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Tom Brady Is Very Popular; So Is His Birthday

Tom Brady was born on August 3rd, 1977. In the Super Bowl, Brady’s Patriots defeated the Los Angeles Rams, who had two players — running back Todd Gurley and pass rusher Dante Fowler — who were born on August 3rd, 1994. Rookie defensive back and All-Pro Derwin James was born two years later, on August 3rd, 1996.

Those four were not picked at random: there were 12 players active in the NFL last season who were born on August 3rd, making it an extremely popular birthday in pro football circles. What’s more, there were 203 players who played in the NFL in 2018 who were born “around August 3rd” — i.e., within 15 days of either side of that date. For fans of astrogoloy, these are your Leos, natural born leaders described as “dramatic, creative, self-confident, dominant and extremely difficult to resist, able to achieve anything they want to in any area of life they commit to.”

In the abstract, knowing that 203 players were born in one 31-day window probably means nothing to you. But I did this same analysis for every day in the calendar year. Christian McCaffrey was born on June 7th, the only such player active last season. As it turns out, the 31 days including and surrounding June 7th (i.e., May 23rd through June 22nd) produced only 147 players.  These are your Gemini, who are generally thought to dislike repetition and routine. Oh, and that window just brings in June 22nd, notable for being the only day on the calendar where no 2018 NFL players were born.

The graph below shows each of the 365 days of the year on the X-Axis. [1]Eric Kendricks is the only February 29th birthday, and to make life simple, I included him with the March 1 birthdays The Y-Axis shows how many players were active in the NFL last season with birthdays plus or minus 15 days of each date. As you can see, Brady’s August 3rd birthday comes in the middle of an extremely popular window for NFL birthdays, while McCaffrey’s June 7th birthday is at the center of one of the graph’s valleys. [continue reading…]

References

References
1 Eric Kendricks is the only February 29th birthday, and to make life simple, I included him with the March 1 birthdays
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Guest Post/Contest: PFRWhacks

Today’s guest post/contest comes from Adam Harstad, a co-writer of mine at Footballguys.com. You can follow Adam on twitter at @AdamHarstad.


Like most of you, [1]I assume. I like to spend my weekends building custom databases of NFL statistics. This past weekend, while doing just that, I happened to notice that Marshall Faulk topped 2,000 yards from scrimmage in both 2000 and 2001 despite playing just 14 games each year. Which sent me scrambling to the Pro-Football-Reference.com player season finder [2]Obviously. so I could share on Twitter the novel observation that Marshall Faulk was, indeed, good at football.

As luck would have it, the humble proprietor of Football Perspective just happened to be sitting at home, trolling around on Twitter, and likewise playing with various historical databases. [3]On second thought, I doubt luck played any role. He saw my tweet and responded in kind, with a list of all NFL players sorted by average yards per game from age 25 to 28.

All of this inspired a fun back-and-forth between various other users on Twitter which culminated in me providing a list of all running back seasons with 250+ carries and 50+ yards per game receiving. It’s a rather short list featuring just 8 total seasons. Marshall Faulk accounted for four of those eight seasons, consecutively, from 1998 to 2001.

I quickly noticed an interesting thing about that last list, though. Not only did Marshall Faulk account for half of those seasons in NFL history, but he actually had the top four by receiving yards per game. In fact, if we adjust our “receiving yards per game” baseline from 50 to 54, we wind up with this list, instead.

Now that is a rather more impressive list. Using just two simple cutoffs, we had managed to create a list that was just four names long, and every single one of those names was “Marshall Faulk.”

Seguing away for a second… in the early days of the internet, before there were continents composed solely of cat pictures (or handy NFL season finders to query, for that matter), people would resort to pretty much anything to keep themselves entertained. One game that sprung from these dark times was known as “Googlewhacking”. A Googlewhack was two words that, when entered together into the search bar of the eponymous Google, matched just a single result on the entire internet.

For instance, there was once a time when searching the words “ambidextrous scallywags” (but without the quotation marks) would return just a single match. This was then a successful Googlewhack. Googlewhacks were, by their very nature, ephemeral constructs, since the very act of publishing a Googlewhack would cause the published result to show up on Google and would therefore cause the words to lose their Googlewhack status. [continue reading…]

References

References
1 I assume.
2 Obviously.
3 On second thought, I doubt luck played any role.
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One of my favorite sabermetric baseball articles of all time was written by Sky Andrecheck in 2010 — part as a meditation on the purpose/meaning of playoffs, and part as a solution for some of the thorny logical concerns that arise from said mediation.

The basic conundrum for Andrecheck revolved around the very existence of a postseason tournament, since — logically speaking — such a thing should really only be invoked to resolve confusion over who the best team was during the regular season. To use a baseball example, if the Yankees win 114 games and no other AL team wins more than 92, we can say with near 100% certainty that the Yankees were the AL’s best team. There were 162 games’ worth of evidence; why make them then play the Rangers and Indians on top of that in order to confirm them as the AL’s representative in the World Series?

Andrecheck’s solution to this issue was to set each team’s pre-series odds equal to the difference in implied true talent between the teams from their regular-season records. If the Yankees have, say, a 98.6% probability of being better than the Indians from their respective regular-season records, then the ALCS should be structured such that New York has a 98.6% probability of winning the series — or at least close to it (spot the Yankees a 3-0 series lead and every home game from that point onward, and they have a 98.2% probability of winning, which is close enough). [continue reading…]

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