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Consecutive Playoff Losses For a Franchise

From 1993 to 2015, the New York Islanders lost eight consecutive playoff series, beginning with a loss in the conference finals to Montreal in 1993, and culminating in a heartbreaking, 7-game series loss last year to Washington. Last night, the Isles came from behind and defeated Florida, to win the series, four games to two.

So the streak stopped at eight for the Islanders; as it turns out, the longest streaks for consecutive playoff losses in NFL history is also at eight, with two of those streaks being active. [click to continue…]

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Yesterday, I wrote how the NBA seemed to undervalue the three-point shot for many years. While the 3-point shot was consistently the better EV play, and the ratio of three-point shots to overall shots was increasing, it didn’t seem to increase quickly enough. As pointed out in the comments, one could make a pretty similar claim about pass/run ratio in the NFL.

It’s a little misleading to start things in 1970, since that’s really the beginning of the dead air era in football history. Pass efficiency was very high in the late ’40s and parts of the ’60s, so a chart beginning in 1970 would inaccurately imply a linear progression of the passing game. That said, because first down data is spotty the farther back we go, and because of the complexity involved in deciding how to treat the AFL, I’m going to limit myself today to the period from 1970 to 2016. [click to continue…]

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NBA 3-Point Attempts and Going For it On 4th Down

In overly simple terms (ignoring things like fouls, rebounds, game theory, etc.), the expected value of a 2-point field goal attempt is the 2-point field goal percentage multiplied by 2, and the expected value of a 3-point field goal attempt is the 3-point field goal percentage multiplied by 3. Here’s a look at the EV for both 2-point and 3-point attempts in every NBA season going back to 1979-1980, courtesy of basketball-reference:

nba

The inflection point came right around 1990; after that, the 3-point shot was associated with a higher expected value, and since ’97-’98, the 3-point shot has about 12% more EV than a 2-point shot. Now, I know just about nothing about the NBA and even less about NBA analytics, but it’s easy to draw a couple of conclusions from this chart. One would be that teams should be taking more 3-pointers, even though “traditional coaches” have not been fans of the 3-point shot. It’s easy to look at this chart and dismiss it, and say that a team shouldn’t take a bunch of 3 pointers just because the math says it makes sense. On the other hand, you have the Golden State Warriors. [click to continue…]

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Jalen Ramsey, and Defensive Backs In The Draft

Florida State cornerback/safety Jalen Ramsey is going to be the first defensive back selected in the 2016 Draft. Ramsey may go as high as #3 overall to San Diego, as the first non-quarterback off the board. On a recent Bill Barnwell podcast — and by the way, he has a new podcast that you should subscribe to — Bill wondered when we will see the day when a cornerback goes first overall.

Technically, that already happened, when Colorado State’s Gary Glick was the first pick off the board in ’56 (Glick played safety, running back, and even kicked for the Steelers). But in the common era draft beginning in 1967, the highest a defensive back has been drafted is second overall, when the late great Eric Turner was drafted by the Browns. The trio responsible for that pick? GM Ernie Accorsi, head coach Bill Belichick, and
defensive coordinator Nick Saban. Those guys knew a thing or two about defensive back play, and were comfortable taking a safety with the second pick.

But in general, the first defensive back goes off the board at around the 10th pick, although it is happening a bit earlier in recent years (the median spot for the top DB has been 6 over the last 15 drafts). The graph below shows the slot where the top defensive back was taken in every draft, and no, that 1974 Draft is not a bug: [click to continue…]

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Quarterbacks Going 1-2 in the NFL Draft, Part II

A year ago, I wrote that quarterbacks going with the first two picks in the NFL Draft was a pretty unusual thing. From 1967, the start of the common draft, through 2011, it happened just four times. Since then, it has happened two more times, and now will apparently happen in 2016, too, after the Eagles sent way too many draft picks to the Browns for the right to pick second overall. We can save for another day how this was a shrewd move by Cleveland — if nothing else, the Browns do have a history of getting a boatload to move down, including in trades for Sammy Watkins and Julio Jones — and a head-scratcher for the Eagles.

This move also opens up San Diego as the team “in control” of the draft, non-QB edition. The Chargers will now take the first non-QB off the board. Unfortunately, that’s a lot less exciting than it sounds, although it may come with it the ability to extract some trade value, potentially from the Cowboys at #4. Let’s take a look at the six times since 1967 that quarterbacks went 1-2, and who was the first non-QB taken. [click to continue…]

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NFL Gray Ink Sack Leaders

Watt has a lot of gray ink in a short amount of time

Watt has a lot of gray ink in a short amount of time

Gray Ink tests are fun ways to measure player dominance by giving some — but not too much — credit to longevity. In simplest form, gray ink tests give 10 points for finishing 1st in a category, 9 points for finishing 2nd, and so on. Let’s use Kevin Greene, third all-time (shorthand for since 1982, of course) in career sacks with 160, and Bruce Smith, the career leader with 200, as examples.

Smith was the better player — he was an 11-time Pro Bowler and an 8-time AP first-team All-Pro, compared to just 5/2 for Greene — and consequently was a clear first-ballot Hall of Famer. For whatever reason, it took Greene 12 years, but this summer, he will finally be inducted into the Hall. Given the fact that Smith has 25% more career sacks than Greene, you probably think that Smith was the better pass rusher. To that, the Gray Ink test says not so fast, my friend. [click to continue…]

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Matt Waldman 2016 Rookie Scouting Portfolio

Every April 1st, friend-of-the-program Matt Waldman (@MattWaldman) releases his Rookie Scouting Portfolio. The RSP is, well, insane. It’s a 300-page draft guide that not only provides rankings and analysis of 167 players, but also provides over 1,548 pages of scouting checklists and play-by-play notes.

Matt does top-notch work year round, and I can confidently state that the Rookie Scouting Portfolio is the most comprehensive analysis of rookie draft prospects at the offensive skill positions I’ve ever seen. But it’s not just about rankings and his analysis; he makes the evaluation process as transparent as possible to the reader, by identifying:

  • Players that have boom-bust potential, players who may have already maxed out their potential, or players with great upside.
  • Breakdowns/rankings of players by individual skills at the position.
  • Player comparisons to past NFL players based on style and builds.
  • Overall rankings and comparisons in cheat sheet/table format with pertinent measurements and workout results.
  • Overall rankings with written explanations in paragraph form.
  • Overrated, underrated, and long-term projects.
  • Fantasy-friendly tiered cheat sheets.

Matt documents what he sees with play-by-play detail. Yes, that’s a lot of work. No, you don’t have to read that part of the book to get tremendous value from the RSP. And here’s something pretty neat: Matt ranks every player graded by position and then writes a post-draft analysis with rankings assembled in a tiered cheat sheet. This is free with the RSP purchase and available a week after the NFL Draft.

The RSP is $19.95 and available at www.mattwaldman.com. Matt donates 10 percent of every sale to Darkness to Light, a non-profit that combats sexual abuse through individual community and training to recognize how to prevent and address the issue. All told, the RSP contains nearly 1300 pages this year. If you’re the type who likes to read testimonials, well, Matt has lots of those. He’s also provided a few sample evaluations from prior years that you can review.

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The best player in the AFC South is in this photo.

The best player in the AFC South is in this photo.

Good article from Peter King this morning on J.J. Watt and the injury struggles he dealt with last year.  King also noted that Watt has 69 sacks over the last four seasons, the most in the NFL.  In fact, that’s the second most by any player in any four-year stretch over at least the last 31 years. FRom 1985 to 1988, Reggie White had 70 sacks, and he did it in seven fewer games (he missed the first three games of ’85 due to being a member of USFL,1 and then four games in ’87 due to the players’ strike.)  Of course, White did play in a friendlier era for sacks (2.63 sacks per game vs. 2.37 over the last four years), so cross-era comparisons always have their limitations.

But I thought it would be interesting, especially in light of Jared Allen retiring, to look at the leaders in sacks on a trailing four year basis: [click to continue…]

  1. The Eagles, after starting 0-2, paid a million dollars to Memphis to essentially buy White from the league. []
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You probably heard that Kobe Bryant has retired from the NBA. In his final game, he put up a whopping 60 points, albeit on a modern record 50 shot attempts. On twitter, Topher_Doll asked me what were some of the greatest final games in NFL history.

Since 1970, there have been 37 times where a player eclipsed 100 yards from scrimmage in his final game. This includes Calvin Johnson, but not Johnny Manziel, who rushed for over 100 yards in his last game but is not exactly out of the NFL just yet. The record-holder is Domanick Williams (formerly Davis) of the Houston Texans, who had a very successful but short career that was ended by a knee injury. [click to continue…]

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Some Thoughts on the 2016 NFL Schedule

Some thoughts as I review the 2016 schedule:

Monday Night

  • There are 17 games on Monday evenings this year: two during the opening week (Pittsburgh/Washington at 7:10 Eastern, Rams/49ers at 10:20), one every other week, and as usual, none during week 17.
  • Carolina, Chicago, Houston, Minnesota, the Giants and Jets, Philadelphia, and Washington each have two MNF games this year. Meawhile, the Browns, Jaguars, Chiefs, Dolphins, Chargers, and Titans do not play on Monday this season.
  • Since hosting two games on Monday Night Football in 2011, the Jaguars have not played on Monday Night Football. Every other team has played on MNF at least once since 2013, but Jacksonville’s streak will extend to at least 2017 now.
  • The Vikings host the Giants in week four. Minnesota has not had a home game on Monday Night since December 20, 2010. That was the second-longest stream in the NFL, a week shorter than Houston. The Texans streak will continue for another year: Houston plays two Monday Night games this year: in Denver and in Mexico (against Oakland).

Thursday Football

  • There are 18 games on Thursday this year, although not all are on what is labeled the Thursday Night Football schedule. There is no game in week 17, but three on Thanksgiving — Minnesota/Detroit, Washington/Dallas, and Pittsburgh/Indianapolis — and one every other week during the season.
  • Every team plays on Thursday at least once this year, with Carolina, Minesota, Dallas, and Denver getting that honor two times. The Panthers and Broncos play in the season opener and then later during the traditional TNF schedule, while the Vikings and Cowboys play (other teams) on Thanksgiving and then each other one week later on TNF. The NFL seems to be making a new trend out of this: last year the Packers and Lions played a memorable TNF game a week after both teams played on Thanksgiving, the Bears and Cowboys played seven days after both franchises played on Thanksgiving 2014.

[click to continue…]

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The 2016 NFL Schedule

The color-coded schedule is back!

Download the Excel file here

That Excel file contains full page and wallet-sized copies of the schedule, in both color and black and white. On the wallet-sized copies, the line between weeks 8 and 9 has been enlarged — that is where you want to fold the paper in half to put in your wallet.

iPhone 6s page: http://www.footballperspective.com/wp-content/uploads/2016/04/nfl-2016-iphone-6s.png

Go to that page on your phone, then hit your power and home button at the same time to take a photo (or hit the button on the middle of the Safari browser and click ‘save image.’) The schedule has been formatted to fit an iPhone 6s screen, so you can always carry the schedule with you.

Go to that page on your phone, then hit your power and home button at the same time to take a photo (or hit the button on the middle of the Safari browser and click ‘save image.’) The schedule has been formatted to fit an iPhone screen, so you can always carry the schedule with you.

2016 nfl schedule_final

Commentary to follow, but for now, enjoy! And, of course, please report any bugs you see.

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Perhaps giving Fisher more picks isn't the answer

Perhaps giving Fisher more picks isn’t the answer

In 2012, St. Louis took advantage of one of the most inefficient aspects of the NFL: the top of the draft is a seller’s market, with teams desperately willing to overpay in a variance-seeking endeavor that usually disappoints. That year, the Rams moved down four spots, by trading the 2nd overall pick to Washington for the 6th overall pick…. and also picking up the 39th pick, a first round pick the following year (#22 overall), and a first round pick the year after that (#2 overall, incredibly). That trade was a steal for St. Louis the second it was made, but it became a home run when Washington tanked in 2013 (of course, one could argue that the home run was called back when the 2nd overall pick in 2014 was used on Greg Robinson, who has been one of the worst tackles in football since being drafted).

Today, the Rams — now in Los Angeles, of course — were on the buy side of things. And, as usual, to move up in the draft is quite expensive. THe Rams moved up from #15 to #1, and also gained a 4th (#113) and a 6th (#177) back in this year’s draft. But the price was exorbitant: Los Angeles had to give up both 2nd round picks it has this year (#43, courtesy of the Sam Bradford/Nick Foles swap last season, and #45, the team’s original selection), its third round pick (#76), and next year’s 1st and 3rd rounders. And while that doesn’t have quite the screaming headline of “Washington sends 3 first round picks for RG3,” make no mistake: the Rams gave up a massive amount to move up to #1, presumably to draft either Carson Wentz or California’s Jared Goff.

To simplify things, let’s try to cancel some things out. The 4th and 6th round picks received by the Rams this year is roughly equivalent to the 3rd giving up by Los Angeles next year; given the time value of the draft pick, a 6th round pick, it can be argued, makes up for getting to use that pick a year earlier, even if it’s a round later. I am sure both teams would have done this deal even if you take those three picks out of the mix, and it was probably included just to give Los Angeles a bit more in draft picks (instead of giving up 4 draft picks for 1 this year, now it’s 4 for 3). My hunch is the Rams were the one asking to throw in that last piece of the puzzle, even if it’s probably a better deal for Tennessee (since the time value of the draft pick is usually overstated). [click to continue…]

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Yesterday, I looked at the Pythagenpat records for all teams since 2000. Since I crunched all that data, I thought it would be fun to look at the biggest outlier teams.

The 2003 Steelers were not very good. Pittsburgh went 6-10, scoring 200 points and allowing 327 points. Because of regression to the mean, the ’04 Steelers were expected to be a little better, and finish with 7.2 wins. Instead, behind a rookie Ben Roethlisberger and an outstanding running game and defense, the Steelers went 15-1, exceeding expectations by 7.8 wins.

Last year’s Panthers also went 15-1, and have a similar story. Cam Newton, the AP MVP, was more of the driving force, of course, but a great running game and defense powered the team. But based on a mediocre ’14 season, Carolina was expected to win only 7.8 games, so the 2015 Panthers exceeded expectations by 7.2 wins.

The third biggest outlier? That would be the ’07 Patriots, who went 16-0 with a projection of just 9.5 wins. The next year, New England was projected to win 10.99 games, and… went 11-5.

The table below shows each team since 2000, and their number of projected and actual wins. The table is sorted by the difference column: [click to continue…]

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The Browns have been running in place

The Browns have been running in place

A good read from ESPN yesterday about new Clevleand Chief Strategy Officer Paul DePodesta, who is being labeled as the man who will (attempt to) bring Moneyball philosophies to the NFL. Putting aside the inaccuracy of that statement — Moneyball philosophies mean different things to just about everyone, and such philosophies are already a staple in many organizations — there will be a certain spotlight cast on DePodesta in Cleveland. And, according to some statistical analysts, that’s a bad thing.

At MIT Sloan Sports Analytics Conference in March, unilateral fear existed inside analytics community that systemic ineptitude of Browns franchise will be too substantial for even DePodesta to repair. Failure would damage legacy of beloved industry pioneer and set field of sports data science back decades. “If you love analytics and want it to grow and succeed in the NFL, then you know Cleveland is a nightmare scenario,” states NFL executive with 20 years of experience in analytics. “Cleveland is a crazy, terrible place for this to be tested in football.”

The idea that Cleveland is too toxic to be resurrected is…. well, it’s more supported by the data than you might think. Certainly DePodesta could turn things around, but if he doesn’t, he’ll just be the next man in a long line of failed Browns executives. You won’t be surprised to learn that Cleveland has the worst winning percentage in the NFL since re-entering the league in 1999. But even accounting for the fact that the Browns have been bad, Cleveland has still underperformed to the tune of about 26 wins over the last 16 years, most in the NFL.

How did I arrive at that number?

  • First, I calculated each team’s Pythagnpat winning percentage in each season beginning in the year 1999, which is based solely on the number of points scored and allowed by each team. For example, in 2014, the Browns scored 299 points and allowed 337, which translates to a 0.429 Pythagenpat winning percentage (the Browns actually beat that slightly, by going 7-9).
  • Next, I ran a regression on the years 1999 to 2014, using Year N Pythagenpart winning percentage to predict Year N+1 wins. This would, in theory, help out the Browns, because Cleveland would be expected to win fewer games than the average team in Year N+1 because the Browns typically have a poor Year N performance. The best-fit formula was 0.311 + 0.376 * Yr_N_Pyth_Win%. This shows that regression to the mean is a large factor, because past performance only accounts for 38% of what goes into a team’s projection for Year N+1; the remainder is a constant for all teams.

Using Cleveland’s 2014 line as an example, the 2015 Browns would have been expected to win 7.6 games, because the 2014 team had 6.9 Pythagenpat wins, and regression to the mean drives that number towards 8 wins. But Cleveland won just 3 games last year, falling 4.6 wins shy of expectation. And that’s only the second-most disappointing season of the new Browns era: in ’08, Cleveland fell 4.7 wins shy of its Pythagenpat prediction. Take a look at every Cleveland season from 2000 to 2015 (obviously there was no prediction for ’99, since there was no ’98 team): [click to continue…]

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Guest Post: Testing the Tape on Running Back Metrics

Brian Malone, a writer for dynastyleaguefootball.com, has put together a great guest post today. You can follow him on Twitter at @BrianMaloneFF. Thanks to Brian for today’s article!


Testing the Tape

Projecting a player’s NFL potential from his college football performance is something like predicting a player’s potential as a tennis pro from his performance in the collegiate racquetball club.  Sure, there’s correlation, but the variance in level of competition and style of play create ample noise.  No wonder folks on Twitter spend hours debating hand size: at least it’s a standardized measure, and it’s not obviously worse than things like collegiate yards per carry.

The better approach is film study.  Unfortunately, I’m not any  good at it.  Indeed, I don’t even know how to tell whether anyone else is any good at it.  But that’s a problem we can attack.  And the natural starting point is Matt Waldman’s Rookie Scouting Portfolio (RSP), which has the benefits of quantified observations, independent analysis, and a 10-year history.

The RSP includes a checklist of observed skills and abilities, including things like “Runs behind pads/Good pad level” and “Catches ball with proper hands technique.”  The RSP assigns a weight to each and combines them into what I’ll call trait scores (i.e., “Power” and “Balance”) and an overall score.

Note the three steps to this process: (1) observing the skills and abilities; (2) assessing the importance of observed skills and abilities to each trait; and (3) assessing the importance of each trait to a player’s overall ability.  The first step is off limits: we’ll take the observations as given.  But the others are fair game: we have the tools to use Waldman’s observations, plus a little math, to build a traits-based model for predicting a prospect’s success. [click to continue…]

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Over the last week, I’ve looked at the biggest quarterback declines and quarterback turnarounds when it comes to career records. But there were some limitations in those studies, so today, I want to use a new method.

I assigned 20 games of .500 play — i.e., a 10-10 record — to each quarterback’s record after every start of his career. Then I checked to see which quarterbacks had the biggest declines/improvements in record/rest-of-career record using these metrics.

Let’s take Marc Bulger as an example. He started 95 games in his career. At one point, he was 28-11, which is a 0.718 winning percentage. For the rest of his career, he went 13-43, for a 0.232 winning percentage. If we add 20 games of .500 play to his first stint, that makes him 38-21, which translates to a 0.644 winning percentage. For his rest of career, his record would go down as 23-53, a 0.303 adjusted winning percentage. That’s an adjusted winning percentage decline of 0.341, the most of any quarterback in history. [click to continue…]

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Jim Brown, Bobby Boyd, and Retiring Early

The GOAT.

The GOAT.

Jim Brown is the standard bearer for athletes who retired too young, and for very good reason. Brown led the NFL in rushing yards, rushing touchdowns, yards from scrimmage, and total touchdowns in his final season in 1965, all while averaging 5.3 yards per run and 9.6 yards per reception. With D’Brickashaw Ferguson choosing to retire “early” yesterday, on the heels of Calvin Johnson doing the same thing, I decided to run a quick query on the players who were best in the final season of their career.

The table below shows all players who had at least 10 points of Approximate Value in the final season of their career (Megatron had 10 points of AV in 2015; Ferguson had 9) and whose last season came in 2014 or earlier.1  As it turns out, Brown ranks tied for first on this list, next to Colts defensive back Bobby Boyd.

Here’s how to read the table below. Boyd’s last season came in 1968 with Baltimore.  Playing left cornerback, he accumulated 21 points of AV that year at the age of 31. He received a number of awards that season: he was 1st-team All-Conference (that’s what the + sign means) according to the Sporting News, and a 1st-team All-Pro choice by the AP, Pro Football Writers, NY Daily News, Pro Football Weekly, and the UPI. [click to continue…]

  1. Note that Patrick Willis had just 3 points of AV in his final year in the NFL. []
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Friend of the program Bryan Frye is back for another guest post. As regular readers know, Bryan operates his own fantastic site, http://www.thegridfe.com. You can view all of Bryan’s guest posts here, and follow him on twitter @LaverneusDingle.


Floating around the internet, there are copious metrics for measuring quarterback performance. Some are very basic (passing yards, completion rate), while others are quite complex (EPA, WPA). Some are open-source (passer rating, ANY/A), while others are proprietary (DVOA, Total QBR). It seems there is a stat to cover just about every aspect of QB play, so the last thing we need is another useless number.

Well, I didn’t get that memo.

Today, I’m going to look at a somewhat abstract measurement for career value, based on adjusted yards per attempt relative to league average. I prefer ANY/A and my own TAY/P (and the different iterations of both metrics), but gaps in the record books mean we can only go so far with either.1 With AY/A, we can go back to 1932, the very first season of the “official stat” era in the NFL.

The methodology is simple and straightforward. I took Pro Football Reference’s AY/A Index Scores for every quarterback with at least 1500 career pass attempts. If you are familiar with PFR’s advanced passing stats, you know they are based on three seasons’ worth of data (years n-1, n, and n+1), and a score of 100 represents league average output.2 To find the AY/A+ score itself, you simply multiply a player’s z-score by fifteen and add the product to 100. Using this knowledge, I reverse engineered the passing Index Scores in order to find the number of standard deviations above or below average each quarterback’s AY/A was. I then multiply that number by pass attempts to come up with an abstract career value metric. I also did this for replacement level, using one standard deviation below average as the baseline for replacement play.

The formulas:

Value over average = [(AY/A Index Score – 100)/15]*Attempts

Value over replacement = [(AY/A Index Score – 85)/15]*Attempts

Like I said, this isn’t forking any lightning in the realm of quarterback analysis. It’s just a quick and dirty way to approximate career productivity based on a well-known metric.

The Results

The table below shows the abstract career value of the 182 quarterbacks who met the 1000 attempt threshold. Read it thus: Peyton Manning played 266 career games and had 9380 pass attempts. His career AY/A+ score was 116. This gives him a total value of 10005 above average and 19385 above replacement (this is the metric by which the table is sorted). Note that the table below does list all 182 quarterbacks, but for ease of scrolling, only the top 25 are displayed by default. You can change that using the dropdown arrow on the left, or you can search for your favorite passer.

RkQuarterbackGAttAY/A+ValRepl
1Peyton Manning26693801161000519385
2Tom Brady2257792115779215584
3Dan Marino2428358112668615044
4Drew Brees2178085112646814553
5Brett Favre30210169106406814237
6Joe Montana1925391118646911860
7Steve Young1694149125691511064
8Fran Tarkenton2466467110431110778
9Aaron Rodgers1264047124647510522
10Ben Roethlisberger1715423114506110484
11Dan Fouts1815604113485710461
12John Elway2347250106290010150
13Warren Moon2086823107318410007
14Philip Rivers164533911346279966
15Johnny Unitas211518611138038989
16Tony Romo155433111646208951
17Kurt Warner124407011643418411
18Ken Anderson192447511338788353
19Jim Kelly160477911031867965
20Donovan McNabb167537410725087882
21Len Dawson211374111639907731
22Otto Graham126262612950777703
23Boomer Esiason187520510724297634
24Sonny Jurgensen218426211131257387
25Roger Staubach131295812243387296
26Carson Palmer160544310518147257
27Dave Krieg213531110517707081
28Y.A. Tittle204439510926377032
29Phil Simms164464710721696816
30Mark Brunell193464010721656805
31Trent Green120374011229926732
32Sammy Baugh165299511835946589
33Roman Gabriel183449810617996297
34Eli Manning185622710006227
35Rich Gannon157420610719636169
36Steve McNair161454410515156059
37Craig Morton207378610922726058
38Randall Cunningham161428910617166005
39Troy Aikman165471510412575972
40Bob Griese161342911125155944
41John Hadl224468710412505937
42Jim Everett15849231039855908
43Jeff Garcia125367610922065882
44Drew Bledsoe194671798-8965821
45Vinny Testaverde233670198-8935808
46Matt Ryan126453010412085738
47Terry Bradshaw168390110718205721
48Bart Starr196314911225195668
49Norm Van Brocklin140289511427025597
50Jim Hart20150761013385414
51Daunte Culpepper105319911021335332
52Matt Hasselbeck209533010005330
53Neil Lomax108315311021025255
54Joe Theismann167360210614415043
55Jeff George131396710410585025
56Ron Jaworski18841171038234940
57Chris Chandler18040051038014806
58Ken O'Brien129360210512014803
59Matt Schaub141327110715264797
60John Brodie20144911012994790
61Joe Namath140376210410034765
62Bobby Layne17537001049874687
63Steve Beuerlein147332810613314659
64Jay Cutler13443541012904644
65Brad Johnson17743261012884614
66Steve Bartkowski129345610511524608
67Steve Grogan14935931049584551
68Neil O'Donnell125322910612924521
69Bernie Kosar126336510511224487
70Brian Sipe12534391049174356
71Steve DeBerg206502498-6704354
72Daryle Lamonica151260111017344335
73Danny White166295010713774327
74Earl Morrall255268910916134302
75Ken Stabler18437931025064299
76Bert Jones102255111017014252
77Marc Bulger96317110510574228
78Kerry Collins198626195-20874174
79Russell Wilson64173512124294164
80Sid Luckman128174412023254069
81Billy Kilmer17029841059953979
82Chad Pennington89247110914833954
83Jim Harbaugh177391810003918
84Charley Johnson16533921024523844
85Charlie Conerly16128331059443777
86Jim Plunkett157370110003701
87Michael Vick14332171024293646
88Joe Ferguson186451997-9043615
89Cam Newton78241910711293548
90Joe Flacco122407098-5433527
91Mark Rypien10426131058713484
92Norm Snead178435397-8713482
93George Blanda340400798-5343473
94Jeff Blake11932411012163457
95Matthew Stafford93369199-2463445
96Don Meredith104230810710773385
97Jay Schroeder11828081035623370
98Aaron Brooks9329631023953358
99Lynn Dickey15231251012083333
100Jake Delhomme10329321023913323
101Jeff Hostetler15223381069353273
102Frank Ryan126213310811383271
103Bill Kenney10624301058103240
104Greg Landry14623001069203220
105Tommy Kramer129365198-4873164
106Archie Manning151364298-4863156
107Alex Smith126361998-4833136
108Jim McMahon11925731035153088
109Brian Griese9327961011862982
110Jim Zorn140314999-2102939
111Bobby Hebert118312199-2082913
112Jake Plummer143435095-14502900
113Gus Frerotte147310699-2072899
114David Garrard8622811046082889
115Babe Parilli189333098-4442886
116Jack Kemp122307399-2052868
117Billy Wade12825231023362859
118Gary Danielson10119321067732705
119Doug Williams8825071011672674
120Bill Nelsen9019051067622667
121Jon Kitna141444294-17772665
122Andy Dalton7724971011662663
123Elvis Grbac10524451011632608
124Stan Humphries88251610002516
125Chris Miller98289298-3862506
126Wade Wilson125242810002428
127Milt Plum129241910002419
128Tom Flores10617151066862401
129Tobin Rote149290797-5812326
130Doug Flutie9221511011432294
131Bob Waterfield9116171066472264
132Frankie Albert9015641066262190
133Scott Mitchell99234699-1562190
134Erik Kramer83229999-1532146
135Ed Brown15419871011322119
136Bill Munson10719821011322114
137Tony Eason9015641055212085
138Jason Campbell90251897-5042014
139Kyle Orton87271296-7231989
140Richard Todd119296795-9891978
141Andrew Luck55210699-1401966
142Rodney Peete104234697-4691877
143Eddie LeBaron134179610001796
144Tony Banks96235696-6281728
145Ryan Tannehill64224896-5991649
146Cotton Davidson111175299-1171635
147Ryan Fitzpatrick113347392-18521621
148Charlie Batch81160410001604
149Jay Fiedler76171799-1141603
150Mike Livingston91175197-3501401
151Bubby Brister99221294-8851327
152Byron Leftwich60160597-3211284
153Don Majkowski90190595-6351270
154Steve Bono88170196-4541247
155Mike Tomczak185233793-10911246
156Matt Cassel100257492-13731201
157Marc Wilson126208193-9711110
158Sam Bradford63229292-12221070
159Josh McCown77195693-9131043
160Eric Hipple102154695-5151031
161Dan Pastorini140305590-20371018
162Vince Ferragamo75161594-646969
163Josh Freeman62204892-1092956
164Kordell Stewart125235891-1415943
165Trent Dilfer130317289-2326846
166Tim Couch62171492-914800
167David Carr94226790-1511756
168Mark Sanchez75226789-1662605
169Derek Anderson68154390-1029514
170Billy Joe Tolliver79170789-1252455
171Rex Grossman54156289-1145417
172Chad Henne64195488-1563391
173Frank Tripucka75174588-1396349
174Dave Brown73163488-1307327
175Mike Pagel132150986-1408101
176Kyle Boller67151983-1722-203
177Jack Trudeau67164483-1863-219
178Mike Phipps119179983-2039-240
179Mark Malone73164882-1978-330
180Joey Harrington81253882-3046-508
181Rick Mirer80204381-2588-545

I normally like to point out a few curiosities I notice in the data, but I’d rather just present the numbers and leave the comments to the readers. What sticks out to you? Oh, and one note: back in 2006, Chase did some back-of-the-envelope calculations that had Rick Mirer as the worst quarterback of all time. 10 years later, not much has changed.

  1. Pro-Football-Reference doesn’t have ANY/A prior to 1969. I don’t have TAY/P prior to 1991; even without including first down data, I can only go back to 1963 before I run out of complete sack data. []
  2. Except in 1932, when there is no year n-1, and the current year, when there is no n+1. []
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Fran Tarkenton, Warren Moon, and Career Turnarounds

Getting 62 wins is much easier the second time around

Getting 62 wins is much easier the second time around

A couple of days ago, I looked at the quarterbacks with the best records before ultimately finishing their careers with losing records. Today, the reverse, and we start with Hall of Famer Fran Tarkenton, who has a fascinating career split.

Tarkenton went 124-109-6 in his 18-year career with the Vikings and Giants. His first 62 wins took him a long time; at age 32, he was 62-86-4 after a week 6 loss to the Bears in 1972. At 24 games under .500 and with a career 0.421 winning percentage, Tarkenton was a five-time Pro Bowler with little to show for it and zero career playoff appearances.

But for the rest of his career, he won another 62 games, and he did so much quicker, going 62-23-2. That’s 41 games over .500 and a 0.724 winning percentage. That’s extremely impressive, of course, enough to make Tarkenton have a career 0.531 winning percentage. And, among quarterbacks who finished their career at .500 or better, Tarkenton is the only quarterback to ever be 24 games below .500 at any point in his career.

Although one could argue that Warren Moon had an even more remarkable career turnaround. I’ve written before about the terrible Oilers franchise that Moon joined in the mid-’80s. After 43 games, Moon had a 10-33 record. While it took Tarkenton 152 games to get to 24 games below .500, Moon was one shy of that mark in over 100 fewer games! At that point, the odds of Moon — then 30 years old — finishing his career with a winning record would have been seen as astronomically low. Yet he did just that, going 92-68 over the remainder of his career. [click to continue…]

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The Dallas Cowboys are rumored to be drafting a replacement for Tony Romo with the fourth pick in the first round. In general, teams with bad offenses are the ones that draft quarterbacks, and technically, the Cowboys would fit that mold given the team’s struggles last year. But, of course, the Cowboys expect to have a good offense in 2016 with a healthy Romo, so I was curious how unusual it would be for a good team to spend a first round pick on a quarterback.

The table below shows the offensive SRS grade and the number of wins1 for each team that has drafted a quarterback since 1971 in the year preceding such draft. For example, the 2014 Bucs and Titans had very bad offenses and went 2-14 before drafting quarterbacks with the first two picks. That’s how things typically go, but not always. [click to continue…]

  1. Pro-rated to 16 games for non-16 game seasons. []
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The under-appreciated Jim Hart

The under-appreciated Jim Hart

Yesterday, I noted that Cleveland Browns quarterback Bernie Kosar had a 39-23-1 career record after the 1989 season, but actually finished his career with a losing record. That sounded pretty wild to me, so I wanted to investigate further.

Kosar’s Browns defeated the Steelers in the 1990 season opener, which brought his career record to 40-23-1, or 17 games over .500. But Kosar went just 13-31 over his final 44 games; after a 0.633 winning percentage in his first 64 games, he posted a 0.295 winning percentage for the remainder of his career.

So I wondered, among quarterbacks who finished their career with a .500 record or worse, does Kosar hold the record for most games above .500 at any one point? As it turns out, that honor goes to Jim Hart. Younger fans likely know very little about Hart, but he’s one of the better quarterbacks not in the Hall of Fame. He spent 18 years with the Cardinals, and made the Pro Bowl in four straight seasons from ’74 to ’77. By 1981, he ranked third all time in career passing yards and ninth in passing touchdowns. He made it into the top 50 on Brad Oremland’s list, and snuck into the top 30 on my list.

But if you look at the raw numbers, you’re likely to be unimpressed. That’s because the bulk of his career took place during the ’70s, but also because he retired with an 87-88-5 record. But as of November 20th, 1977, Hart had a 69-47-5 record, a 0.591 winning percentage. Of course, it was all downhill from there for Hart, who went just 18-41 (0.305) for the rest of his career. [click to continue…]

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Here is Colin Kaepernick’s ANY/A average in each of the last four years:

kaep decline

Kaepernick won't listen to comments about his declining ANY/A

Kaepernick won’t listen to comments about his declining ANY/A

That is not a very promising graph. Last year, I wrote about how Kaepernick, Cam Newton, and RG3 were a unique trio of young quarterbacks who had declined in two consecutive years. Well, 2015 was where those quarterbacks diverged: Newton won the MVP, Griffin did not take a single snap, and Kaepernick continued his decline.

Kaepernick’s 2012-2015 represents just the 44th instance where a quarterback saw his ANY/A decline in three straight seasons (minimum 100 pass attempts each year). But he’s even an outlier in this group. He was one of just six quarterbacks who was younger than 25 at the start of the first season, joined by Pat Haden, Jeff Blake, Bernie Kosar, Rick Mirer, and Ken O’Brien. And he and Aaron Brooks are the only two players to have a dropoff of at least 0.5 ANY/A in each season.

Here’s how to read the table below, using Philip Rivers as an example. His four-year stretch began at the age of 28 in 2009, when he had an ANY/A average of 8.3. Over the next three years, that dropped to 7.77, 6.64, and then 5.45. His lowest decline in any of those seasons was 0.53 ANY/A, and this is the column by which the table is sorted. His total decline from Year 1 to Year 4 was 2.85 ANY/A. Finally, in the next season — what would be 2016 for Kaepernick — Rivers rebounded with a 7.79 ANY/A average. For players who did not have 100 pass attempts (and for Kaepernick) in season N+4, that cell is blank. [click to continue…]

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More Thoughts on the Jaguars Passing Attack

Over the last couple of days, I’ve been looking at measuring the age of a team’s passing attack. On Friday, I noted that the Jaguars had the 2nd youngest passing offense in the NFL behind only Tampa Bay. And yesterday, I measured the youngest passing offenses in football history, with Jacksonville checking in at #20.

The Jaguars threw for 4,428 gross passing yards last season (or, 8,856 combined passing/receiving yards), though, so that makes them a bit more of an outlier. The table below shows all teams with at least 8,500 combined passing/receiving yards, and ranks them in ascending order based on average age: [click to continue…]

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Yesterday, I measured the age of each team’s passing attack by calculating the yards-weighted age of each player who gained either a passing or receiving yard. Today, the historical results.

I’ve written a bit about Terry Bradshaw and his terrible rookie season of 1970, mostly in the context of number one picks taking a long time to break out. But here’s something that often gets lost in the mix: Bradshaw was just one of many inexperienced players on the ‘70 Steelers.

Bradshaw played as a rookie that year at age 22 (Terry Hanratty also started 6 games, and was also 22). The top 6 players in receiving yards on the ’70 Steelers were wide receiver Ron Shanklin (age 22), wide receiver Dave Smith (23), tight end Dennis Hughes (22), fullback John Fuqua (24), wide receiver Hubie Bryant (22), and wide receiver Jon Staggers (22). Incredibly, five of those six players were rookies, with Frenchy Fuqua being the sole exception — and he was drafted in 1969! In the ’70 draft, Pittsburgh took Bradshaw with the 1st overall pick, drafted Shanklin at 28, Staggers in the 5th round, and Smith in the 8th round, while both Hughes and Bryant were undrafted free agents that year. That’s unbelievable, and makes the ’70s Steelers passing attack akin to an expansion team — or rather, an expansion team with almost no access to the veteran market. As a result, Pittsburgh’s 1970 passing attack ranks as the youngest in history: [click to continue…]

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Bortles led the 2nd youngest passing offense in the NFL

Bortles led the 2nd youngest passing offense in the NFL

After a 1-4 start to the season, it might have felt like an odd time to write about how the Jacksonville Jaguars could have the next great offense. But in many ways, Jacksonville’s passing attack only got better as the season went along. Some (the majority?) of the big numbers were more of a function of quantity than quality, but the numbers really were big. Consider:

  • Blake Bortles finished tied for 2nd in passing touchdowns and 7th in passing yards
  • Allen Robinson finished tied for 1st in receiving touchdowns and 6th in receiving yards. He also had the highest yards per reception average of any player with 1,000 receiving yards
  • Allen Hurns also hit the 1,000-yard mark, and had the 6th highest yards per reception average of any player with 1,000 receiving yards. Hurns and Robinson were one of just four duos (Jets, Broncos, Cardinals) to have two players gain 1,000 receiving yards.

That’s an impressive trio by any standard, but what’s incredible is that Hurns was born in November of 1991, and he is the oldest of the three! So how young is the Jaguars passing attack compared to other teams? I have decided to create a passing yards-weighted age grade for each passing attack. And in doing so, I chose to count passing yards and receiving yards equally, which of course has the effect of making the quarterback(s) equal to half of the team’s passing game. I’m OK with that. [click to continue…]

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AV-Adjusted Team Age (Offense) from 2012-2015

Background:

In 2012, the Jaguars went 2-14 with an offense centered around Blaine Gabbert/Chad Henne, Maurice Jones-Drew, Cecil Shorts, and Justin Blackmon. Since then, the team has been rebuilt, and gotten better and younger. Among offensive players, only Marcedes Lewis was on the team during each of the last four years. I’ll have more on the Jaguars tomorrow, but given the way the Jets have moved from young and bad to old and good, I think that’s the more interesting team to analyze today.

Here’s how to read the table below. In 2012, the Jets offense had an age-adjusted AV of 26.9; that dropped to 26.4 in 2013, then rose to 27.5 in 2014 and up to a league-high 29.2 last season. That’s an average of 27.5, but more interesting (to me) is the variance of 1.1 years. [click to continue…]

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AV-Adjusted Team Age (Defense) from 2012-2015

Part of the last non-awful Bears defense

Part of the last non-awful Bears defense

Background:

I thought it would be fun to do a quick checkdown and look at the AV-Adjusted team age for each defenses over the last four years. Here’s how to read the table below, using the Bears as an example. In 2012, Chicago’s average age on defense was 29; in 2013, it was 27.7, then 27.5, and finally, 26.1 last season. That means the Bears average age has had a variance of 1.1 years, the second largest in the data set behind only San Diego. [click to continue…]

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2015 AV-Adjusted Team Age

In each of the last four years, I’ve presented the AV-adjusted age of each roster in the NFL. Measuring team age in the NFL is tricky. You don’t want to calculate the average age of a 53-man roster and call that the “team age” because the age of a team’s starters is much more relevant than the age of a team’s reserves. The average age of a team’s starting lineup isn’t perfect, either. The age of the quarterback and key offensive and defensive players should count for more than the age of a less relevant starter. Ideally, you want to calculate a team’s average age by placing greater weight on the team’s most relevant players.

My solution has been to use the Approximate Value numbers from Pro-Football-Reference.com.  The table below shows the average age of each team, along with its average AV-adjusted age of the offense and defense. For the second year in a row, the Jaguars and Rams were the two youngest teams in the NFL; this year, though, the team formerly known as St. Louis took the top spot.

The average AV-adjusted team age last season was 27.1 years; the Rams (25.6) and Jaguars (25.8) were the only teams below 26, while the Jets (28.2) and Colts (28.6) were the only teams above 28 years. Here’s how to read the table below, using the St. Louis line: the Rams were the youngest team in the NFL in 2015, with an average age of 25.6 years as of September 1, 2015. The team’s offense had an AV-adjusted average age of 25.0, the youngest in the NFL, while the defense was at 26.0, the second-youngest. [click to continue…]

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Bob Ford, a longtime fan of Pro-Football-Reference and Football Perspective, has contributed a 2-part guest post on Yards Per Carry Leaders. Bob is the owner and founder of GOATbacks.com, which looks at the greatest running backs of all time. Thanks to Bob for yesterday’s and today’s articles!


Yesterday, I looked at the YPC leaders for the 46 seasons since the merger was completed, 1970-2015 at the 100/120/180-carry cutoffs. Today, a look at the YPC leaders since 1970 at three higher thresholds. [click to continue…]

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Bob Ford, a longtime fan of Pro-Football-Reference and Football Perspective, has contributed a 2-part guest post on Yards Per Carry Leaders. Bob is the owner and founder of GOATbacks.com, which looks at the greatest running backs of all time. Thanks to Bob for today’s (and tomorrow’s) article!


I’ve been curious about YPC leaders over the years, particularly as they’re sorted through increasing numbers of carries. Over the next two days, I will look at the YPC leaders using six different carry minimum thresholds: 100, 120, and 150 today, and 180, 220, and 280 carries tomorrow. These cutoffs weren’t arrived at in an analytically rigorous way, just through instinct and personal judgment. I ran a number of different carry thresholds and simply tried to keep my statistical eyes peeled; in my view, these are at least 6 of the minimums where interesting changes seemed to emerge.

As a general rule, though not an absolute one, I’m in the camp that regards YPC as, at best, a questionable stat when it comes to assessing skill and performance, and at worst a misleading and even bunkum stat, to borrow a term from Chase and the crew over at Intentional Rounding. Don’t get me wrong, I’m not suggesting YPC is useless. In fact in some narrow contexts I think it’s even key. But I think it’s woefully overused and over relied on, and I do regard it with suspicion when it comes to assessing rushing and running back value and effectiveness, particularly in “real-game” situations. I think the same holds for mobile quarterbacks, too.

I decided to look at YPC leaders for the 46 seasons since the merger was completed, 1970-2015. Again, no special reason, just to make things more manageable. This would probably get really interesting if we included all pre-merger seasons, but I didn’t do that here. If anyone does, kudos. At any rate, here are the YPC leaders since 1970, sorted at 6 different carry thresholds. [click to continue…]

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