Arkansas is found in The New Age Magazine (Volume 18, 1913) given by the highly regarded reporter Victor Schoffelmeyer.


Skulls of giants with cranial deformation.

During the filming of Search for the Lost Giants, the site of the cave was investigated.
It had been flooded with the damming and creation of Beaver Lake between 1960-1966.
Bill Vieira and professional scuba diver Mike Young dived into the lake and found a huge shelter cave believed to be the site of the skeletal finds.
While a 70ft stone wall was found at the entrance of the cave, showing likely human habitation, no more clues were forthcoming.
Text from the original article reads as follows:
"While the historical features of the Ozarks held our attention, by far the most fascinating discovery was one made by an aged recluse and naturalist who for ten years had lived in a shelter cave near where we camped.
'Dad' Riggins spent much of his time digging in the ashes which form the floor of many of these caves.
At a depth of more than three feet he found the remains of several giant human skeletons, including an almost perfect skull which differed in many particulars from a modern specimen. When partly joined the largest skeleton was almost ten feet tall.
'Dad' Riggins showed us hieroglyphics covering the Palisades thought to be thousands of years old."


2. Lompock Rancho, California, 1819 - 12 ft skeleton Hugh investigated this famous report back in November 2008, by visiting the area of the ranch it was discovered on.
"In 1819 an old lady saw a gigantic skeleton dug up by soldiers at Purisima on the Lompock Rancho. The natives deemed it a god, and it was reburied by direction of the padre." 8
This short report re-emerged with a broader range of details in 1833 and now various authors and websites repeat the same story.
It goes something like this:
Soldiers digging a pit for a powder magazine at Lompock Rancho, California, hacked their way through a layer of cemented gravel and found a 12ft sarcophagus.
The skeleton of a giant man about twelve feet tall was found inside. The grave was surrounded by carved shells, huge stone axes, two spears and thin sheets of porphyry (purple mineral with quartz) covering the skeleton.
These were covered with unintelligible symbols. He had a double row of teeth, both upper and lower.
The soldiers consulted a local tribe of Indians, who after going into trance, exclaimed they were geographically displaced Allegewi Indians from the Ohio Valley area.
When the natives began to attach some religious significance to the find, authorities ordered the skeleton and all the artifacts secretly reburied.
No further information is available so it is impossible to verify this information, but numerous other skeletons of this height have been reported in such newspapers at The New York Times.
Two further 12ft examples were reported in Jeffersonville, Kentucky ( The New York Times, May 22, 1871) and Barnard, Missouri ( The Providence Evening Press, September 13, 1883).
Furthermore, a 13ft example was said to have been unearthed in Janesville, Wisconsin (The Public Ledger, August 25, 1870) and even bones that were estimated to be from a skeleton 14ft tall at Etowah Mounds (The New York Times, April 5, 1886).
These are all well out of the normal range for humans but are worth noting here as these immense sizes pop up again and again in well-respected newspapers.


1. West Hickory, Pennsylvania, 1870 - 18ft skeleton The headline of this chart-topper reads: "The Cardiff Giant Outdone: Alleged Discovery of a Giant in The Oil Regions."
This report originally came from the Oil City Times in 1870 and underneath the immense armor, it revealed some startling anatomic oddities, and a skeleton that reached a staggering height (the tallest example we have come across):
"They exhumed an enormous helmet of iron, which was corroded with rust. Further digging brought to light a sword which measured nine feet in length."
The report continued that they had discovered:
"…a well-preserved skeleton of an enormous giant… The bones of the skeleton are remarkably white. The teeth are all in their places, and all of them are double, and of extraordinary size."
It was estimated to be 18 feet tall, and the bones were being prepared to be sent to New York. Clearly, however, this could be an exaggeration, as 18ft is unheard of in the historical record, but the matter-of-fact description is intriguing.
Interestingly the discovery was reported to be buried 12 feet below a mound, so it could suggest a deep antiquity, however tall he was.


The report from 1870 describing an 18-feet-tall giant skeleton.

We hope this tiny selection of accounts leaves one realizing there may be some truth to these reports (although numbers 9 and 10 cannot be verified, and they are well beyond the established scope of human height).
We do not believe they are all authentic, but what you have read here constitutes only 1% of what we have in our archive. We include 250 of these accounts in our book 'Giants On Record: America's Hidden History, Secrets in the Mounds and the Smithsonian Files.'
The genesis of the North American giants is shrouded in mystery, but we believe that they were involved in the sophisticated Mound Building cultures of the Mid-West, as royal tombs with reported enormous skeletons were often found within them.
There are many Native legends that place them in the era of the Megafauna (mammoths, mastodons, sabre-tooth tigers etc.) at around 13,000 years ago. There are dozens of oral histories that revere them as gods, and sometimes as fearsome cannibalistic warriors.
Great wars were said to have taken place between these titans, and prehistoric battlefields with oversized bones and weapons were frequently reported by early colonial farmers.
Eyewitness accounts of live giant giants were reported by English and Spanish explorers and even some of the early presidents.
Mystics such as,
...as well as the Rosicrucians and Freemasons all regarded giants as a reality.
The origins of the North American giants are hotly debated by independent researchers, academics and skeptics, but there is now enough data to begin serious research into the subject.
We cover all the theories of their origins in our new book, ranging from the Denisovans of Siberia to the Nephilim of the Bible Lands.
There is also compelling evidence that the giants may have originated within the Americas. Hundreds of Native American creation myths and oral histories attest to this, with the giants being mentioned in the stories from remote times.
One example can be found in the writings of Tuscarora Indian David Cusick in his book 'Sketches of Ancient History of the Six Nations' (1825). He states that when the Great Spirit made the people, some of them became giants.
However, most people don't believe in giants, but rather scoff at the idea, saying it's all just folklore that got mixed up and sensationalized by newspaper journalists.
We disagree, as there is ample evidence within,
Native American mythology
...to suggest otherwise.
Now is the time for academia to take a look at this data, and to investigate what really happened at the Smithsonian, as an important chapter in human history is on the verge of being lost forever.
References
Wilkins, Fate Magazine, January, 1952 Don W. Dragoo . Mounds for the dead. Annals of Carnegie Museum, Vol. 37. McDonald and Woodward / Carnegie Museum.1963. p.72 The World, October 7, 1895 Giants On Record: p.128 The Pittsburgh Press, July 20, 1913 Ogden Standard Examiner, Sunday, November 10, 1929, pg.32 The New Age Magazine, Volume 18, 1913, pg.207 Hubert Howe. The Native Races of the Pacific states of North America. 1875 Jeffrey Goodman Ph.D. American Genesis: The American Indian and the origins of modern man. Summit Books. 1981
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2020.11.24 16:20 Perryapsis The Distribution of Votes and Outlier Analysis of the AP Poll (Week 12)

TABLE

Sorry for being late this week. Excel threw a pre-emptive fit that no G5 team will be ranked in the top 10 by the playoff committee and had to be consoled before it would make the tables this week. Anyway...
HOW TO READ THIS TABLE
Teams are ranked in their order from the AP Poll for the current week. The column to the right of the team name shows the number of points that team received using the AP Poll's Borda Count rules. The following columns show how many votes for each ranking the team received. The "U" column shows how many voters left the team off their ballots entirely. Gridlines are placed every 5 lines for ease of reading. A double-line is placed below the 25th-ranked team to distinguish "ranked" teams above it to "receiving votes" teams below it.
Some cells are shaded to highlight points of interest. The green diagonal highlights how many voters ranked a team exactly where they ended up in the overall poll. For example, flair Miami is ranked 10th in this week's poll and 15 voters placed Miami in their 10th spot. Values for which a team received no votes at that rank are shaded in red, while placements chosen by only exactly one voter are highlighted in blue. The most common selection (the mode) for each team is shaded yellow. Votes that are more than three standard deviations away from the mean are considered outliers and outlined in with dashed red lines. Finally, since there are very few votes that ever end up near the top-right or bottom-left of the chart, those cells are filled in with black diagonally as much as possible without covering up any nonzero values. This helps naturally guide the eye while viewing the chart and helps identify outlying votes.
NOTES FOR THIS WEEK
The upper Wilner Diagonal was set by Jon Wilner himself, who left flair Oregon at 18th. This is the first week this season that the upper diagonal has not been set by some voter leaving another team unranked. The lower Wilner Diagonal is set by Jonas Pope ranking flair Florida Atlantic 21st, their only vote this week. A total of 62 votes were cast for receiving-votes teams amounting to a total of 138 points (0.7%). 518 votes matched their team's rank exactly this week (e.g. putting the 10th place team at 10, 20th place at 20th, etc). flair Oregon has the largest disagreement between voters this week with a standard deviation of 2.38. This is way less than in previous weeks. This week's poll has an unusual amount of consensus: there are only 9 receiving-votes teams, and only flair Washington received any votes above 20th amongst that group. There are only 15 total outlying votes for ranked teams, 4 of which are people leaving flair Texas unranked. Alabama is the first consensus #1 of the year. Only 8 teams are receiving top-4 (e.g. playoff caliber) votes: the actual top 4 along with flair Texas A&M, flair Florida, flair Cincinnati, and flair Brigham Young. Similarly, there are only 16 teams receiving top-10 votes. So despite the relative uncertainty of team strength this season, the pollsters seem to have made up their minds about who is who. With more and more games being cancelled, it remains to be seen whether any of these top teams will drop for missing games, or if they will need to lose for anyone to change their minds.
OUTLIER ANALYSIS
Adjusted rankings
This follows the same methodology as my original analysis from the preseason poll. Not much to see this week. Like last week, there are no shifts among ranked teams. This will probably continue if the poll retains as much consensus as we have this week. Three teams get trimmed from the receiving-votes section, but that's basically it.
COLUMN ANALYSIS
Who is the best team to receive a last place vote? (Marshall) What is the worst team to receive a top 5 vote? (Oregon) This table isn't pretty (yet), but here's the raw data.
AUSTRALIAN POLL
Why not flip all the votes upside down for fun and chaos? Then the goal is to be ranked as low as possible on each ballot, but not get left off of any ballots. This results in a silly ranking, but screw it, why not? flair Oklahoma State tops the Australian Poll this week.

Flipped-votes rankings

ACKNOWLEDGEMENT
I would like to thank u/bakonydraco for providing the data set for this table.

TABLE

No shading

Outlier-adjusted rankings

Column extremes

Flipped-votes rankings

submitted by Perryapsis to CFB [link] [comments]


2020.11.23 16:25 LeeNobody A compelling, concise and competitive 15 team ACC schedule with supporting data

The ACC current divisional alignment are poorly constructed. Schools less than 30 minute drive apart are in separate divisions. Division are geographically vast. Florida State is in the same division as Louisville and Boston College. Numerous teams have 4 our more preferred annual games. Competitive balance has never been close to even in the ACC. Forced divisional rivalries have been uncompelling, and lackluster to fan bases. I have devised a superior schedule that addresses all these concerns.
The Current ACC
With the Coastal and Atlantic divisions, each ACC team play 6 divisional opponents +1 permanent rival +1 rotating rival for a total of 8 conference games. With only one rotating team it will take a team 6 years to play every team, and 12 years to play at every stadium. This is simply not enough rotation, but adding a 9th conference game would hurt the 4 ACC teams with permanent ACC-SEC rivalries, reducing those teams' ability to schedule non-conference games.
A Better ACC Schedule
The answer is to group conference teams into geographically concise unit called pods. The ACC can be divided into 3 pods of 5 teams. The pods are based in concise geography would look like this with composition below:
Southern Pod Coastal Pod Northern Pod
Georgia Tech Duke Louisville
Clemson North Carolina Notre Dame
Florida State NC State Syracuse
Virginia Tech Virginia Boston College
Miami Wake Forest Pittsburgh
Yearly each team would play every member of it pod (4 opponents in its column), 2 cross pod rivals (team in its rows) and two rotating teams from the rest of the conference for an 8 conference game schedule. With this rotation it will take 4 years for every team to play each other at least ones, and eight years to visit every stadium at least once. The breakdown of annual opponents is as follows
Team Annual Pod Opponent Annual Pod Opponent Annual Pod Opponent Annual Pod Opponent Annual Cross Pod Opponent Annual Cross Pod Opponent
Georgia Tech Clemson Florida State Virginia Tech Miami Duke Louisville
Clemson Georgia Tech Florida State Virginia Tech Miami North Carolina Notre Dame
Florida State Georgia Tech Clemson Virginia Tech Miami NC State Syracuse
Virginia Tech Georgia Tech Clemson Florida State Miami Virginia Boston College
Miami Georgia Tech Clemson Florida State Virginia Tech Wake Forest Pittsburgh
Duke North Carolina NC State Virginia Wake Forest Georgia Tech Louisville
North Carolina Duke NC State Virginia Wake Forest Clemson Notre Dame
NC State North Carolina Duke Virginia Wake Forest Florida State Syracuse
Virginia North Carolina Duke NC State Wake Forest Virginia Tech Boston College
Wake Forest North Carolina Duke NC State Virginia Miami Pittsburgh
Louisville Notre Dame Syracuse Boston College Pittsburgh Georgia Tech Duke
Notre Dame Louisville Syracuse Boston College Pittsburgh Clemson North Carolina
Syracuse Louisville Notre Dame Boston College Pittsburgh Florida State NC State
Boston College Louisville Notre Dame Syracuse Pittsburgh Virginia Tech Virginia
Pittsburgh Louisville Notre Dame Syracuse Boston College Miami Wake Forest
Note that annually games cover every trophy or named ACC rivalry except BC vs. Clemson, the most forced of rivalry games. These are games that each fanbase would get excited about, and have been sorely neglected. The breakdown of rotating opponents is as follows:
Team Y1 Opponent Y1 Opponent Y2 Opponent Y2 Opponent Y3 Opponent Y3 Opponent Y4 Opponent Y4 Opponent
Georgia Tech North Carolina Notre Dame NC State Syracuse Virginia Boston College Wake Forest Pittsburgh
Clemson NC State Syracuse Virginia Boston College Wake Forest Pittsburgh Duke Louisville
Florida State Virginia Boston College Wake Forest Pittsburgh Duke Louisville North Carolina Notre Dame
Virginia Tech Wake Forest Pittsburgh Duke Louisville North Carolina Notre Dame NC State Syracuse
Miami Duke Louisville North Carolina Notre Dame NC State Syracuse Virginia Boston College
Duke Miami Pittsburgh Virginia Tech Boston College Florida State Syracuse Clemson Notre Dame
North Carolina Georgia Tech Louisville Miami Pittsburgh Virginia Tech Boston College Florida State Syracuse
NC State Clemson Notre Dame Georgia Tech Louisville Miami Pittsburgh Virginia Tech Boston College
Virginia Florida State Syracuse Clemson Notre Dame Georgia Tech Louisville Miami Pittsburgh
Wake Forest Virginia Tech Boston College Florida State Syracuse Clemson Notre Dame Georgia Tech Louisville
Louisville Miami North Carolina Virginia Tech NC State Florida State Virginia Clemson Wake Forest
Notre Dame Georgia Tech NC State Miami Virginia Virginia Tech Wake Forest Florida State Duke
Syracuse Clemson Virginia Georgia Tech Wake Forest Miami Duke Virginia Tech North Carolina
Boston College Florida State Wake Forest Clemson Duke Georgia Tech North Carolina Miami NC State
Pittsburgh Virginia Tech Duke Florida State North Carolina Clemson NC State Georgia Tech Virginia
The rotating opponents are scheduled to allow for every team to see each other in four year and help create greater competitve balence. Notice Clemson's rotating opponents are historically weaker teams, as Clemson has strong pod and cross pod annual games. On the opposite side Wake Forests's rotating opponents offset the lake of strength in Wake Forest's pod .
Competitive Balance
With rotation listed above, I gathered the SP+ average for each team since 2014-15 season, the first ACC year for all conference members. I compiled the average opponent SP+ for each team in each year of the schedule. The data is compiled here. Georgia Tech Year 1 has the hardest schedule with an average conference opponent SP+ rating of 9.97. NC State YR 4 has the easiest schedule with an average conference opponent SP+ rating of 2.76. Over the 4 year schedules, teams average opponents SP+ ratings range from 8.22 (Georgia Tech) to 4.03 (NC State). I believe this schedule is far superior as the differences is strength of opponents scale with historic quality of the teams. I.E Blue bloods get schedules that are a little harder, cellar dwellers get schedules are a little easier. I think the schedules are balanced well, and better than alternatives.
How will you Deal with Conference Championship Game?
Until Conference Championship Games (CCG) are deregulated, the NCAA requires either divisions or Round Robin. In 2020, this requirement was waived. I hope that this will continue and as a result the best two records could meet in the CCG. If not ditch the CCG let the ACC crown a champ. We could even have a last week matchmaker game where all teams match up 1 vs 2, 4 vs 3, .. till 13 vs 14 with 15 sitting out, similar to what the B1G and Pac12 are attempting this year.
TL;DR: In first table each team would play every member of it pod (4 opponents in its column), 2 cross pod rivals (team in its rows) and two rotating teams from the rest of the conference for an 8 conference game schedule. With this rotation it will take 4 years for every team to play each other at least ones, and eight years to visit every stadium at least once. Third table shows cross pod yearly rotations.
submitted by LeeNobody to ACC [link] [comments]


2020.11.22 06:33 CornQoQo Data-Dump: When Do Coaches Leave & How Long To Turn Around A Program

Foreword

This is a long-winded post and is full of a bunch of data I assimilated from sources when I was bored. This post is not to pitch my opinion or to convince anybody. It is simply a data dump of information publicly available to stimulate conversation and contribute to the community. I am not attempting to peddle my opinion regardless of the data. I collected it to simply gauge what it says.

This is a two-part post I put into one. This first segment is rather shoddy as I wrote it up in about 25 minutes during the absolute shellacking we took this week against Illinois. If you want to skip the first section I don't blame you. It's haphazardly put together. I will post a TL;DR at the bottom of each section.

Part 1: When Do Universities Dump Coaches?


I will commence my data-dump of seemingly useless information regarding an assortment of teams and when they fire coaches. I started this endeavor once the "Fire Scott Frost" train started picking up some localized steam in the Nebraska fanbase.

Before we begin let me set the criteria for my selection of teams. I am taking a look at an assortment of 30 teams across the varied power landscape that is CFB. I have three groups:

The Greats:

Teams: Winning Percentage
Ohio State .730
Notre Dame .729
Michigan .728
Alabama .728
Oklahoma .725
Texas .704
USC .699
Nebraska .689
Penn State .687
Tennessee .673

Average Joes:

Team: Winning Percentage
North Carolina .559
Navy .555
California .551
Missouri .545
Ole Miss .545
Iowa .540
TCU .539
Oklahoma State .520
Virginia .520


Bottom-Dwellers:
Team: Winning Percentage:
Mississippi State .492
Vanderbilt .490
Kansas .472
Oregon State .471
Iowa State .455
Kansas State .455
Northwestern .452
Tulane .452
Indiana .423
Wake Forest .415


How these teams were chosen: I wanted an array of teams that covered the elite, the middle-class, and those that just are not very good. We have 10 teams per category. The entire collection of teams across CFB were sorted based on their overall winning percentage as seen on Winsipedia. Before I sorted the teams I had already thought to myself I didn't want to use teams like App State, Boise State, Coastal Carolina, et al, that have few wins at the Division 1-FBS level. I decided to add up all teams' total amount of games played and found the median: 1163. For a team to be selected they must have a greater than or equal amount of wins to this number. After that, I simply selected the top-10 teams for the first group. The second group was selected as the middle-ground number of 65, which was Ole Miss. They are the 65th highest winning percentage team in CFB out of 131 teams. I used them as the center and selected an even amount of teams above them and below them that also had a greater than or equal amount of games played as compared to the median figure of 1163. Next, we go to the bottom of the list and work our way up. We get rid of teams like Charlotte, Georgia State, Kent State, et al, who have not played the required total of 1163 games.

A quick note: There are several teams I could have included that were almost at the 1163 mark, or within a handful but I chose not to. Why? Just because. No rhyme or reason really. As an example: Rice has 1135 wins and could have been included in the Bottom-Dwellers but I decided to stick with a requirement of 'more' than the median for a larger game n= sample.

I also had to deal with the fact that season length is not the same for every year. How do you value a year in 1910 when a team may have only played 8 games, but in 2010 they may have played 12? My shoddy solution: judge coaches based on total games and then simply define a "year" as 12 games. The problem with this is the fact the "years of good coaching" may not actually line up with the total amount of years said "good coaching" may have actually been with the team. It still however matches the total amount of games if you simply multiple the "year" value by 12. Bottom line: A "year" is 12 games. Enough said about that.

Next, we have to determine what "good" and "bad" are. I once again went back to Winsipedia and sorted the teams once by winning percentage and picked the top-25 as my barometer. If a team is inside the top-25 we usually consider them to be "good", yes? So why not here. Thanks, Texas A&M, for setting our "good" baseline. If a team has a winning percentage equal to or higher than Texas A&M's (.604) we will consider them to be good.

A quick note: I lowered the bar to .600 instead of their actual .604 mark. Why? Because the team below them is at .599 and .600 makes my brain happy. Don't judge me.

To be an average team they must be above .500, but below .600. To be bad the team must be below .500 with no floor. This gives us the three groupings of:


Good >= .600
Average >= .500 & < .600
Bad < .500

With the pageantries out of the way let's get to the data. What does it tell us? Absolutely nothing we could not have already figured out with 5 seconds of critical thinking.

The short and skinny: Good teams hire good coaches and minimize years with bad coaches. Average teams are average in terms of having good/average/bad coaches. They tend to hold onto "bad" coaches longer, however. Bad teams: Bad. They tend to hold onto bad coaches the longest and have good coaches for fewer amount of years due to varying reasons.
Quick Note: This does not differentiate between firings, retirements, poached coaches, or other varying reasons a coach and school may part ways. This includes any and all forms of parting.

Here's the data!


The teams are sorted by overall winning percentage to give us a quick look at overall power. We can immediately notice that there is only one team that is in the "elite" category of winning percentage (>.600) that has historically held onto bad coaching for more than 3 years and that would be Notre Dame. With that one exception noted, there is not a single elite-level team that would hold onto a coach with a below .500 record for 3 years or longer. In short: Good teams do not put up with bad coaching and that is the reason they are historically good.

On the opposite end of the spectrum, we see the inverse is true. Bad teams almost exclusively hold onto bad coaches for 3 years at a minimum. They "ride or die" with their coaches and thus it costs them more wins over a longer period of time. Hence, an overall worse winning percentage due to having worse coaches for longer. Who would of thunk it?

WAIT A MINUTE! This is taking into account the early 1900s where the game had completely different rules! Coaching was sometimes done by player-coaches, and it wasn't taken as seriously as it was now! This is bad data!

.....you got me. You are right. Let's then look at only the "modern era' of college football and see how that changes the data. To do so, we must first define what the modern era is. The general consensus is that it's undoubtedly after WWII, and most say at around the late '70s, or early '80s. This is when the transition to scholarship limits and the transition to Div 1 and Div 2 (FBS/FCS) took place. Combine this with the fact that television rights took off in the '80s and programs started to actually take the game seriously points to a common answer being the year of 1982 to be the unofficial "Modern Era of College Football". With this in mind, we must account for coaches who coached both during the year 1982, after, and of course, before. I haphazardly decided to let the entire coach's tenure count as long as they coached during the 1982 season. This means coaches like Bear Bryant of Alabama get their entire tenure counted even though his last year was...1982. This happens a few times and it does alter the data slightly but not enough for me to change the implementation. So here is the data if we are only counting coaches who coached during the modern era of college football (and all their games prior) in the years 1982 and after!

The Modern Era Version


Quick Note: This version is sorted by bad years instead of winning percentage.

How does this change our perspective of the data? It really doesn't. We can still see the teams who have never had a good coach are near the bottom right where we expected them to be. Teams at the top who have never had bad coaches are also expected like Alabama, Notre Dame, USC, and even Penn State who had Penn State for an eon; instances like Paterno are also seen at Iowa who is seemingly the "top team" at retaining elite level coaching. In reality, it's because their number of coaches is a grand total of 2 since 1982. Fry followed by Ferentz. No one else. That's it. However, the previous data statements still hold true: Good teams have good for longer while minimizing time with average or bad coaches.

Overall what this data really tells me is that teams must not hire bad coaches; and if they do, do not hold onto them for more than about 3 years. Once again, not a single team with a winning percentage above .600 is seen having a bad coach for much longer than 3 years. This also shows us that parting ways with a coach after 3-4 years is not as uncommon as many fans think it is. I see a lot of speak about "give them time" but in reality that isn't what is done. The teams who hold onto their bad coaching for longer are statistically at the bottom of every list I find. While it begins with hiring good coaches in the first place, it also transitions into minimizing time with the worst.

You can see additional data from BannerSociety that also shows coaches stay 3.9 years on average (Data: 2005-2014). Saturday Down South collected data on SEC coaches since the start of their programs and you can once again see the most dominant conference in college football has had coaches for...~4 years on average.

What really matters is hiring the right coach. I am currently putting together an actual analysis that isn't shoddily put together in 25 minutes about the top tier coaches and how we identify them. Stay turn for that either later tonight, or tomorrow (hopefully).

TL;DR Teams will dump coaches roughly every 4 years. Good teams hold onto good coaches, bad teams hold onto bad coaches. Moral of the story: Hire a good coach to begin with.


Part 2: How Quickly Does A Coach Turn A Program Around?

This post is an actual review of coaching talent and how we can identify it, if at all. It is an addendum to my previous post about how long coaches are at their universities. Once again, we will be looking only at coaches in the "modern era" which we previously defined as 1982; however, we will only be viewing seasons from 1982 and not the coaches' previous seasons like we did last time.

The Set Up:

Here is a list of all coaches and their overall winning records for all Division 1 FBS teams since the 1982 season. If this information is inaccurate I apologize. My source for this data is the absolutely fantastic CollegeFootballData API located here. If you have never used that API I highly recommend it, although it is not perfectly accurate at all times.

Quick Note: This list is sorted by overall winning percentage. We can effectively ignore the individuals at the top of the list who have never coached a game, or have only coached a few and won them. The green "YES" next to their name indicates whether they have coached for at least 48 games or 4 years' worth. With this in mind, we can notice the greatest coach in terms of overall winning percentage that has coached for at least 4 years is....Coach Tom Osborne of Nebraska fame.

Next, we want to determine which coaches we're going to take an in-depth review of. We'll eliminate coaches like Day of Ohio State, Drinkwitz of App. State/Missouri, Riley of Oklahoma, et al because they simply do not have a large dataset to go off of. We're going to be looking at those coaches with a high overall winning percentage and we'll look at some of the top coaches since 1982, some middling coaches, and a few...not so good ones.

The Metrics:

We will compare the coaches to their predecessors and determine whether the increased, decreased, or maintained the status quo of their programs during their runs. We will also keep a note of how quickly we can objectively say they were improving. In other words, how many years until we saw the win total go up!

Up to bat first is good 'ol Urban Meyer! Come on down!

URBAN "HEART ACHE" MEYER

Mr. Meyer got his first start as a head coach with the Bowling Green Falcons. Bowling Green has a total winning percentage of .572 including Meyer's time. Urban took over the head coaching vacancy in 2001 following the work done by Gary Blackney who coached with them from '91-'00. Blackney is an interesting starting point because he took over for Moe Ankney. Mr. Moe had a winning percentage (hereby noted as WP) of .398. Blackney immediately improved upon that by winning 11 and then 10 games in his first two seasons. However, he would finish with a WP of .544. A decent clip, but below Bowling Green's historical figure and far from elite. His hot start would end in shame and he would ultimately quit his duties. Meyer enters for two years and accomplishes 8 and 9 wins for a WP of .739. While not as elite as Blackney's start, it is still really good considering where Blackney left the program and was in an immediate improvement. Winning as many games in just two years as Blackney accomplished in the previous 4 and a half years. This qualifies as an immediate improvement and it did not even take a transition period.
The Fighting Bowling Green Meyers:
Transition: None
Improvement: Yes
Length: 2 Years
WP: .739
Continued: No
Meyer's success would be noted by Utah where he would move on to be the new head coach. Meyer is replacing Ron McBride who coach at Utah for 13 years with a WP of .582. Utah has a historical WP of .593 so McBride's figure is nothing to write home about. Meyer enters and immediately wins 10 and then 12 games in his two years at Utah for a WP of .917. Once again, Meyer strikes.
The Raging Utah Meyers
Transition: None
Improvement: Yes
Length: 2 Years
WP: .917
Continued: No
Note: Meyer's successes at BGSU and Utah were not followed up with success by his successors. The drop was instant and noticeable once he left. This gives credence to the fact that Meyer was responsible.
Meyer is finally on the big-boy radar and gets picked up by Florida. The year is 2002 and Florida is coming off a coaching high that was Spurrier. Stevie posted a WP of .817 and a national championship. He is followed by Ron Zook and his .605 WP. While not terrible, it is an extreme reduction in what UF is used to, so after 3 years he is replaced by Meyer. In his first year, Meyer wins 9 games which are more than Zook managed in his 3-year stint. Meyer follows this up with a national championship in year 2 and finishes his heart-filled career at Florida with two national titles and a WP of .850. This figure is an immediate and drastic improvement upon both Zook and the legendary Spurrier. Also noted is the fact that Florida's historical WP is .633. Meyer would be followed by Will Muschamp who posts a WP of .580 while at Florida. This means his success was his own and not continued by his successor.
Hearty Florida Meyer's
Transition: 1 year
Improvement: Yes
Length: 6 Years
WP: .850
Continued: No

Meyer isn't done yet.. He takes a gap year and then returns to coaching with Ohio State following in the footsteps of Jim Tressel. Tressel posted a WP of .828 and is above their historical WP of .730. (Counting vacated wins). Urban boat races his competition and goes undefeated in his first year and never loses more than 2 games in his 7 year OSU career. He finishes with a WP of .905. An improvement on both Tressel, and the interim Luke Fickell and is well above the OSU historical WP.
Poisonous Ohio State Meyer's
Transition: None
Improvement: Yes
Length: 7 years
WP: .905
Continued: TBD (Only 1-year post-Meyer)
We can plainly see Meyer is elite. No one is really questioning that. However, it does set up a sort of upper limit of achievements. Meyer has turned around every program he has ever been to and done so immediately, or with very little amounts of transition years. Meyer shows that elite coaches will immediately improve a team and start to win games.
---

Additional Elite Coaches

To save you the boredom of having to listen to my spiel about every single coach (as well as save me time) I will now do the same for some more top-tier coaches but only with the metrics we listed. Here they are:


Coach Team Improvement Transition Years Tenure WP Continued
Pete Carroll USC Yes 1 9 .789 No
Jim Tressel Ohio State Yes 1 10 .828 Yes1
Gene Stallings Alabama Yes 1 7 .810 Push
Dabo Swinney Clemson Yes 3 13+ .811 -
Bob Stoops Oklahoma Yes 1 18 .798 Yes
Chris Petersen Boise State Push 0 8 .885 Yes
Nick Saban Alabama Yes 1 14+ .874 -
Kirby Smart Georgia Slight 1 5+ .774 -
Bob Pruett Marshall Yes 0 9 .803 No
Jimmy Johnson Miami Yes 1 5 .852 Yes
Bryan Harsin Boise State Push 0 7+ .788 -
Gary Moeller Michigan No - 5 .733 -
Jimbo Fisher Florida State Yes 0 8 .783 No
LLoyd Carr Michigan Slight 2 13 .753 No
Vince Dooley Georgia Yes 2 25 .715 No
1 - There was continued success after Luke Fickell's interim year
What does this tell us? These are the top-16 coaches in college football history by WP (not including coaches prior to the 1982 season). Every single one of these coaches took 3 transition years or fewer to turn their programs around completely, increase their status, or maintain the status quo. Only one coach, Moeller, is someone I'd consider to not have "improved" his team's situation. Smart and Carr slightly improved their already good teams. Petersen and Harsin of Boise State I don't believe really improved their programs - they were already good and remained good. Half of the coaches left the program and they got worse immediately following. Short point: Elite coaches do not need more than a few years to show you why they are elite. The turn-around will be near immediate and it will be grand as all these coaches have a WP of .715 or higher with their respective programs. All these coaches also have a career WP of .750 or higher.

Mid-Tier Coaches


How about non-elite coaches? Let's take a look at some above-average, or average coaches and see how they fare.


Coach Team Improvement Transition Years Tenure WP Continued
Bo Pelini Nebraska Yes 0 8 .713 No
Tom Herman Texas Yes 1 3+ .625 -
Les Miles LSU No - 12 .770 -
Paul Chryst Wisconsin Yes 0 5+ .761 -
Mike Gundy Oklahoma State Yes 3 15+ .673 -
Bill Snyder Kansas State Yes 1 27 .647 No / Push2
Mark Dantonio Michigan State Yes 0 13 .667 N/A3
Dan Mullen Mississippi State Yes 1 8 .600 No
Dan Mullen Florida Yes 0 2+ .818 -
Ken Niumatalolo Navy Slight 0 14+ .612 -
Luke Fickell Cincinnati Yes 1 3+ .723 -
Matt Campbell Iowa State Yes 1 4+ .543 -
Matt Campbell Toledo Yes 0 3 .700 No
Art Briles Houston Yes 1.5 5 .548 Yes
Art Briles Baylor Yes 2 8 .637 N/A4
Jeff Brohm Purdue Yes 0 3+ .452 -
Jeff Brohm Western Kentucky Yes 1 3 .750 No
Paul Johnson Georgia Southern Yes 0 5 .861 No
Paul Johnson Navy Yes 1 6 .608 Push
Paul Johnson Georgia Tech Yes 0-15 11 .573 No
Scott Frost Nebraska No - 3+ .375 -
Scott Frost UCF No6 1 2 .684 Yes
2 - Snyder had two separate stints at Kansas State. Opinions for 1st and 2nd stint listed.
3 - Dantonio and Michigan State only separated ways in 2019.
4 - Art Briles scandal at Baylor. An odd situation to judge; however, I'd say no. It was reinvented by Rhule.
5 - Subjective. I do believe he transitioned smoothly without a gap year.
6 - Subjective. UCF had a coach retire mid-season and they went 0-12 to make the turn-around look more impressive.
So it seems the truth is still the same for mid-tier coaches. If they will turn around teams then they will do so within 2-3 years. None of the coaches I selected took more than 3 years to turn their programs around. These coaches were chosen at random going down my list. There was no rhyme or reason to choosing their names outside of a few selects being chosen simply based on name popularity.
If we combine this information with the information we already know being that teams part ways with their coaches on average every 4 years or so it makes sense; because teams will see improvement or not within those 4 years and be able to decide if a coach is worth keeping or ditching.

TL;DR It takes 3 years or less (usually less) to turn a program around. If success is not seen within 3 years it usually will not happen. There are of course outliers but I found NONE in the random couple dozen coaches I chose to look at.

---
This post is NOT to call for a firing of Head Coach Scott Frost. It is simply a data-dump of my boring weekend to stimulate conversation in this sub. I do have an opinion on whether Frost is the answer but this information was simply gathered to see what it showed - not to prove a point. If there are any data errors please let me know. There probably is as both the API I use to scrape information from is sometimes inaccurate and I am only one man and make errors. I also know there are already some errors, especially in the coaching section as the API did NOT pull all head coaches in the early years. Alas, I didn't fix it as the resulting data change was negligible for a simple Reddit post.

---

If you would like to analyze the data yourself I have uploaded both the historical and 1982+ versions to Google Drive for your viewing and analysis. They are available here. You are free to download, utilize, and change it. Keep in mind these were made using Microsoft Excel and use formulas and interactions specific to Excel and it will more than likely NOT look accurate in Google Sheets. Specifically nestled functions such as the VLookup nestled Matrix function I used for the coaching section. You have been advised.
submitted by CornQoQo to Huskers [link] [comments]


2020.11.20 12:03 remote-enthusiast List of 84 remote jobs - (non)tech

Hello friends! These are the open remote positions I've found that were published today. See you tomorrow! Bleep blop 🤖
submitted by remote-enthusiast to remotedaily [link] [comments]


2020.11.19 01:37 BeLikeLeBron WELCOME! READ ME: SLASH DIABLO TOOLS, TIPS, AND UPDATES

Welcome to Slash Diablo - the community run, vanilla-like, Diablo II private server.

RECENTLY ADDED FEATURES

SLASH DIABLO DIFFERENCES COMPARED DIABLO 2 LOD

  • No Botters, realm down, no perming, no expiry, real trading economy. Ladder resets every ~4 months.
  • NoDrop=0. Every monster drops something.This effectively makes drop rates slightly better (or easier) in comparison to Battlenet or Single Player.
  • Use up to 4 instances, SlashBH(maphack), robust default item filter, Approved High Resolution Mod
  • Plague Runeword enabled (cleansing aura, 1-2 skills)
  • Dclone spawn for Anni: Gul rune + Tp scroll in cube=herb, sell herb to vendor in a hell game.
  • Progressive item filter with on the fly filter levels and notification ping tiers
  • Everyone can chat globally while playing in different games. Type //sub chat and use like so //c hello
  • Multiple Game servers! Play on a game server closest to you for less lag! To use type GS# in the description field when creating a game (i.e: GS4 for Seattle). See above for list of servers.
  • All trading is done either in game with our global chat feature, on our Discord, or in this subreddit. Highly recommend joining our Discord because of this.
Rules
Don't be a dick, don't bot, 4 connections max per IP, no third-party trading. Details here

SLASH TOOLS

Websites
In-game tools
Reddit tools

SETUP AND INSTALL GUIDE

WINDOWS
1) Download & Install Diablo II & Diablo II LOD straight from Blizzard here. It is your responsibility to provide any CD keys during installation.
2) Download & Install the Slash Diablo Launcher
3) Setup the Launcher Open the Slash Diablo launcher. Click settings, Add Diablo II Install, point it to your installed Diablo II folder, read and set your options (more info below), hit done, update, and play!
Recommended Settings:
  • Launch Parameters: -w
  • Instances to Launch: 1 for testing, then go to 4 if you want 4 to MultiBox
  • Maphack Version: 1.9.9
  • HD Mod Version: HD 2.0
    • HD Mod Version 1.0 - Max resolution of 1344x700, window resize bug, no performance fixes
    • HD 2.0(Recommended) - Max resolution of 1068x600, window resize bug fix, general video performance/glide fixes
  • Override Maphack Config: off
  • After entering a game hit esc, options, video options, click resolution to increase to a higher resolution.
Want full screen?
Option 1 for fullscreen is to just hit the maximize button after you enter a game with the recommended settings above. It will look like this
Option 2 gives actual fullscreen like this with the recommended settings above, but requires the use of Glide:
 In the launcher enable -w and -3dfx Go into your `Diablo II` folder open `glide init.exe` and select these settings: Settings Tab: Window Mode Windows Extra No Static Size Render Tab: 10MB Texture Memory 4069x4069 Buffer Texture Memory Then launch the game via launcher, create a game, then you can now use Alt+Enter to toggle back and forth from full screen 
MAC/LINUX
This guide is used for Linux, but can also be used for mac
Another Mac method to install here
You can also use the launcher, simply extract this zip file after installing D2 & D2 LOD on Mac/Linux and follow step 3 above
LEGACY SETUP GUIDE To setup manually click here

MAPHACK v1.9.9 GUIDE

Included with Slash Launcher installation
TIER SYSTEM!!!! - By default the filter is set to filter level 0. IT IS RECOMMENDED TO make sure you have ping level set to 6 and filter level 0 at start of ladder and change it as you progress through the game. Set it in-game (Example)

COMMON ISSUES

  • When exiting Diablo 2, two errors pop up The two errors that occur on exit when quitting D2 are normal. You can avoid the errors by closing diablo 2 from task manager or using the file here to quickly close all Diablo 2 windows. We’re working on solving these soontm
  • I want to Install Slash Diablo, but also want to play on Battle.net
    1. Follow step 1 of the setup guide above, then create a copy of your Diablo II folder and rename it Diablo II Slash Diablo
    2. Follow step 2 of the setup guide above
    3. Follow step 3 of the setup guide above, but after clicking 'Add Diablo II install', select your newly created Diablo II Slash Diablo folder instead of the Diablo II folder. Read and set your options, hit done, hit update, then play! You now have a Diablo II folder for Battle.net and can use the launcher for playing Slash when you want.
  • Launcher shows "Unable to patch game files" Open task manager and end task on any diablo 2 processes hanging then try again. If you're still having issues, restart your PC and try again before launching D2.
  • Diablo II is not opening when I hit play This is usually due to an invalid path. Double check you have correctly pointed the launcher to your Diablo II folder, and that you installed BOTH Diablo II and Diablo II LOD.
  • C0000005 Error In the launcher, click settings, hit Run on Disable DEP. Reboot PC. You might have to reboot PC a few times to get this to work. Windows can sometimes be tricky with DEP. In the launcher, click settings, hit Run on Disable DEP. Reboot PC. You might have to reboot PC a few times to get this to work. Windows can sometimes be tricky with DEP. The full guide on every step on how to solve this annoying error can be found here
  • My map reveal isn't working even though I have it selected in the SlashDiablo Launcher settings Download and Install Microsoft Visual C++ Redistributable x86 (2015-2019) from Microsoft over here
  • Diablo 2 errors out when shift + clicking things or you see Loading MPQ data In the SlashDiablo Launcher, increase the launch delay above the play icon to a higher amount of seconds, restart all D2 instances. Might have to restart Diablo 2 twice.
  • Clicking Video Options errors out Close out Diablo 2 and download and run this file as administrator to fix.
  • Not seeing maphack options in-game Increase your resolution in game to see if it's visible then (esc, options, video options, click resolution). If not, download this file and put it in your D2 folder and relaunch. Create a game, shift+left click the "BH 1.9.9" menu when it's closed to move it wherever you please afterwards.
  • Monsters are not dropping any loot or loot isnt being filtered on the ground Our newest maphack has 'filter level' and notification ping tiers feature. CTRL + Left click the "BH X.X.X" box visible in game. Select the 'Item' tab up top, then select the filter level and ping level you desire. More information on this is available in this user guide. Filter level corresponds to the items you see on the ground, 0 filter level wont filter anything on the ground. The higher # the ping tiers the more notifications you will get on the top left when items drop.
  • My custom maphack config keeps getting overwritten when the launcher applies patches There's an option on your SlashDiablo launcher settings called Override maphack config. If you enable this the launcher won't download new maphack configs and leave your custom config on disk. The launcher downloads the default SlashDiablo maphack config if this setting is off. You can use old configs with the new 1.9.9 maphack version, but they wont take advantage of the new filters and pings features.
  • How do I edit the loot filter so items look the way I want? You will want to edit the BH.cfg file and turn on the "config override" button in the SlashDiablo launcher. Here's a guide on how to edit the config correctly. Check out the Maphack wiki and the Item Display Wiki for more info.
  • When running the Launcher, an icon shows up on my taskbar but no window appears Install DirectX from here
  • Why are the servers restarting and why do I see that message? For stability and reliability, all our servers are set to restart once every few hours and they only take about a minute to restart. Type //w to see when the next restart is. You can relax in the chat lobby for about a minute and it will be back up and ready to use fast. D2GS is the backend software we along with other private servers use, It has some memory issues that cause lag and drops if they aren't restarted often.
  • If you're still having trouble ask for help in the #help-and-support or #maphack-support channels. In our Discord
  • I want to Install Slash Diablo, but also want to play on Battle.net, and have somewhere to play Single Player PlugY on, and play X mod We Do not support PlugY or other mods, however, if you want to install them and have them be playable without issues, I'd do it this way:
 1. Follow step 1 of the setup guide above then create a copy of your Diablo II folder and rename it `Diablo II Slash Diablo` . Create another copy, rename it to `Diablo II PlugY` and another for whatever other mod you may want. 2. Follow step 2 of the setup guide above 3. Follow step 3 of the setup guide in above, but after clicking 'Add Diablo II install', select your newly created `Diablo II Slash Diablo` folder instead of the `Diablo II` folder. Read and set your options, hit done, hit update. 4. In Slash Diablo Launcher settings, click 'Add Diablo II Install', point it to the `Diablo II PlugY` folder, configure the settings for how you'd like PlugY to work (with or without HD Mod/Maphack etc.) , Update. Click Settings again, delete only `Diablo II PlugY` from the slash launcher by clicking the Trash Icon. This step patches to 1.13c required for PlugY as well as give you options to add HD Mod or maphack to it. 5. Install PlugY from the link here and point the installer to the `Diablo II PlugY` folder: http://plugy.free.fPlugY_The_Survival_Kit_v11.02.exe You now have a Diablo II folder for Battle.net, A PlugY folder for that, a mod folder for whatever else, and can use the launcher for playing Slash when you want. 6. For Plugy, Bnet, and Mod, you will need shortcuts with `-w` in the launch parameters and run them in compatibility mode. You will also have to change your `Install Path` in registry under `Computer\HKEY_CURRENT_USER\SOFTWARE\Blizzard Entertainment\Diablo II\` to the folder of what you'd like to play before launching. E.g. If you want to play PlugY, change the `Install Path` in registry from `C:\Program Files (x86)\Diablo II` to `C:\Program Files (x86)\Diablo II PlugY` then launch PlugY. Vice versa if you want to play Bnet again. Note: Your characters will probably all be saved in the `Diablo II/Save` folder instead of each individual save location. This can be changed in the registry under `Computer\HKEY_CURRENT_USER\SOFTWARE\Blizzard Entertainment\Diablo II\Save Path` if you want to change the save path, but it can only save to 1 location at a time. You can also config `PlugY.ini` and change the save path for PlugY to somewhere else if you wish. 
  • My Install is very screwed up, What do I do? Nuke uninstall all Diablo 2. Backup your Save folder and config if you wish to keep those, then delete any Diablo II folders in C:\Program Files (x86). Open registry and delete anything under Computer\HKEY_CURRENT_USER\Software\Blizzard Entertainment\Diablo II Reinstall using the setup guide above.
Donate to Slash Diablo
submitted by BeLikeLeBron to slashdiablo [link] [comments]


2020.11.16 19:01 SPAC_Time New Beginnings Acquisition Corp. Announces the Separate Trading of its Common Stock and Warrants Commencing on November 19, 2020 NBA NBA.WS

"MIAMI--(BUSINESS WIRE)--New Beginnings Acquisition Corp. (the "Company") today announced that, commencing on November 19, 2020, holders of the units sold in the Company’s initial public offering may elect to separately trade shares of the Company’s common stock and warrants included in the units.
Those units not separated will continue to trade on the NYSE American (the "NYSE") under the ticker symbol "NBA.U," and the common stock and warrants that are separated will trade on the NYSE under the symbols “NBA" and "NBA WS," respectively."
https://www.businesswire.com/news/home/20201116005425/en/New-Beginnings-Acquisition-Corp.-Announces-the-Separate-Trading-of-its-Common-Stock-and-Warrants-Commencing-on-November-19-2020
"On November 3, 2020, New Beginnings Acquisition Corp. (the “Company”) consummated its initial public offering (“IPO”) of 10,000,000 of its units (“Units”). Each Unit consists of one share of common stock, $0.0001 par value per share (“Common Stock”), and one redeemable warrant (“Warrant”), with each Warrant entitling the holder to purchase one share of Common Stock at a price of $11.50 per share. The Units were sold at an offering price of $10.00 per Unit, generating gross proceeds of $100,000,000.
Simultaneously with the consummation of the IPO, the Company consummated the private placement (“Private Placement”) of 500,000 units (“Private Units”), with each unit consisting of one share of Common Stock and one redeemable warrant (the “Private Warrants”), at a price of $10.00 per Private Unit, generating total proceeds of $5,000,000, to New Beginnings Sponsor, LLC, the Company’s sponsor (“Sponsor”)."
https://www.sec.gov/Archives/edgadata/1823882/000121390020035895/ea129525-8k_newbeginnings.htm
" While we may pursue an initial business combination target in any industry or geographic region, we will seek to capitalize on the operational and investment experience of our management team and focus on companies that we believe have significant growth prospects with the potential to generate attractive returns for our stockholders. We intend to initially focus on companies in the travel, hospitality, leisure, financial technology (fintech), insurance technology and property technology (proptech) sectors. We believe that the dislocation caused by the coronavirus (COVID-19) pandemic will create significant value opportunities in these sectors. "
Prospectus:
https://www.sec.gov/Archives/edgadata/1823882/000121390020034487/f424b41120_newbeginnings.htm
submitted by SPAC_Time to Spacstocks [link] [comments]


2020.11.15 00:43 Overall-Message6460 Spotts around the world

Mexico
San Luis Potosí
Mercedes-Benz GL63 AMG https://www.google.com.mx/maps/@22.1448774,-101.0371333,3a,15y,3.88h,82.55t/data=!3m7!1e1!3m5!1sqjxLVZuYYkYSXgO6K1ryiw!2e0!5s20190401T000000!7i16384!8i8192
BMW X6 M https://www.google.com.mx/maps/@22.1405757,-101.0006024,3a,44.9y,284.2h,79.57t/data=!3m6!1e1!3m4!1sSJZY7aLHtzgUTKEF9WQY9w!2e0!7i16384!8i8192

San Pedro Garza Garcia
Mercedes-Benz SLK AMG https://www.google.com.mx/maps/@25.6534134,-100.3468951,3a,15y,327.44h,78.01t/data=!3m6!1e1!3m4!1sdlHXAzhPmZJ67RAIPRsv_Q!2e0!7i16384!8i8192?hl

Cancun, QROO
Porsche 911 https://www.google.com.mx/maps/@21.1601111,-86.8078687,3a,18.2y,63h,86.96t/data=!3m7!1e1!3m5!1s2Tk3r6ZQ2gj3jALHv1NhBQ!2e0!5s20190601T000000!7i16384!8i8192
Porshce 911 (probably the same) https://www.google.com.mx/maps/@21.1612665,-86.8124826,3a,15y,127.1h,86.7t/data=!3m7!1e1!3m5!1sold2W6J_WoJ1UaBfgOFojw!2e0!5s20190401T000000!7i16384!8i8192
¿Porsche Panamera? https://www.google.com.mx/maps/@21.2320628,-86.8046715,3a,17.2y,109.74h,88.16t/data=!3m7!1e1!3m5!1sW0K2ybDUal-H9phK-tqLLg!2e0!5s20170701T000000!7i13312!8i6656
Porsche Cayenne https://www.google.com.mx/maps/@21.2328212,-86.8023896,3a,73.7y,107.36h,73.96t/data=!3m6!1e1!3m4!1sZu7ZHPnFcVUY0-c85Kx2Rg!2e0!7i16384!8i8192
Ferrari F430 Spider https://www.google.com.mx/maps/@21.162537,-86.8387502,3a,75y,228.03h,74.45t/data=!3m7!1e1!3m5!1sDYlDyc97MksNixz8rrWSZQ!2e0!5s20190401T000000!7i16384!8i8192
Porsche Boxster (not dealer, parked) https://www.google.com.mx/maps/@21.1168865,-86.8366416,3a,15y,261.58h,87.63t/data=!3m7!1e1!3m5!1saQcKsl3TaLos5WkgzkAqSQ!2e0!5s20190401T000000!7i16384!8i8192
MG MGA 1600 https://www.google.com.mx/maps/@21.1291102,-86.8307993,3a,45.5y,230.63h,78.35t/data=!3m7!1e1!3m5!1sVaXe4F8DS2uBPfRv58Kw6w!2e0!5s20190401T000000!7i16384!8i8192

Guadalajara and Zapopan
Ford Mustang Mach 1 https://www.google.com.mx/maps/@20.6775783,-103.3990026,3a,50.1y,201.1h,78.42t/data=!3m7!1e1!3m5!1smeyWpR3jGfZG9AXPnPJLgQ!2e0!5s20140901T000000!7i13312!8i6656
BMW M4 https://www.google.com.mx/maps/@20.6856348,-103.4202167,3a,15y,106.35h,84.83t/data=!3m7!1e1!3m5!1sEqDRNfzWZOnQrD4P1MScXg!2e0!5s20190401T000000!7i16384!8i8cC192
Chevrolet Corvette C7 https://www.google.com.mx/maps/@20.6856176,-103.4202279,3a,21.3y,107.87h,81.62t/data=!3m7!1e1!3m5!1sLPrBh8IsYgDF4Ovt8m6pYA!2e0!5s20190201T000000!7i13312!8i6656
BMW i8 Protonic Red https://www.google.com.mx/maps/@20.7096079,-103.4066855,3a,17.6y,239.07h,85.79t/data=!3m7!1e1!3m5!1sh9N9nwNA1ANcdH65W4vyqQ!2e0!5s20190101T000000!7i13312!8i6656
¿Porsche Boxster? https://www.google.com.mx/maps/@20.7099445,-103.4106486,3a,23.7y,282.15h,86.09t/data=!3m7!1e1!3m5!1sKBICkbojGDSVjZUT5VwP1Q!2e0!5s20170901T000000!7i13312!8i6656
BMW 1M https://www.google.com.mx/maps/@20.6999815,-103.4159023,3a,46.1y,129.18h,80.84t/data=!3m7!1e1!3m5!1sr-xmRPlr_kqssZ8dD-uRVw!2e0!5s20170101T000000!7i13312!8i6656
BMW X6M https://www.google.com.mx/maps/@20.6925072,-103.4153335,3a,21.9y,199.96h,82.04t/data=!3m7!1e1!3m5!1s111DEPEWKty7D3Nenlx7hQ!2e0!5s20170101T000000!7i13312!8i6656
Audi R8 V10 https://www.google.com.mx/maps/@20.6903426,-103.4159046,3a,21.2y,178.2h,86.23t/data=!3m7!1e1!3m5!1sIh1Qpj71xGQWIiAxEPJ9Mw!2e0!5s20170901T000000!7i16384!8i8192
Ford Mustang GT Freddy Van Beuren https://www.google.com.mx/maps/@20.685435,-103.4204495,3a,20.8y,139.07h,89.19t/data=!3m7!1e1!3m5!1sRRNp3ryKlwcOGuhqB4o09Q!2e0!5s20170101T000000!7i13312!8i6656
Porsche Boxster https://www.google.com.mx/maps/@20.6900355,-103.4163613,3a,21.3y,250.4h,86.78t/data=!3m7!1e1!3m5!1sF-lI-_hY1PJUrerEzQy4eg!2e0!5s20170101T000000!7i13312!8i6656
Porsche Boxster https://www.google.com.mx/maps/@20.6913591,-103.4151321,3a,47y,49.23h,87.08t/data=!3m7!1e1!3m5!1s8c39WJ9kuW0YjQ51Ritc-g!2e0!5s20170101T000000!7i13312!8i6656
Porsche 911 Carrera S https://www.google.com.mx/maps/@20.7079918,-103.4107293,3a,20.8y,116.11h,83.38t/data=!3m7!1e1!3m5!1sWEm6_DLCWCTag18OMuQ7dg!2e0!5s20170401T000000!7i13312!8i6656
Ford Mustang Shelby GT500 https://www.google.com.mx/maps/@20.6729583,-103.4228376,3a,15y,84.5h,86.94t/data=!3m7!1e1!3m5!1sD-JZVky_qpwNwuu-wCo8kA!2e0!5s20170901T000000!7i16384!8i8192

Cuernavaca
Porsche 911 GT3RS Weissach Package!!! https://www.google.com.mx/maps/@18.9391738,-99.1900909,3a,15y,365.19h,93.18t/data=!3m7!1e1!3m5!1sOQHbpe80KzIGGLg_T4A8FA!2e0!5s20190801T000000!7i16384!8i8192
Porsche 911 Targa 4S https://www.google.com.mx/maps/@18.9688917,-99.2319327,3a,41y,109.5h,77.6t/data=!3m7!1e1!3m5!1spT91KgGeLwsk-ztU_1UcBQ!2e0!5s20190701T000000!7i16384!8i8192
Jeep Grand Cherokee SRT and Chevrolet Corvette C7 https://www.google.com.mx/maps/@18.968886,-99.2319354,3a,69.1y,287.81h,67.96t/data=!3m7!1e1!3m5!1sMf2CA2ej68bbK1e0od43VQ!2e0!5s20180701T000000!7i13312!8i6656

Mexico City
Aston Martin DB11 https://www.google.com.mx/maps/@19.3589989,-99.27692,3a,44.9y,301.16h,77.09t/data=!3m7!1e1!3m5!1sip0EvKCDOaiWZePBReduEg!2e0!5s20180401T000000!7i13312!8i6656
Chevrolet Corvette C7 https://www.google.co.il/maps/@19.3022893,-99.1678339,3a,36.6y,21.86h,84.12t/data=!3m7!1e1!3m5!1sobD2J8CcsHE_ZGY70uVKTg!2e0!5s20180601T000000!7i13312!8i6656
Rover (very rare in Mexico) https://www.google.com.mx/maps/@19.4332199,-99.184184,3a,20.2y,156.79h,83.15t/data=!3m6!1e1!3m4!1swicEUJLUYvBA72aFeRScdQ!2e0!7i16384!8i8192
Mercedes-Benz C63 AMG https://www.google.com.mx/maps/@19.284634,-99.4599312,3a,15y,242.29h,81.06t/data=!3m7!1e1!3m5!1sj8xSeHZSBWfsLajRL7uyjg!2e0!5s20140101T000000!7i13312!8i6656
Audi R8 V10 Plus https://www.google.com.mx/maps/@19.5485527,-99.2871043,3a,16.2y,184.74h,93.2t/data=!3m6!1e1!3m4!1snk3vUvm_BadG8oGsKf-qww!2e0!7i16384!8i8192
Porsche Boxster https://www.google.com.mx/maps/@19.5526274,-99.2730294,3a,21.7y,353.54h,86.14t/data=!3m6!1e1!3m4!1svJKxs2eteO0UZ19WjjrIwQ!2e0!7i16384!8i8192
BAC Mono!!! (dealer) https://www.google.com.mx/maps/@19.5527442,-99.2727595,3a,25.1y,11.26h,92.75t/data=!3m7!1e1!3m5!1s_R_ujsQtCFbTgNQtJV5Keg!2e0!5s20190101T000000!7i16384!8i8192
Mercedes-Benz AMG GTS https://www.google.com.mx/maps/@19.552151,-99.2724056,3a,15y,328.69h,92.21t/data=!3m7!1e1!3m5!1s1OGtVCmcaBuAUMdoUxWeJw!2e0!5s20190101T000000!7i16384!8i8192
Porsche Cayman GT4? https://www.google.com.mx/maps/@19.5481154,-99.272305,3a,21.8y,252.54h,86.31t/data=!3m7!1e1!3m5!1sKcJr0KG7ZmoeV9I1XrRXLg!2e0!5s20190101T000000!7i16384!8i8192
Lotus Elise https://www.google.com.mx/maps/@19.5589201,-99.297171,3a,22.5y,112.2h,80.04t/data=!3m7!1e1!3m5!1sko1NWCvfoDdRDin4Nxl5Lg!2e0!5s20091101T000000!7i13312!8i6656
Audi R8 and Audi RS3 https://www.google.com.mx/maps/@19.553722,-99.2928525,3a,61y,85.74h,75.65t/data=!3m7!1e1!3m5!1sS2dlLU52_U4KIjv6ohvRQw!2e0!5s20190101T000000!7i16384!8i8192
Audi R8 V10 Plus https://www.google.com.mx/maps/@19.3823301,-99.2672658,3a,23.2y,34.48h,83.35t/data=!3m7!1e1!3m5!1s0oN1X9VhzCBAMrL0VLap7w!2e0!5s20170801T000000!7i13312!8i6656
Rolls-Royce Silver Shadow https://www.google.com.mx/maps/@19.4194026,-99.2151807,3a,21.4y,272.82h,83.52t/data=!3m7!1e1!3m5!1sG8U_17P9_9I6ZF37m7udcw!2e0!5s20090901T000000!7i13312!8i6656
Porsche 911 https://www.google.com.mx/maps/@19.4008612,-99.2354616,3a,47.5y,56.27h,79t/data=!3m7!1e1!3m5!1sZravmaXKrmtNW3qcYAA2rQ!2e0!5s20161101T000000!7i13312!8i6656
Mercedes-Benz G500 4x4 Squared https://www.google.com.mx/maps/@19.4249233,-99.1747994,3a,18.4y,267.01h,87.78t/data=!3m7!1e1!3m5!1s3VsH3X7mKeGqcelPo7JN6w!2e0!5s20181201T000000!7i13312!8i6656
Maserati GranTurismo Sport https://www.google.com.mx/maps/@19.4281978,-99.1936715,3a,72.9y,246.72h,69.37t/data=!3m7!1e1!3m5!1sxJejuXSvxMUB5JLM4uOS0g!2e0!5s20140301T000000!7i13312!8i6656
Bentley Continental x2 https://www.google.com.mx/maps/@19.4277748,-99.1943697,3a,24y,330.52h,81.89t/data=!3m7!1e1!3m5!1smw0X0jU0K7AP3fqUiUFKxQ!2e0!5s20140901T000000!7i3328!8i1664
BMW M2 https://www.google.com.mx/maps/@19.39583,-99.1742657,3a,15y,183.19h,79.04t/data=!3m7!1e1!3m5!1smRCVaVgQ0txdddT8m35HAA!2e0!5s20190401T000000!7i16384!8i8192
Morelia
Porsche 911 https://www.google.com.mx/maps/@19.6984125,-101.1852976,3a,75y,328.93h,88.59t/data=!3m7!1e1!3m5!1s9zJcVQhGq2Nsux1Xl8SUAQ!2e0!5s20111201T000000!7i13312!8i6656

London
Ferrari 458 Speciale https://www.google.com.mx/maps/@51.5011932,-0.1533484,3a,75y,272.44h,70.77t/data=!3m7!1e1!3m5!1s0u_PhAhA3PRk5SNdggsywg!2e0!5s20140501T000000!7i13312!8i6656
Mercedes-Benz C63 AMG Black Series https://www.google.com.mx/maps/@51.5106755,-0.1409112,3a,16.9y,163.16h,78.91t/data=!3m7!1e1!3m5!1stzZkrmzbfEgAJ2XdEnT0lg!2e0!5s20140501T000000!7i13312!8i6656
Mercedes-Benz SLR McLaren Edition https://www.google.com.mx/maps/@51.5125632,-0.148982,3a,75y,335.79h,69.7t/data=!3m7!1e1!3m5!1sfpSiW5yfwWPdBHy8HcHA1Q!2e0!5s20140501T000000!7i13312!8i6656
Aston Martin DBS https://www.google.com.mx/maps/place/51%C2%B030'20.3%22N+0%C2%B008'55.1%22W/@51.5056496,-0.1485875,3a,52.3y,342.06h,65.4t/data=!3m7!1e1!3m5!1sIweUnG2KqS5oNo9tZBgVFA!2e0!5s20120601T000000!7i13312!8i6656!4m5!3m4!1s0x0:0x0!8m2!3d51.505639!4d-0.148643
DBS https://www.google.com.mx/maps/@51.4969263,-0.1575652,3a,67y,255.99h,55.56t/data=!3m7!1e1!3m5!1sR2Ui4g7vUn-ym_yfzknErg!2e0!5s20140501T000000!7i13312!8i6656
DBS https://www.google.com.mx/maps/@51.4993859,-0.1492111,3a,45.6y,7.29h,71.24t/data=!3m7!1e1!3m5!1si2aA-vl8HPxMtVzfZbDiPQ!2e0!5s20140801T000000!7i13312!8i6656
DBS https://www.google.com.mx/maps/@51.4858339,-0.1609113,3a,48.9y,177.99h,66.08t/data=!3m7!1e1!3m5!1ssPZjnSO5bN5WMtOkD3xumA!2e0!5s20150501T000000!7i13312!8i6656

Miami Beach
Dodge Viper SRT-10 https://www.google.com.mx/maps/@25.7847654,-80.1298122,3a,75y,285.21h,68.55t/data=!3m7!1e1!3m5!1skW82uKRLUwEqZh1aY4yuww!2e0!5s20080901T000000!7i3328!8i1664
Dodge Viper SRT-10 x4 https://www.google.com.mx/maps/place/25%C2%B046'44.0%22N+80%C2%B007'51.6%22W/@25.7788528,-80.1309629,3a,86.2y,304.76h,82.7t/data=!3m6!1e1!3m4!1sEl-qoCQhE9ee2XA5Jfw12A!2e0!7i3328!8i1664!4m5!3m4!1s0x0:0x0!8m2!3d25.778884!4d-80.13099

Cannes
The Koenigsegg Agera RS in different location https://www.google.com/maps/@43.5464839,7.0365827,3a,15y,277.68h,87.64t/data=!3m6!1e1!3m4!1sQKJQ6rK2lopvo6-YpO9Ojw!2e0!7i13312!8i6656

Tel Aviv
458 Italia x2 and 458 Speciale (360º) https://www.google.co.il/maps/place/%D7%92'%D7%A8%D7%90%D7%9C%D7%93%E2%80%AD/@32.076046,34.7817192,3a,33y,122.55h,85.82t/data=!3m8!1e1!3m6!1s-_uGH1COefBU%2FVk8lW2vZfwI%2FAAAAAAAAbP8%2FILXqAyVeUAU!2e4!3e11!6s%2F%2Flh6.googleusercontent.com%2F-_uGH1COefBU%2FVk8lW2vZfwI%2FAAAAAAAAbP8%2FILXqAyVeUAU%2Fw424-h106-n-kno%2F!7i14336!8i3584!4m13!1m7!3m6!1s0x151d4b8477684ea7:0xd9710f44e5cb6307!2z16jXldec16fXoSDXqdeV15DXlSDXqtecINeQ15HXmdeRIC0gVGVsIEF2aXYgUm9sZXggQm91dGlxdWU!3b1!8m2!3d32.0761162!4d34.7817358!3m4!1s0x0000000000000000:0x07be8efe4fea7146!8m2!3d32.0761162!4d34.7817358?hl=iw
458 Italia https://www.google.co.il/maps/@32.1210288,34.8350793,3a,16.6y,336.53h,90.24t/data=!3m6!1e1!3m4!1svllws13X7Gv2ue271g-Ksg!2e0!7i13312!8i6656

Beverly Hills
Mercedes-Benz SLS AMG Black Series https://www.google.com/maps/@34.0675369,-118.403065,3a,15y,332.42h,87.66t/data=!3m6!1e1!3m4!1s72xcUARvbsI82bolT8Lpyg!2e0!7i13312!8i6656

Russia
Bentley Mulsanne https://www.google.com.mx/maps/@55.7378326,37.2598416,3a,18.6y,348.54h,83.98t/data=!3m6!1e1!3m4!1sIZodUhOSrvKWlYSQx4nZCA!2e0!7i13312!8i6656
Bentley Mulsanne https://www.google.com.mx/maps/@55.7382156,37.2627323,3a,46.1y,20.82h,76.76t/data=!3m7!1e1!3m5!1sJbfjod7M8hBos3zjIy5Spw!2e0!5s20190601T000000!7i13312!8i6656
Maserati Ghibli https://www.google.com.mx/maps/@55.7382864,37.2632663,3a,23y,342.93h,84.28t/data=!3m7!1e1!3m5!1s_UsU57o6u2LFTVgWpxDsoA!2e0!5s20190601T000000!7i13312!8i6656
Widebody BMW X6M https://www.google.com.mx/maps/@55.7372448,37.2540346,3a,20.6y,292.51h,81.84t/data=!3m6!1e1!3m4!1sTLtDQ6m75R5c4cqmx_AF3g!2e0!7i13312!8i6656
Ferrari Portofino https://www.google.com.mx/maps/@55.7369129,37.2505106,3a,75y,346.78h,61.29t/data=!3m6!1e1!3m4!1sV7KwiRYnr4vfo1DoGz5Eaw!2e0!7i13312!8i6656
Jaguar F-Type https://www.google.com.mx/maps/@55.7365095,37.2482511,3a,75y,350.76h,80.66t/data=!3m7!1e1!3m5!1snJSnzrOFr4qvwZm8Z4bmBQ!2e0!5s20190601T000000!7i13312!8i6656
Bentley Continental GT https://www.google.com.mx/maps/@55.7363866,37.2475327,3a,40.6y,355.13h,68.84t/data=!3m7!1e1!3m5!1sbR_LkdNY88SEW6-7OaRksg!2e0!5s20190601T000000!7i13312!8i6656
Bentley Bentayga https://www.google.com.mx/maps/@55.7361143,37.2460669,3a,19y,203.77h,85.99t/data=!3m7!1e1!3m5!1siS9-aDtlyBGbm58Nk7k8LQ!2e0!5s20190601T000000!7i13312!8i6656
Bentley Mulsanne (probably the same as second) https://www.google.com.mx/maps/@55.7368722,37.2482344,3a,45y,18.37h,73.82t/data=!3m6!1e1!3m4!1ssaA4lzgXrbp6yzahtpKNPg!2e0!7i13312!8i6656
Mercedes-Benz SLS AMG, Bentley Continental x2 and Porsche Panamera (360 tour) https://www.google.com.mx/maps/@55.7380865,37.2601207,3a,53.2y,346.57h,76.4t/data=!3m6!1e1!3m4!1sAF1QipPYSxShjy3cJz6gUUAWyKV07RFNaXNj7JOauli4!2e10!7i7776!8i3888
Bentley Mulsanne https://www.google.com.mx/maps/@55.7389142,37.2688143,3a,15y,294.51h,89.33t/data=!3m7!1e1!3m5!1sunZgZa1hSzV4ubt3c52D-w!2e0!6s%2F%2Fgeo0.ggpht.com%2Fcbk%3Fpanoid%3DunZgZa1hSzV4ubt3c52D-w%26output%3Dthumbnail%26cb_client%3Dmaps_sv.tactile.gps%26thumb%3D2%26w%3D203%26h%3D100%26yaw%3D246.1413%26pitch%3D0%26thumbfov%3D100!7i13312!8i6656
Bentley Continental https://www.google.com.mx/maps/@55.7390992,37.2693514,3a,15y,114.2h,89.36t/data=!3m6!1e1!3m4!1sRXXICi7kD7rm-sf4Y_t06A!2e0!7i13312!8i6656
Maserati Levante https://www.google.com.mx/maps/@55.7393128,37.2722555,3a,21.3y,67.93h,83.59t/data=!3m7!1e1!3m5!1sQzakiUW4Bfs4gdWD4glHeQ!2e0!5s20190601T000000!7i13312!8i6656
submitted by Overall-Message6460 to StreetviewCarSpotting [link] [comments]


2020.11.14 20:49 JauneSiriusWhut Dealer/Garage/Detailer 2

Since the original post was already getting too big (too many characters), I've split them up, so here we go! T-Z.
Taiwan
Taipei - Continental / Amazing / Unknown / M3 shop - LaFerrari / M3's / 458 / Drophead Coupe / Beetle RSI / M2 CS
Taipei - Porsche - Carrera GT
Taipei - SMS - 997 GT3 / Huracan
Taipei - Unknown - 991 GT2RS / 997 GT3 RS 4.0 / DBS Superleggera
Taipei - Unknown / Wrap - 600LT / Aventador / 675LT
Taipei - Unknown - LaFerrari / Senna
Taipei - Urban Legend - Senna / 570S / 458 Speciale
Taipei - Yun San Motors - LaFerrari / DBS Superleggera
The Netherlands
Achterveld - Italautos - Ferrari 400i / Testarossa
Almelo - First Gear - SLS AMG Black Series / F12
Almere - Noble Cars - Spyker C8 Spyder / Lot of classics
Amsterdam - Classic Car Auctions - 330 GT / Testarossa
Amsterdam - Gray Audio - 997 GT3RS 4.0 / 991 GT2RS
Amsterdam - Real Art On Wheels - DB5
Apeldoorn - Saab / Alfa Romeo - Z8 / 991 GT3 RS
Bergschenhoek - JD Customs - Maybach 57 / 458 Italia
Best - Forza Service - F40 Barchetta / 512M / 599 GTO / Enzo
Best - Van de Akker - 991 Turbo S Cabrio
Brummen - Gallery Aaldering - Lot of classics
Burgerveen - Real Art On Wheels - 458 Speciale
Eindhoven - Cito Motors - DBS Superleggera / Vanquish Volante Zagato / XJ220 / Vantage GT12
Enschede - Wiggers Mastercars - 575 Superamerica / Murcielago
Geleen - Hoefnagels - F12tdf / Carrera GT / Diablo / SLR
Hengelo - Munsterhuis - F12tdf / 575 Superamerica / F430 Scuderia
Hengelo - S2 Classic Cars - Lamborghini 400GT
Heteren - Porsche - 918 Spyder / Carrera GT / 997 GT2RS / 993 Carrera RS / 997 GT3RS
Hilversum - Kroymans Ferrari - 250 GTE
Hilversum - Mugello Engineering - Lamborghini 400GT / 550 / F430
Huizen - Eastcorner Carcleaning - 720S / Continental SuperSports
Maastricht - Porsche - 991 GT2RS
Maastricht - Race Art - F40 / Carrera GT / GTR GT3 / Shelby Cobra Replica / More collection!
Nieuwerkerk aan den IJssel - Van Vliet Automotive - Veyron (blue)
Nunspeet - Wim Prins Automotive - 8C Spider / F12
Oirschot - Porsche - 997 Sport Classic
Purmerend - Custom Dreams - SLS AMG Black Series / Solarbeam Yellow S65 AMG / 991 Turbo S Mk2 Cabrio
Rijnsburg - HAI - 996 GT3 / Murcielago Roadster
Rotterdam - Porsche - PTS Green 991 Turbo S
Uithorst - Automobielfabriek - DBS
Utrecht - Louwman - 675LT / Diablo
Veghel - ASV Mercedes-Benz - SLR / G63 Brabus / SLS / G500 4x4 / AMG GT-R
Velddriel - Nino Hooymans - F12 / 599 GTB
Waardenburg - Thijs Timmermans - SLS AMG Black Series / SLR Roadster / SL65 AMG Black Series / G500 4x4 / G63 AMG 6x6 / S650 Maybach Convertible / 812 Superfast
Woerden - BMW Hans Severs - M4 GTS / Portofino
Wijchen - Auto Wijchen - Aventador SV
Turkey
Istanbul - Autobank / Narin / Levent - RS6 C8 / Taycan / F12 / Aventador
Uruguay
Montevideo - Jaguar - F-Type
USA
Arizona
Scottsdale - McLaren - Centenario
California
Beverly Hills - Ferrari - 599XX / LaFerrari (white) / Enzo (black) / F12tdf / LaFerrari (black) / 599 GTO / F40 / Enzo (yellow) / F40 LM / 250 GT Cabrio / 275 GTS
Beverly Hills - GI Automotive - Aventador SV / Widebody C7 / CLK63 AMG Black Series / 991 GT3RS
Beverly Hills - Lamborghini - Veyron Grand Sport Vitesse (orange)
Beverly Hills - McLaren - 675LT / Carrera GT / R8 GT
Beverly Hills - Pagani / Unknown - Veyron (black) / Huayra (black) / F40 / F12tdf / Huayra Roadster (white) / Huayra (white) / Huayra (grey) / Huayra (grey) / Carrera GT / Huayra (blue)
Costa Mesa - Ilusso - SLS AMG Black Series / Maybach G650 Landaulet / CCX / Enzo / Veyron SuperSports (blue) / Huayra (white) / Huayra (black) / Veyron (silver) / LaFerrari / Chiron
Los Angeles - Black & White Rental - Carrera GT / Aventador / Aventador Roadster / G550 4x4
Los Angeles - Ferrari - F12tdf / Tuned F12
Los Angeles - Platinum Motorsport - 675LT / 62S / Murcielago LP640-4 / Murcielago / Lotta Rolls
Los Angeles - Platinum Collision - 918 Spyder / Enzo / Murcielago SV / SLR / SLR Roadster
Los Angeles - Porsche - Carrera GT (grey 2x) / 997 GT3RS 4.0 / Carrera GT (black)
Los Angeles - RDB - Ford GT / Brabus G550 4x4 / Brabus G550 4x4 Pickup / Aventador / 720S
Los Angeles - Rolls-Royce / Bentley / Bugatti - 918 Spyder / Veyron (blue/black / Chiron (blue/black) / Veyron Grand Sport (silver) / Veyron (red/black) / Veyron (white) / Veyron (black) / Veyron (grey/red) / Veyron Grand Sport (white) / probably missed some
Los Angeles - Specialty Car Craft - 512TR / 675LT / SLR / Ford GT / SLR Roadster / Enzo / Murcielago SV /
Los Angeles - Sticker City - 918 Spyder (blue) / 918 Spyder (black) / Viper ACR / 458 Speciale
Los Angeles - The Auto Gallery - Aventador SV / 991 R
Newport Beach - Aston Martin - Vanquish Zagato Volante / DBS Superleggera
Newport Beach - Ferrari - Enzo / F12tdf / 599 GTO
Newport Beach - McLaren - P1 (orange) / P1 (yellow) / P1 (brown) / Senna / Senna GTR
Newport Beach - Newport Exotics - Veyron (white/blue)
Newport Beach - Pagani / Other - Huayra BC (blue) / Huayra (grey) / Huayra (blue) / Veyron (black) / Huayra (white) / Classics
Palo Alto - McLaren - F1 / Senna / P1 / GT
San Diego - Lamborghini / Bentley / Rolls Royce / McLaren - Continental GT3R / Miura / SV's / SLR Roadster / Carrera GT / Veyron (red/black) / Spyker C8 Spyder / Saleen S7
West Hollywood - Al & Ed's Autosauna - F12tdf / Dawn / 488 GTB
Connecticut
Greenwich - Ferrari / McLaren - MC12 / F40 / LaFerrari / SL65 AMG Black Series / Senna
Greenwich - Miller Motorcars / Pagani - Veyron (black/red) / Huayra BC / Vanquish Zagato Shooting Brake / Vulcan
Florida
Fort Lauderdale - Fort Lauderdale Collection - SLR 722S Roadster McLaren Edition / SLS AMG Black Series / 918 Spyder / P1 / F12tdf / Veyron (black) / F40 / Aventador SV / SLR Mansory / Veyron SuperSports (orange) / Veyron (black/red) / Veyron (black/blue)
Miami - Braman Motors - Veyron (blue/black) / Veyron SuperSports (black/orange)
Miami - Curated - Miura / Murcielago R-GT / Countach's / Diablo / 918 Spyder / F50 / CLK DTM AMG Convertible / XJ220 / EB110 / 997 GT2 RS / LaFerrari
Miami - Speedart Motorsports - F40 / Viper ACR
North Miami Beach - Prestige Imports - LaFerrari (2x) / Centenario / Huayra Roadster (grey) / Huayra (red) / 918 Spyder (silver) / CCX / Huayra (white) / Veyron (black/blue) / Vanquish Zagato / Zonda F / Veyron (black/white) / 918 Spyder (white)
Louisiana
New Orleans - Nolasport - 997 GT2 / 991 GT3RS Mk2 / Murcielago Roadster
Massachussets
Dedham - Automotive Solutions - 360 Spider / Huracan Spyder / Viper / R8 V10 Spyder
Newton - AVI - Huracan Spyder Performante / 991 GT3RS / 458 Italia / Aventador SVJ
New Jersey
Red Bank - Auto Exotica - F430 Scuderia / Aventador
New York
New York City - Manhattan Motorcars - CCX / Veyron (white) / Veyron (silveblack) / Enzo / Spyker C8 / LFA / SLR Roadster
Texas
Carrollton - RAC Performance - F12tdf
Houston - Porsche / Rolls Royce / Lamborghini - 991 GT2RS / GT3RS 4.0 / 997 GT2RS / Carrera GT
Houston - Motorwerks - 991 GT2RS / Gallardo Superlegerra / G550 4x4 / G550 4x4 Brabus / SLR
Washington
Seattle - Ferrari - 458 Speciale / F1 / F12
submitted by JauneSiriusWhut to StreetviewCarSpotting [link] [comments]


2020.11.11 12:03 remote-enthusiast List of 105 remote jobs - (non)tech

Hello friends! These are the open remote positions I've found that were published today. See you tomorrow! Bleep blop 🤖
submitted by remote-enthusiast to remotedaily [link] [comments]


2020.11.09 13:26 Perryapsis The Distribution of Votes and Outlier Analysis of the AP Poll (Week 10)

TABLE

HOW TO READ THIS TABLE
Teams are ranked in their order from the AP Poll for the current week. The column to the right of the team name shows the number of points that team received using the AP Poll's Borda Count rules. The following columns show how many votes for each ranking the team received. The "U" column shows how many voters left the team off their ballots entirely. Gridlines are placed every 5 lines for ease of reading. A double-line is placed below the 25th-ranked team to distinguish "ranked" teams above it to "receiving votes" teams below it.
Some cells are shaded to highlight points of interest. The green diagonal highlights how many voters ranked a team exactly where they ended up in the overall poll. For example, Indiana is ranked 10th in this week's poll and 16 voters placed Indiana in their 10th spot. Values for which a team received no votes at that rank are shaded in red, while placements chosen by only exactly one voter are highlighted in blue. The most common selection (the mode) for each team is shaded yellow. Votes that are more than three standard deviations away from the mean are considered outliers and outlined in with dashed red lines. Finally, since there are very few votes that ever end up near the top-right or bottom-left of the chart, those cells are filled in with black diagonally as much as possible without covering up any nonzero values. This helps naturally guide the eye while viewing the chart and helps identify outlying votes.
NOTES FOR THIS WEEK
The upper Wilner Diagonal was set by Ryan Aber leaving flair Wisconsin unranked. The lower Wilner Diagonal is set by Jon Wilner himself ranking flair Arizona State 15th, their only vote of the week. A total of 80 votes were cast for receiving-votes teams amounting to a total of 282 points (1.4%). 442 votes matched their team's rank exactly this week (e.g. putting the 10th place team at 10, 20th place at 20th, etc). flair Northwestern has the largest disagreement between voters this week with a standard deviation of 3.44.
OUTLIER ANALYSIS
Adjusted rankings
This follows the same methodology as my original analysis from the preseason poll. This week, we have two flips in the top 25. First, flair Indiana jumps to 9th over flair Miami. Second, flair Wisconsin hops over flair Georgia to 12th.
COLUMN ANALYSIS
Who is the best team to receive a last place vote? (Marshall) What is the worst team to receive a top 5 vote? (flair) This table isn't pretty (yet), but here's the raw data.
AUSTRALIAN POLL

Flipped-votes rankings

Why not flip all the votes upside down for fun and chaos? Then the goal is to be ranked as low as possible on each ballot, but not get left off of any ballots. This results in a silly ranking, but screw it, why not? flair Liberty tops the Australian Poll this week.
ACKNOWLEDGEMENT
I would like to thank u/bakonydraco for providing the data set for this table.

TABLE

No shading

Outlier-adjusted rankings

Column extremes

Flipped-votes rankings

submitted by Perryapsis to CFB [link] [comments]


2020.11.07 12:03 remote-enthusiast List of 74 remote jobs from last couple of days

Hello friends! These are the open remote positions I've found that were published today. See you tomorrow! Bleep blop 🤖
submitted by remote-enthusiast to remotedaily [link] [comments]


2020.11.05 16:38 Ottawa_CS Assorted Spots from Ottawa, Miami and Taipei

Miami
Morgan Plus 4?
Ottawa
Audi RS4 Avant
Mercedes G550 4x4 ^ 2
Taipei
Laferrari (Detail Shop)
Porsche 911 GT3 (997 mk2)
submitted by Ottawa_CS to StreetviewCarSpotting [link] [comments]


2020.11.04 20:26 TIESLab Help Us Understand Families' Daily Lives with a Paid Research Opportunity for Families in the Miami-Dade Community

The Technological Interventions for Ecological Systems Lab at the FIU Center for Children and Families is using mobile devices to study the everyday lives of parents, caregivers, and their children. We are looking for low-income families in the Miami-Dade community who have children between 6 and 9 years old and speak English or Spanish. Each family will be compensated $200 total for participating in all parts of the study. This will include (1) a virtual meeting ($50), (2) a virtual meeting plus remote data collection using smartphones and wearable devices (Apple Watches or Fitbits) ($100), and (3) a final virtual meeting ($50). Call us at 305-684-3905 or email us at [[email protected]](mailto:[email protected]) to complete a short screening over the phone and see if you are eligible!
El Laboratorio de Intervenciones Tecnológicas para Sistemas Ecológicos del Centro para Niños y Familias de FIU esta utilizando dispositivos móviles para estudiar la vida cotidiana de padres, cuidadores y sus niños. Estamos buscando familias de bajos recursos en el condado de Miami-Dade con niños que hablen fluidamente Ingles o Español. Cada familia será compensada $200 por participar en todas las partes del estudio. Esto incluye (1) encuentro virtual ($50), (2) encuentro virtual más la recopilación remota de data por teléfonos y relojes inteligentes (Fitbits o Applewatches) ($100), y (3) ultimo encuentro virtual ($50). ¡Llámanos al 305-684-3905 o escríbenos a [[email protected]](mailto:[email protected]) para completar una corta evaluación y descubrir si eres elegible para participar en nuestro estudio!
submitted by TIESLab to MDC [link] [comments]


2020.11.02 13:17 Perryapsis The Distribution of Votes and Outlier Analysis of the AP Poll (Week 9)

TABLE

HOW TO READ THIS TABLE
Teams are ranked in their order from the AP Poll for the current week. The column to the right of the team name shows the number of points that team received using the AP Poll's Borda Count rules. The following columns show how many votes for each ranking the team received. The "U" column shows how many voters left the team off their ballots entirely. Gridlines are placed every 5 lines for ease of reading. A double-line is placed below the 25th-ranked team to distinguish "ranked" teams above it to "receiving votes" teams below it.
Some cells are shaded to highlight points of interest. The green diagonal highlights how many voters ranked a team exactly where they ended up in the overall poll. For example, Wisconsin is ranked 10th in this week's poll and 10 voters placed Wisconsin in their 10th spot. Values for which a team received no votes at that rank are shaded in red, while placements chosen by only exactly one voter are highlighted in blue. The most common selection (the mode) for each team is shaded yellow. Votes that are more than three standard deviations away from the mean are considered outliers and outlined in with dashed red lines. Finally, since there are very few votes that ever end up near the top-right or bottom-left of the chart, those cells are filled in with black diagonally as much as possible without covering up any nonzero values. This helps naturally guide the eye while viewing the chart and helps identify outlying votes.
NOTES FOR THIS WEEK
The upper Wilner Diagonal was set by 9 voters leaving flair Oregon unranked, while the most common place to put them was 12th with 16 such votes. The lower Wilner Diagonal is set by Dylan Sinn putting flair Utah 13th. A total of 166 votes were cast for receiving-votes teams amounting to a total of 735 points (3.6%). 425 votes matched their team's rank exactly this week (e.g. putting the 10th place team at 10, 20th place at 20th, etc). flair USC has the largest disagreement between voters this week with a standard deviation of 3.52. flair Coastal Carolina got 9 votes for each of 15th, 16th, and 17th places. Similarly, flair Southern Methodist got 8 votes each for 16th, 17th, and 18th places. flair Boise State appears on 56 ballots, but is ranked one spot below flair USC on only 43 ballots.
OUTLIER ANALYSIS
Adjusted rankings
This follows the same methodology as my original analysis from the preseason poll. The results are pretty benign this week. flair Oregon hops one spot over flair Miami to 11th. Then flair Auburn edges out flair Michigan for 22nd. After that, a few teams mingle in the also-ran arboretum and five teams get dropped from the rankings.
COLUMN ANALYSIS
Who is the best team to receive a last place vote? (Indiana) What is the worst team to receive a top 5 vote? (Oregon) This table isn't pretty (yet), but here's the raw data.
AUSTRALIAN POLL

Flipped-votes rankings

Why not flip all the votes upside down for fun and chaos? Then the goal is to be ranked as low as possible on each ballot, but not get left off of any ballots. This results in a silly ranking, but screw it, why not? flair Oklahoma tops the Australian Poll this week. Also flair Miami (Aus.) has 666 points.
ACKNOWLEDGEMENT
I would like to thank u/bakonydraco for providing the data set for this table.

TABLE

No shading

Outlier-adjusted rankings

Column extremes

Flipped-votes rankings

submitted by Perryapsis to CFB [link] [comments]


2020.10.31 19:31 John_Krolik MVP Tier Shooting list (WARNING: LONG)

Just a quick intro, because there’s a lot to get to. Since the 3-pointer is a part of every superstar’s game now, I wanted to see how good every MVP of the 3-point era were at shooting and rank them – shooting is literally the fundamental skill of basketball, but is it typical for the very best players to be the best shooter? The higher the tier, the better (although to be honest I didn’t really know where to put the Rose/AI/Westbrook tier, do with that what you like), and the list is in descending order – each player written about is a better shooter than the one above him. (Also, this is a repost from nba -- I legit just learned this subreddit exists today, and y'all seem to be a pretty cool bunch of dorks -- I say "dorks" as the highest of compliments, for reasons that should become apparent if you finish this monster of a post.)
Tier 8: Shaquille O’Neal
Shaquille O’Neal – 0.0 3PA, 0.45 3P%, 52.7 FT%
This is what interests me about Shaq: he broke both of his wrists at 11 years old, and they never healed properly, making it impossible for him to snap his wrist properly and develop anything approaching a passable jump shot or free throw stroke. (It’s been argued that Shaq had a fixable mechanical flaw or should have shot underhand, but we can talk about that another time.)
Shaq’s wrist issues meant that his scoring arsenal was essentially limited to a jump hook over his left shoulder or a drop-step leading to a dunk or right-handed bank shot. He also happened to be one of the most physically imposing big men of all time.
So the question becomes: if you have a player with the ability to create and convert shots at the immediate basket area at a historically high rate, is it the worst thing in the world if he is physically incapable of taking a difficult shot? How many missed free throws is it worth to have a dominant post player who never wastes possessions by falling in love with his 18-footer? Is it worth giving up the ability to dump the ball to Shaq at the mid-post and get a decent fadeaway out of it late in the clock in order to guarantee he’ll never take one early in the clock?
The sheer terror of what Shaq would have been if he hit 75-80% of his free throws keep me from going as far as saying Shaq’s messed up wrists were a blessing in disguise (we’ll talk more about this when discussing why Shaun Marion is accidentally one of the 5 most influential players of the 21st century), but I think the floor spacing and shot creation teams gave up by accepting Shaq’s limitations may not have been worth Shaq being forced to take every shot from a high-percentage area. When you consider Shaq’s somewhat laisse-faire approach to the game and prideful streak, it’s not terribly hard to imagine an alternate-universe version of Shaq firing up shot after shot in attempts to capture the scoring title and daring his coaches to bench him for it.
Tier 7: True Big Men
Moses Malone – 0.0 3PA, 0.96% 3PT%, 76.0% FT%
Gonna be honest, I know pretty much jack shit about Moses Malone other than that he was a dominant offensive rebounder and was one of the first players to win a Finals MVP with a team that did not acquire him on draft day. (There were 5 of them in 2011, now there are like 40.) Considering he lived underneath the basket grabbing those offensive boards and shot 49.5% from the field over his career, I’m assuming he wasn’t much of a marksman. although I do know enough about him to know his FG% was dragged down because he did a lot of his damage playing volleyball under the basket but ultimately coming away with the bucket. I could be wrong, though. Solid FT% for a center.
Tim Duncan – 0.1 3PA, 17.8% 3PT%, 69.6% FT%
I enjoy putting Tim Duncan all the way down here while being a massive Tim Duncan fan. When people talk about all the things that made Tim Duncan great – his efficient, no-flash approach, the beauty of his banker from the left block, his footwork and passing from the post, his quiet brand of leadership, his willingness to play whatever role his team asked him to, his defensive acumen, his work ethic, and his intelligence, they tend to forget a very important part of why Tim Duncan was so great: TIM DUNCAN WAS A FUCKING MONSTER.
I do not know why people are so willing to forget that Tim Duncan was a fucking monster. Perhaps it’s because, despite spending the vast majority of his career as a center, he got labeled as “The Best Power Forward of All Time” because he began his career next to David Robinson. Maybe it’s because nobody can really look like a fucking monster while standing next to David Robinson. Maybe it’s because he spent so much time as a crafty veteran. In any case, Tim Duncan in his prime was a huge man who would put his left shoulder into your chest, push you under the basket, and flip in a hook shot as you caught your breath. It was only once enough of those put the fear of god in his defender that he’d turn to his right shoulder and deliver that boring bank shot. He had an odd jumper where he put his guide hand under the basket that went in a decent amount of the time and his free throws, which he shot in one quick yank like he was trying to get them over with as fast as possible, were never a hack-a-Duncan level weakness, but he was a pretty bad shooter. The “Big Fundamental” is one of only 2 MVPs in the 3-point era with a career FT% under 70%. However, the “Big Fundamental” is also a fucking monster.
David Robinson – 0.1 3PA, 25% 3PT%, 73.6% 3PT%
Another person whose demeanor tends to overshadow the fact he was a goddamn freak of nature. David Robinson was literally a super-soldier. Just a good enough outside shooter to get himself in trouble sometimes (surprisingly low career FG% of 51.8%, considering he didn’t make 3s, although his TS% was always excellent because he lived at the line), but he also had enough shot creation ability to drop an extraordinarily petty 71-point game, which I respect. Discussion question: what if David Robinson had come into the league at 19 instead of 24?
Hakeem Olajuwon – 0.1 3PA, 20.2% 3PT%, 71.2% FT%
Seems low, right? Hakeem, with the beautiful fadeaway? Well, Hakeem took too many fucking jumpshots. He could make them, absolutely, but a guy with Hakeem’s physical ability and skill in the post has no goddamn business having a career FG% of 51.2% and a TS% of 55.3%. (The league average TS% over his career was 53.5%.) This is an idea I’ll expand more on, but in every competitive game of imperfect information, the player acting with initiative has to balance his action between how efficient it is and how deceptive it is. I think Hakeem chose the deceptive option too much. I call Hakeem’s choice to settle for more difficult (and aesthetically pleasing) shots the Ian Malcolm syndrome – he got so caught up wondering if he could make those shots that he never asked whether or not he should.
However, it can certainly be argued that against better defenses, such as ones teams face deep in the playoffs, deception gains value, as better defenses will be better at allowing their opponents to get efficient shots. Hakeem and his destructive playoff performances are certainly a good argument for this.
Kareem Abdul-Jabbar – 0.0 3PA, 0.56% 3PT%, 72.1% FT%
Fun fact: Like Shaq, Kareem made exactly one 3-pointer in his career. This is a tricky one. Like another 6-time NBA champion you’ll see later on this list, Kareem was essentially completely unique as a shooter. On the one hand, Kareem was nobody’s idea of a stretch big, didn’t have much of a turnaround, and wasn’t a particularly good free-throw shooter.
On the other hand, he made 15,837 of the 28,307 shots he took (55.9%), and a whole lot of those 23,307 shots were skyhooks. And Kareem’s skyhooks were nothing like the jump hooks you see today. In fact, a very good answer to the question “why does nobody shoot the skyhook anymore?” is “it’s a fucking miracle anyone was able make that shot effectively, let alone someone 7 foot 2.” Look at this shit – a lot of those are closer to midrange shots than post shots, and he’s flicking the ball over his goddamn head with his body perpendicular to the backboard. That should not be possible.
Hence, the question of “is the skyhook a ‘shot’” becomes crucial to determining if Kareem was a fairly poor shooter or one of the best shooters ever. I’m going to put him at the top of this tier and shrug my shoulders. Kareem was really good.
Tier 6: Big Men With Some Stretch
Giannis Antetokounmpo – 2.1 3PA, 28.4% 3PT%, 72.2% FT%
First things first – Despite the fact Giannis is his team’s primary ballhandler and could easily be classified as a wing, I’m calling him a big. He’s 6-11, 242, shoots under 30% from 3, and a full quarter of his shots were dunks the first year he won MVP. He’s not not a big man.
I am writing this on the night of August 31st, 2020, a pretty bad night in Giannis’ career. The Miami Heat have just taken a 1-0 lead against Giannis’ Bucks in the Eastern Conference Semifinals, and Giannis was held to 18 points on 6-12 shooting from the field and 4-12 from the line. It currently looks like Giannis may have a true Achilles’ heel when it comes to teams that can wall off the paint effectively, and looking forward his shooting stroke seems built more for catch-and-shoot situations than it is for keeping defenses honest off the dribble. This all may change in a few weeks, so hang with me here.
Giannis’ rise to two-time MVP was atypical – generally, hyper-athletic players ascend to the MVP level when they “round out” their game by developing a jumper. Giannis won his first MVP by packing on muscle and doubling down on attacking the paint. In his first MVP season, his 3PT% fell from 30.7% to 25.6%, his FT% fell from 76.0% to 72.9%. (This season, Giannis’ overall effectiveness went up even though his FT% was a truly abysmal 63.3%.) He also dunked the ball 279 times last season and 197 times this year. Instead of working on his backhand, Giannis found more ways to run around his forehand. The next several weeks will show if that’s enough to take the Bucks where they want to go. Giannis is allowed to join the Warriors when LeBron retires and not before.
Charles Barkley – 1.9 3PA, 26.6% 3PT%, 73.5% FT%
Charles makes it easier than anyone else, especially pre-shot tracking era, to do a “loss leader” analysis of his shot selection. His 26.6% 3PT% for his career is the lowest among qualified players. He also had an absolutely ludicrous career TS% of 61.2% (league average TS% over his career was 53.5%), made 58% of his career 2-pointers, and led the league in 2-point shooting percentage 5 times in a row between 1986 and 1991.
Given that data, it’s fairly easy to conclude that Charles should have just pocketed the 3-point shot, but let’s do a little experiment. Let’s assume 2 things: that Charles was taking a relatively high percentage of 3-pointers compared to long 2-point jumpers, and the 3-pointers he did take helped “keep the defense honest” and opened up the floor for his drives. (It should be noted that Charles’ overall efficiency pretty much fell off a cliff from 2-point range as his athleticism dipped at age 30, so we’re talking about prime Charles here.)
Given those assumptions, did Charles Barkley take the correct amount of 3s? For our case study, we’re going to compare Barkley’s 89-90 season to his 90-91 season, as these were the last two years he led the league in 2-point percentage and he changed his shot selection fairly dramatically.
In 1989, Charles averaged 25.2 on 60%/21.7%/72.2%, for a league-leading TS% of 66.1%. In 1990, Charles averaged 27.6 points per game on 57%/28.4%/72.2%, for a TS% of 63.5%, which broke his four-year streak of leading the league in TS%. Charles also almost doubled his 3-pointers taken per game, going from 1.2 3PA per game to 2.3. Again, we’re going to assume that Charles could not have simply turned those 3-pointers into 60%+ 2-pointers, or that he could have shot the exact same percentage from 2 if those 3-point attempts simply disappeared entirely. Without further ado:
A 28.4% 3-point shot has a TS% value of 42.6%. The league average TS% in 1989 was 53.4%. This means that every Barkley 3 had an expected value of 0.972 points per attempt, compared to a league average of 1.068. This means Barkley cost his team .096 points per 3-point attempt in ’89. Barkley’s 2-point percentage that season was 59.7%, for a TS% (we’re not even factoring in FTr) of 1.194. That means the 76ers gained .187 points every time Charles shot a 2-pointer.
This means, by my quick-and-dirty math, Charles “gave back” the added value of his 2-point attempts about every 2 times he shot a 3 – if Charles had shot 1.95 as many 3s as 2s, he would have had league-average efficiency in 1991.
Based on the above, Charles taking 1.6 more 3-point attempts per game in 90-91 to get 1.4 more 2-point attempts per game was worth it for the 76ers, although not by an overwhelming amount. The 3s made Charles less efficient, but Charles’ efficiency was so far above the league average that it was worth sacrificing some of Charles’ efficiency for volume for the 76ers. (This version of the shot creation vs. efficiency argument is a variation on “is it selfish for your best hitter to take a 6-pitch walk with 2 outs and a man on 2nd?” question brought over from baseball.)
Forgive my math, especially since I’m not very good at it. The point is that Charles was a pretty bad shooter, but his 3-point attempts were probably worth the extra 2-point attempts they generated for him.
Karl Malone – 0.2 3PA, 27.4% 3PT%, 74.2% FT%
Alright, it’s the first person I’d call a good shooter! Malone is the exception to two rules: that players improve from the foul line way less often than you think, especially after their third season (Malone went from a 48% foul shooter his rookie year to 70% his 3rd year, and ended up with a career FT% of 74.2%), and that if you’re going to take a spot-up shot, you should always take it from beyond the arc, because nobody shoots better than 50% on long 2s – Malone shot 53.6% on long 2s in 96-97 and 52.8% on long 2s in 97-98. He ducked under that for the last years of his career and there isn’t tracking data from before 96-97, but it’s safe to say he was really good at knocking down mid-range jumpers.
Kevin Garnett – 0.4 3PA, 27.5% 3PT%, 78.9% FT%
We got robbed of the best version of KG, right? Not only did his giant pre-cap contract and the Joe Smith fiasco keep him from ever getting a good supporting cast in Minnesota, he was so much better suited to the post-handcheck, pace-and-space era (and no, it is not the “everyone arbitrarily decided to shoot a bunch of 3s” era) than the era he played in. The MVP version of KG lived on midpost fadeaways, and the version who won a championship played defense and shot spot-up 20-footers. Look at what Anthony Davis gets to do with LeBron feeding him the ball and the freedom to go beyond the arc, or what Giannis is doing, and tell me KG wasn’t tragically ahead of his time.
An aside: “KG went undefeated in the 2000 Olympic team’s 1-on-1 tournament” is one of my favorite basketball tall tales that are probably true, along with “when the UCLA Freshman team with Kareem scrimmaged the varsity team, who had just had an undefeated national championship season and were about to win another championship, Kareem fucking destroyed them,” and “lane violations were created because Wilt started dunking all his free throws in high school.”
Tier 5: Guards Who Weren’t Terribly Good at Shooting
Russell Westbrook – 3.7 3PA, 30.5% 3PT%, 79.9% FT%
It should be noted that Russ’ shooting is getting worse. He was a reliable free throw shooter during the first part of his career, and was a passable if below-average jump shooter, but his jump shot and free throws have both been trending downwards. (His FT% did bounce back to 76.3% this season after last season’s 65.6% nightmare.)
It’s not the most unique observation that Russ has more in common with Charles Barkley than just about any player, especially on the micro-sized Rockets, who traded away their center to leverage Russ’ strengths (his rebounding and ability to attack the basket) and minimize his glaring weakness (shooting).
However, while Charles managed to be hyper-efficient while hemorrhaging points from the 3-point line, Russ has not. Russ’ career TS% is 53.0%, with the league average over the course of Russ’ career being 54.5%. The reasons for this are essentially “all of the reasons” – a higher proportion of Russ’ shots over his career have been 3s, his free throw rate is lower than Barkley’s was, and most importantly, his career FG% on 2-point shots (46.9%) has been lower than the league average (49.6%). Russ is effective at the basket and nowhere else, and that hasn’t been a formula for efficiency for him.
Allen Iverson – 3.7 3PA, 31.3% 3PT%, 78.0% FT%
Would an efficient version of Allen Iverson been a better version of Allen Iverson? In the eternal struggle between shot creation and efficiency, Iverson is all the way on the side of shot creation. His ability to create a decent shot for himself is at a historic level, but it was a struggle for him to create particularly good shots – his career TS% was 51.8% against a league average of 52.8%.
Conventional Wisdom on Iverson is, of course, that he was saddled with horrible teammates during his prime years in Philadelphia, and I’m not arguing that he played with a particularly talented supporting cast. During his MVP season, the players who got the most minutes after Iverson were George Lynch, Aaron McKie, Tyrone Hill, Theo Ratliff, and Eric Snow, which is a war crime. (Dikembe was injured for the majority of the 2000-01 season.)
However, let’s flip this on its head for just a second and make the presumption that resource management is a crucial part of team-building. For example, if you spend the same amount of money for a good shooter as you do for a bad one, the bad shooter will be good enough at defense to have his value, in a vacuum, be exactly as good as the good shooter’s. (The draft, player empowerment, and other factors mean this isn’t quite the case in the actual NBA, but it makes enough sense as a concept.)
During the seasons Iverson played under Larry Brown, the 76ers chose to allocate their resources towards defense. They were a top-5 team in defensive efficiency from Iverson’s rookie season until Brown’s last year with the team, 2002-03, when they finished 12th in defensive efficiency. (They lost to the Pistons in the playoffs that year, Larry Brown said “fuck it, I’d rather be with that team than keep trying to make it work with this guard who shoots all the time but can’t shoot,” and won a championship with them the next season. Larry Brown was Kevin Durant before Kevin Durant.)
Iverson’s role on these teams was to be a sin-eater. Since the 76ers spent their resources on extremely good defensive players who couldn’t create shots of average quality, Iverson’s job was to try and drag the 76er offense towards league-average by getting up as many decent shots as he possibly could. During his MVP season, his 51.8% TS% was exactly at league-average, and he shot the ball 25.5 times a game. This took some shots away from more efficient players who could have benefitted from more of a creator (Ratliff and McKie, Mutombo and Kukoc when they were healthy), and it took the burden of shooting away from some truly horrific offensive players (Hill, Lynch, Snow. The end result was that Philadelphia’s TS% was league-average at 51.9%, and they managed to have the 13th-best offensive rating in the league to go along with their #5 defensive rating, and of course they ended up making the Finals that season.
I think Iverson certainly could have benefitted from playing on a team with enough talent to allow Iverson to take a higher proportion of the shots that were efficient for him (namely, ones at the basket) while playing championship-caliber defense, but I think the 76ers may have actually made the most of Iverson’s talents.
Iverson was never more efficient than he was on the 07-08 Carmelo/Iverson Nuggets, who played at the fastest pace in the league and finished 11th in the league in offensive rating, but had the 10th-best defensive rating in the league and were swept in the first round. I think there’s a legitimate argument that while Iverson was better on paper for the Nuggets than he was for the 76ers, he provided more value to the 76ers by allowing them to allocate all the rest of their resources to defense. A rising tide may not have raised Allen Iverson’s boat that much.
We should also probably talk about the 2004 Olympic team, where Iverson led the only “Dream Team” to ever fail to win the gold medal in FGA while shooting 37.7%/36.5%/71.1%. This feels significant to me.
Derrick Rose – 2.6 3PA, 30.4% 3PT%, 82.7% FT%
Like Iverson, Rose won his MVP for sin-eating on a defensively dominant Bulls team. People seem to forget that there’s a different MVP award handed out for every regular season. Rose’s MVP win over LeBron (and Dwight Howard) in 2011 probably wasn’t the best decision, but the Bulls had finished with a better record than the Heat after not being hailed as the superteam to end all superteams before the season, and LeBron had some real late-game gaffes that allowed the Bulls to get that better record. It made a lot of sense at the time! It wasn’t just “people were angry at LeBron and don’t like giving the MVP to one guy too many times.” In any case, people would remember LeBron ending Rose’s whole shit by destroying the Bulls in the ECF and locking Rose down defensively in the 4th quarter better if he didn’t follow that up with the Unforgivable Finals.
It should also be mentioned that Rose has managed to hang around the league despite the destruction of his entire body by being a guy who can come in and knock down some jumpers off the bench. Really good free-throw shooter, too. Also, people who like Derrick Rose fucking LOVE Derrick Rose and I don’t really understand why.
Tier 4 – Wings Who Were Decent Shooters:
Julius Erving: 0.1 3PA, 29.8% 3P%, 77.7% FT%
You might think that Erving playing in the ABA from 1971 to 1976 would have given him a head start when the NBA introduced the 3-point line in 1979. It did not. He didn’t shoot 3s in the ABA, and he didn’t shoot them in the NBA either. Dr. J was also a sub-80% FT shooter, which is not great for an MVP wing. As the wing on this list who spent the most time playing before 3-pointers were anything other than a gimmick, it makes a lot of sense he’s at the bottom of this tier.
Magic Johnson: 1.2 3PA, 30.3% 3PT%, 84.8% FT%
As much as I appreciate Magic turning himself into a shockingly good free throw shooter (Magic came into the league as an 81% shooter from the line, shot 76% in his second and third years, and was consistently shooting at or near 90% before his first retirement), the jump/set shot really wasn’t a big part of his game.
LeBron James: 4.3 3PA, 34.4% 3PT%, 73.4% FT%
I’ll limit myself here, as I’ve thought about LeBron James’ jumper more than pretty much any other single thing in the last 16 years.
Kobe Bryant: 4.1 3PA, 32.9% 3P%, 83.7% FT%
Kobe’s 3-point shooting percentage will age poorly, as it’s just under the Mendoza line (33.0%) for his career. It’s important to remember he came up before the pace-and-space era, and was really the first wing on this list to shoot 3s in volume. With Kobe, the somewhat deficient shooting from distance balances with his ability to get very, very hot from the field, one of the great mid-range games in NBA history, and an incredibly reliable free-throw stroke.
As much as I’d love to make a cute argument for LeBron over Kobe, can you really say that someone who shoots free throws like LeBron is a better shooter than Kobe, who casually bet Gerald Wallace $500,000 dollars he’d make a clutch free throw? I believe you cannot.
Tier 3: The Polar Opposites
James Harden: 7.7 3PA, 36.3% 3PT%, 85.8% FT%
It’s our first 85% free throw shooter on this list of MVPs! Free throws: harder than you think. Remember how back in the Giannis section it was August 31st? It’s now 1:38 on September 2nd. This project may have been a bad idea. In any case, Harden completely revolutionized the notion of when a player can shoot a 3-pointer with a chance of going in, and in a lot of ways is the next step in the Iverson evolutionary pattern – instead of being able to drag an offensively deficient bunch to the league average, Harden is an efficient offense in a can. This season, Harden shot 22.3 field goals per game, with the majority of those attempts coming from deep, averaged 34.3 points per game, had a TS% of 62.6% compared to the league average of 56.5%, and was assisted on 13.9% of his 2-point attempts and 17.1% of his 3-point attempts. That’s mind-bending. Also, this piece that tries to expose step-back 3s as being inefficient by saying “In other words, if NBA players (save for Harden) took step-back 3s all game, their teams would score about five points fewer per game,” is perhaps not as compelling as it thinks it is. I don’t know who exactly was saying it would be a good idea for a team to only shoot step-back 3s, but that guy sure made him look like a dick.
Michael Jordan: 1.7 3PA, 32.7% 3PT%, 83.5% FT%
As our good buddy Ethan Strauss pointed out, those 3-point numbers actually look better than they should because MJ was only any good at threes during that brief period of time when the NBA moved the 3-point line in. Remember back in the Kareem section when I said we’d be looking at another player with a completely unique shooting profile? This would be him. As Kirk Goldsberry, a pretend Harvard professor who revolutionized APBRmetrics through his mastery of dots, pointed out, MJ, at least post-baseball MJ, was completely unique in both the frequency and efficiency with which he shot mid-range jumpers.
Even looking at all the tape where MJ rose up and popped in those jumpers like he was tossing change into a toll basket, I always figured MJ must have been overrated as a jump shooter: He never shot 3s well, his career FG% is 49.7%, and he must have taken a lot of shots at the rim and converted a ton of them, so his mid-range shooting percentage must have been well under 50%, right?. No, it turns out that MJ was strangely bad at layups and an absolute mid-range savant. Seriously, there is no “lost art of the mid-range game” thing happening here – MJ was on another level from every human being at mid-range shooting. Saying the kids today just don’t work on getting a good midrange jumper like MJ had is like going to the Sistine Chapel and lamenting that artists today just don’t work on ceiling brushstroke fundamentals enough.
Re-watching old MJ film through the lens of his mid-range prowess, it does stand out how willing MJ is to “settle” for those turnarounds and pull-ups – as soon as he gets to one of his spots, it’s going up immediately, even when another dribble or two might get him all the way to the rim. Remember how I mentioned the tug-of-war between efficiency and deception earlier? If you have Kareem’s skyhook or MJ’s mid-range jumper, you don’t really need to worry about it. There are pitchers who dominate with pure stuff fired into the strike zone, pitchers who use changes of speed and location to fool hitters, and then every now and again you get a guy with Mariano Rivera’s cutter.
Ultimately, I’m putting MJ ahead of Harden as a shooter, as well as everyone else that’s come before him on this list, because MJ was mainly a jump shooter, and MJ was the best scorer of all time. When you put those statements together, MJ has a hell of a case.
Tier 2: The Legitimately Elite Shooters
Steve Nash: 3.2 3PA, 42.8% 3PT%, 90.4% FT%
I don’t have much to say about Steve Nash. It seems weird in today’s climate that Nash was such a reluctant shooter, but the offenses he helmed in Dallas and Phoenix were consistently the best ones in the league, so it’s hard to hold that against him. It does feel like Nash was a precursor to Curry – brilliant shooter, genius ballhandler, swashbuckling passer, incredible finisher around the rim for his size – but was used in essentially the exact opposite way, which is a little bit interesting.
Dirk Nowitzki: 3.4 3PA, 38% 3PT%, 87.9% FT%
Given the nuanced and unique nature Dirk’s game, which mainly relied on funky mid-post and face-up moves, it is truly bizarre how long Dirk’s reputation was “the tall white guy who can shoot 3s.” None of the players who were supposed to be “the next Dirk Nowitzki” played remotely like Dirk Nowitzki, but that didn’t stop teams from falling in love with them. If Steve Novak had been playing in the Bosnia league, he probably would have been a top-5 pick. The closest thing we have to a Dirk descendant playing now is probably Jokic – there’s a lot more Dirk in him than there is in Danilo Gallinari.
Kevin Durant: 4.9 3PA, 38.1% 3PT%, 88.3% FT%
Here’s the argument for Kevin Durant being the best offensive player of all time, and I think it’s a fairly decent one: is there one team, from the Mikan Lakers to now, who would not get instantly better offensively by adding Kevin Durant to their starting lineup? With LeBron, you need to space the floor with shooters and come up with ways to get him either downhill making plays or getting touches near the basket. MJ had his completely unique mid-range game that he needs the ball to employ. Same thing with Kobe. You need to install all kinds of off-ball actions to get anywhere near the maximum value out of Steph. Any of the great post players hurts your spacing at least a little bit. KD, though? Pop him in 1964 and he’s bullying everybody in the post. He’d look very good spacing the floor for Magic and Worthy. Put him with AI on the 2001 76ers and you probably have a better version of the Westbrook/Durant Thunder. Put him in the Ron Harper spot on the MJ/Scottie/Rodman Bulls and watch the destruction. (I feel like this would have the worst chance of working, since Jerry Krause would have never shut up about him and MJ may have subsequently started putting cesium in his food, or Phil might have insisted he only play 15 minutes a game for vague triangle reasons.) Heck, the Warriors he ran through the league with might have been the worst team for maximizing his skills, because the one knock on him is that he’s not all that enthusiastic about moving without the ball, which is the staple of the Warriors offense.
On the fast break, he’s a monster. He can destroy you off the dribble. He can post up anyone. He can knock down any catch-and-shoot 3. Give him the ball in space going towards the basket and you’re dead. Anyways, it’s fascinating to me that even though KD is 7 feet tall and pretty much unstoppable once he gets a stride away from the basket, his shot is dangerous enough so that almost everything he does is off the threat of it – every touch he gets, the first thing he looks for is whether he has the space for an open 3, and he forces every defender to close out hard on him despite how screwed they’ll be if he gets past them.
Players on this list who forced rule changes:
Larry Bird: 1.9 3PA, 37.6% 3PT%, 88.6% FT%
Even though I fully believe that Kevin Durant is “objectively” a better shooter than Bird, I’m putting Bird ahead of him for this reason: he was the absolute undisputed best outside shooter in the NBA when he played. In Korea, every so often there comes a competitive gamer who is so clearly the best in the world he gets called a “bonjwa.” (Yes, I’m running out of competitive endeavors to mine metaphors from.) It happens extremely rarely, because there’s almost always a solid argument for one player or another being the best, so it’s special when it does happen. Larry Bird was a shooting Bonjwa. He led the league in 3-pointers made while shooting better than 40% from deep twice. The NBA average 3-point percentage during his career was 29.7%. He won the first 3 3-point contests. He shot nearly 90% from the line. Larry Bird was the first truly great 3-point shooter, and he was great at shooting from everywhere else too.
Tier 1: Steph By God Curry
Steph Curry: 8.2 3PA, 43.5% 3P%, 90.6% FT%
Considering how putting a ball into a basket was the original basketball skill, it’s a little bit absurd how much better at shooting a basketball Steph Curry is than every other human to have ever lived. He’s the best spot-up shooter. He’s the best shooter off the dribble. He’s the best shooter at screens. He’s the best player at using (and setting) screens to get himself open. He’s the best from deep range. (Damian Lillard can be argued for this one.) He has the best free throw percentage of all time. In a time where absolutely everyone is shooting, Steph is an unquestioned shooting Bonjwa. Of course, we learned all the wrong lessons from Steph’s 3-point revolution, but that’s a story for another time.
“Steph is really good at shooting” isn’t news, so here’s a fun fact: No superstar has sacrificed more of their 3-point percentage in pursuit of buzzer-beaters than Steph. He is 4-77 on “heaves” in his career: if he had never attempted one, his career 3-point percentage would be an even 44.0% and he would jump from 6th to 4th on the all-time 3PT% list. For comparison, LeBron has “heaved” the ball 34 times in his career. Durant, 9. Kobe, 21. Dame, 17. You get the picture.
Okay, that should wrap it up. If you actually finished this, my sincere thanks.
submitted by John_Krolik to nbadiscussion [link] [comments]


2020.10.28 15:55 ScamWatchReporter People who spam UPVOTED in certain karma threads this week

Take it as you will and assume what you want of any account that drops the same comment hundreds of times on karma
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