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I like trivia, and Chris Brown asked me a good question on twitter yesterday:

The game Brown was referencing was the Patriots performance against the Saints in week 2 of the 2017 season. Here was the receiving breakdown on the New England side:

Player Tm Pass Yd Rec Yd
Rob Gronkowski NWE 0 116
James White NWE 0 85
Chris Hogan NWE 0 78
Phillip Dorsett NWE 0 68
Rex Burkhead NWE 0 41
Brandin Cooks NWE 0 37
Dion Lewis NWE 0 11
James Develin NWE 0 6
Jacob Hollister NWE 0 5
Tom Brady NWE 447 0

Brady threw for 183 yards to his wide receivers (Hogan, Dorsett, and Cooks), 143 yards to running backs (White, Burkhead, Lewis, Develin) and 121 yards to his tight ends (Gronkowski and Hollister). So that means Brady threw for 400+ passing yards with just 40% of his passing yards coming from his wide receivers. [click to continue…]


Week 1 Game Scripts (2017): Ravens Flip The Script

Two different Ravens running backs had more carries than Flacco had attempts in week one.

Last season, no team was more pass-happy than the Baltimore Ravens. Joe Flacco and the Ravens led the NFL in pass attempts along with both pass ratio and pass identity. Flacco threw at least 30 passes in every game last year. The Ravens threw 50 passes in a game they won 38-6 in a remarkable display of the team’s pass-only identity.

Well, in week 1 of the 2017 season, the Ravens threw just 18 times and on only 29.5% of all plays, both of which were league-lows. Terrance West and Javorius Allen combined for 40 carries, and while both players were on the team last year, clearly something has changed in Baltimore. The Jaguars and Bills also stood out as very run-heavy in week 1: Jacksonville spent the fourth pick on Leonard Fournette, so that makes a lot of sense, while the Bills are always run-heavy in the Tyrod Taylor/LeSean McCoy era.

On the Game Scripts notes: the Rams led the way with the best Game Script of week 1, courtesy of a blowout win over the Colts. And just two teams won with negative Game Scripts in the opening slate of games: the Chiefs and Lions both won by double digits, but were the only two teams to pull off fourth quarter comebacks. [click to continue…]


Sometimes, the headlines speak for themselves. After last night — the Chargers lost when the potential game-tying field goal was blocked in the final second — Los Angeles nee San Diego has now lost 18 of its last 23 games decided by 8 or fewer points.

Query Results Table
Poin Poin Poin
Rk Tm Year Date
Time Opp Week G# Day Result OT PF PA PD
1 SDG 2017 2017-09-11 10:20 @ DEN 1 1 Mon L 21-24 21 24 -3
2 SDG 2016 2016-12-24 1:00 @ CLE 16 15 Sat L 17-20 17 20 -3
3 SDG 2016 2016-12-18 4:25 OAK 15 14 Sun L 16-19 16 19 -3
4 SDG 2016 2016-12-04 4:25 TAM 13 12 Sun L 21-28 21 28 -7
5 SDG 2016 2016-11-27 1:00 @ HOU 12 11 Sun W 21-13 21 13 8
6 SDG 2016 2016-11-13 4:05 MIA 10 10 Sun L 24-31 24 31 -7
7 SDG 2016 2016-11-06 4:25 TEN 9 9 Sun W 43-35 43 35 8
8 SDG 2016 2016-10-30 4:05 @ DEN 8 8 Sun L 19-27 19 27 -8
9 SDG 2016 2016-10-23 4:05 @ ATL 7 7 Sun W 33-30 OT 33 30 3
10 SDG 2016 2016-10-13 8:25 DEN 6 6 Thu W 21-13 21 13 8
11 SDG 2016 2016-10-09 4:25 @ OAK 5 5 Sun L 31-34 31 34 -3
12 SDG 2016 2016-10-02 4:25 NOR 4 4 Sun L 34-35 34 35 -1
13 SDG 2016 2016-09-25 4:25 @ IND 3 3 Sun L 22-26 22 26 -4
14 SDG 2016 2016-09-11 1:05 @ KAN 1 1 Sun L 27-33 OT 27 33 -6
15 SDG 2015 2016-01-03 4:25 @ DEN 17 16 Sun L 20-27 20 27 -7
16 SDG 2015 2015-12-24 8:26 @ OAK 16 15 Thu L 20-23 OT 20 23 -3
17 SDG 2015 2015-12-13 1:03 @ KAN 14 13 Sun L 3-10 3 10 -7
18 SDG 2015 2015-11-29 1:03 @ JAX 12 11 Sun W 31-25 31 25 6
19 SDG 2015 2015-11-09 8:30 CHI 9 9 Mon L 19-22 19 22 -3
20 SDG 2015 2015-11-01 1:02 @ BAL 8 8 Sun L 26-29 26 29 -3
21 SDG 2015 2015-10-25 4:05 OAK 7 7 Sun L 29-37 29 37 -8
22 SDG 2015 2015-10-18 4:25 @ GNB 6 6 Sun L 20-27 20 27 -7
23 SDG 2015 2015-10-12 8:30 PIT 5 5 Mon L 20-24 20 24 -4

For his career, Philip Rivers has a 54-26 record in games decided by more than 8 points, and a 43-54 record in games decided by 8 or fewer points. Read differently, Rivers has lost 28 *more* times in close games than in non-close games. That is (for now) tied with Rich Gannon for the largest spread ever. [click to continue…]


Sacks Are Coming From Lighter Players

In 1994, the “average” sack came from a player that weighted 266 pounds. Wait, what do you mean by average sack? Well, if you look at all 937 sacks in 1994, and identify the weight of the sacker on each sack, you can calculate the weight of the average sack in each season. John Randle was 290 pounds, and he had 13.5 sacks that year, so he gets 13.5 times as much weight a player with one sack. The graph below shows the weight of the player producing an average sack in each year since 1982. As you can see, it peaked in the mid-’90s, and has declined slightly since.

However, players in general are getting heavier, including in the front seven. The graph below shows the average weight of a player in the front 7 — weighted by the number of starts by such a player — for each year since 1982. That data is in orange; the blue line showing the average sack weight is still included in the chart for reference.
[click to continue…]


In 1998, Randall Cunningham may have been the best quarterback in football.  Cunningham was 35.4 years old as of September 1st of that season. If it wasn’t Cunningham, it was probably Vinny Testaverde (34.8 years old as of 9/1/98), or  Steve Young (36.9), or Chris Chandler (32.9), or John Elway (38.2).  Troy Aikman (31.8) and Doug Flutie (35.9) also had great seasons, three other quarterbacks — Dan Marino (37.0),  Steve Beuerlein (33.5), and Rich Gannon (32.7) — finished in the top 20 in passing yards.

That means 10 of the top 20 quarterbacks in passing yards in 1998 were 31.8 years old or older as of September 1st of that year.    Thirteen years later, things were very different, as 8 of the top 16 passers in 2011 by passing yards were under 28 years old as of September 1st, with four being under 25: Cam Newton (22.3), Matthew Stafford (23.6), Josh Freeman (23.6), Andy Dalton (23.8), Mark Sanchez (24.8), Matt Ryan (26.3), Joe Flacco (26.6), and Aaron Rodgers (27.7).

I calculated the average age of quarterbacks in the NFL for each season since 1950, using the methodology described here. The short version: calculate what percentage of league-wide passing yards was produced by each player, calculate that player’s age as of September 1st of that season, and that calculate the league-wide age of all passers, weighted by their percentage of league passing yards. The results below: [click to continue…]


Inexperienced Receiving Games

The 2008 Giants were very experienced; the 2009 Giants were not.

In ’08, New York had Amani Toomer and Plaxico Burress as the team’s starting receivers; Toomer retired after the year, while Burress shot himself in a nightclub late in the ’08 season and missed all of the ’09 and ’10 seasons.

The top 7 receivers on the ’09 Giants were the other Steve Smith (24 years old in ’09), Mario Manningham (23), Hakeem Nicks (21), Kevin Boss (25), Ahmad Bradshaw (23), Domenik Hixon (25), and Brandon Jacobs (27). Entering the 2009 season, Smith had 637 career receiving yards, Manningham had 26, Nicks had 0, Boss had 502, Bradshaw had 54, Hixon had 601, and Jacobs had 359.  Derek Hagan, who finished 8th on the ’09 Giants with 101 receiving yards, was the most accomplished receiver entering the year by virtue of his 645 career receiving yards entering 2009.

On a weighted average, that means the 2009 Giants receiving group entered the year with just 318 career receiving yards (by reference, the 2008 Giants were at 2,608). What do I mean by weighted average? Well, Smith had 28.7% of the 2009 Giants receiving yards, and he had 637 career receiving yards prior to 2009; therefore, his 637 receives 28.7% of the team weight. On the other hand, Manningham and Nicks had, together, 38% of the Giants receiving yards in 2009, and they had, together, just 26 career receiving yards entering 2009. The table below shows the full calculation, with the result equaling a weighted average of 318 career receiving yards. [click to continue…]



Jerry Rice was really, really good for many, many reasons.  Here’s one: he led his teams in receiving yards a whopping 15 times in his career.  In 1985, Roger Craig led the 49ers in receiving yards during Rice’s rookie season. Then, from ’86 to ’96, Rice led San Francisco in receiving yards every season.  In 1997, Rice tore his ACL and was limited to just two games; as a result, Terrell Owens led the team in receiving.  In ’98 and ’99, though, it was Rice again who led the 49ers in receiving yards, before a 27-year-old Owens outgained a 38-year-old Rice on the ’00 49ers.

In 2001, Rice was in Oakland, and a 35-year-old Tim Brown beat Rice by 26 receiving yards (1165-1139) to lead the Raiders in receiving. But in 2002 and 2003, Rice — at 40 and 41 years of age — led Oakland in receiving. So from 1986 to 2003, Rice led his team in receiving yards in 15 of 18 seasons, with the exceptions being due to a torn ACL, losing out to a future Hall of Famer 11 years his junior, and losing out to a Hall of Famer 4 years his junior by 26 yards. That’s why he’s the greatest of all time.

But Henry Ellard was pretty darn good, too. Ellard played for 16 seasons in the NFL, and other than his rookie season and his final two seasons, he led his team in receiving yards every other year of his career.   During the prime years of Jim Everett’s career — 1988 to 1990 — Ellard ranked 1st, 1st, and 2nd in the league in receiving yards per game.  But he still led the Rams in receiving yards the other years, too, finishing as the leader receiver on Los Angeles each year from ’84 to ’93.  When Ellard joined the Redskins in ’94, he eclipsed the 1,000 yards mark and led Washington in receiving in ’94, ’95, and ’96.  In the process, Ellard became the first and only player to lead his team in receiving yards in 13 straight seasons. [click to continue…]


Brown continues to dominate the NFL.

Antonio Brown averaged “only” 12.1 yards per reception last year, although his great reception, receiving yards, and receiving touchdown totals earned him a third straight first-team All-Pro selection. If Brown wasn’t so good and just 28 years old, you might look at that average and think Brown was on the decline or at least was becoming less of a big play threat.

But that’s not really true: with 22 receptions (in 15 games) of at least 20+ yards, Brown had the third most big plays of any receiver last year, and 21% of his catches went for at least 20 yards. What really hurt Brown’s average was that he also caught a ton of short passes: he had 57 receptions of 10 or fewer yards. Kelvin Benjamin caught 63 passes for 941 yards last year, a 14.9 yards per reception average. But while that sounds good, Benjamin only caught 10 passes — or 16% of his total — for 20+ yards. How did Benjamin average nearly three more yards per catch than Brown? You probably already figured this one out: just 20 of his receptions (32%) went for 10 or fewer yards. Either Benjamin wasn’t running short routes or he wasn’t catching passes on those routes. If it’s the latter, it’s a bad thing; if it’s the former, well, it’s also a bad thing (relative to Brown, at least) that all he was doing was running long routes and Brown still caught more long balls than him!

The graph below shows the top 100 wide receivers and tight ends in receiving yards last season, sorted by number of 20+ yard receptions. In addition, I have included the percent of their receptions that went for 20+ yards, the number of receptions that went for 10 or fewer yards, and that percent as well.
[click to continue…]


We know that Amari Cooper is a better receiver than Kenny Stills, but who is the better big play threat? Or, more specifically, who was the better big play threat last year?

To answer this question, most people would focus on one metric: yards per reception. Most people are wrong. [click to continue…]


Gray Ink For Percentage of Team Receiving

On Thursday, I presented a new way to look at wide receivers, focusing on both how the receiver dominated his teammates (i.e., by getting a large share of the pie) and how much his offense dominated the league (i.e., how much better/worse than average his team’s passing attack was).

Since I presented the full dataset covering the years from 1970 to 2016, I thought we might as well use that information in other ways. For example, let’s say you typed Steve Largent into the search box on that post.  You would see that Largent was a monster when it came to dominating his teammates: in 1978, he was responsible for 33.6% of the Seahawks Adjusted Catch Yards, which ranked 3rd in the league.  In five years — 1980, 1981, 1983, 1986, and 1987 — he ranked 4th in the NFL in percentage of team ACY.  In ’85, he ranked 5th, and in ’79 and ’84, he ranked 6th.  That’s remarkable:

If you calculate his gray ink – which means giving him 10 points for a 1st place finish, 9 for a 2nd place finish, and so on, he had 59 points of gray ink in this category.  Remember, % of Team ACY is simply a measure of what percentage of the pie each receiver was able to devour, and % of Team ACY Rk shows where they rank in the league in a given season.  I would never use this as the only way to rank a receiver (more on this in a second), but it is an interesting way. Why?

Receiving production is based on a lot of things outside of a wide receiver’s control — for example, how good his quarterback is, or how often his team passes.  But this isolates that by only comparing how the receiver fared compared to his teammates.  That’s why I like to use this as a check against other metrics.  Below shows the leaders in gray ink in this category since 1970.  Largent, as you can see, ranks 2nd because you always know who is going to rank 1st: [click to continue…]


I spent some time discussing Gary Clark’s 1991 season yesterday. It was really impressive in two notable respects: he accounted for a huge percentage of his team’s production, and his team’s production was easily the best in the league.

What was even more impressive? What Gene Washington did in 1970. That year, the 49ers had a phenomenal passing attack: San Francisco averaged 7.6 ANY/A, while no other team was above 6.0. John Brodie was the AP MVP because of his great passing numbers, but what was arguably more impressive is what Washington did that year. Playing for the best passing offense in football1, Washington caught 23% of the team’s passes, 37% of the 49ers receiving yards, and 48% of San Francisco’s receiving touchdowns.

If you calculate Adjusted Catch Yards with a 5-yard bonus on receptions and a 20-yard bonus on touchdowns, Washington had 1,605 ACY out of the 49ers 4,620 total team ACY, or 35%. That’s even higher than what Clark did on the ’91 Redskins (33%). On the other hand, WR1s tended to get slightly more attention on 1970 offenses than on 1971 offenses. So here’s what I did:

1) Calculate the ACY for each receiver on each team since 1970. For Clark in ’91, this was 1,890.

2) Calculate the percentage of team ACY for each receiving season since 1970. For Clark, this was 33%; for Washington, it was 35%.

3) Calculate the average percentage of team ACY for the top N receivers in the league each season, with N being equal to the number of teams in the NFL. For 1970, this was 29%; for 1991, it was 27%.

4) Calculate each receiver’s percent over average; for both Clark and Washington, this means +6%.

5) Calculate each receiver’s team RANY/A for each year. Clark’s Redskins were at +3.14, while Washington’s 49ers were at +3.45.

6) Plot those seasons in the graph below. [click to continue…]

  1. And along with the ’66 Packers, the only offenses to average at least 7.50 ANY/A from 1961 to 1975. []

Anyone who has spent any time studying football analytics knows one truth: teams are not aggressive enough on fourth down. For example, in situation-neutral contexts, it’s always advisable to go for it on 4th-and-1. The value of possession has become increasingly important in the modern game, where offenses are so adept at gaining yards and scoring points, and the likelihood of conversion is so high that the trade-off of 40-50 yards of field position for a chance to keep possession is almost always worth it. Possession, after all, is worth about 4 points: if having 1st-and-10 at the 50 yard line is worth 2 points, then being on defense in that situation is worth -2, making the swing between having the ball and not having the ball worth 4 points.

So are NFL teams becoming smarter when it comes to 4th down decision making? I looked at all 4th-and-1 plays since 1994 that (i) came in the first three quarters, (ii) with the offense between the 40s, and (iii) with the team on offense either leading or trailing by no more than 10 points. From 1994 to 2004, teams went for it on these 4th-and-1 situations about 28% of the time. Then, from ’05 to 2014, teams went for it 35% of the time. But over the last two years, offenses have stayed on the field for these fourth downs over 40% of the time both years. Take a look: [click to continue…]


Leaders in Percentage of Team Targets

On Friday, I wrote about Rob Moore’s 1997 season, when he set the still-standing record for targets in a year. Moore had 208 targets, but as alluded to in that post, he did not set the record for percentage of team targets in a season, which is simply targets divided by team pass attempts (excluding sacks).

That honor belongs to Brandon Marshall, who was targeted on 40% of all passes for the 2012 Bears, and wound up with a post-1978 record 46% of the Bears receiving yards that year.  Remarkably, Marshall saw over 30% of his team’s targets on three different teams, and saw 29% of a fourth franchise’s targets in a season (2015 Jets). The table below shows all players since 1992 with at least 30% (okay, 29.5%) of their team’s targets in a season:

[click to continue…]


Not Rob Moore

If you find yourself talking about Rob Moore in the summer of 2017, it’s probably for one of four reasons.

1) You are a diehard Jets or Cardinals fan choosing to reminisce about Boomer Esiason and the halcyon days of the ’90s.

2) You just finished watching Jerry Maguire. That movie, which was released in December 1996, saw Cuba Gooding Jr. play the role of Rod Tidwell. Gooding’s character wore 85 and played wide receiver for the Arizona Cardinals, just like Moore (who even had a bit role in the movie, playing himself).

3) You are researching the best players in Supplemental Draft history, and Moore’s name came up. A star at Syracuse, Moore graduated early (back when it was still unusual for undergraduates to enter the draft), and therefore elected to enter the Supplemental Draft. The move cost the Jets the 8th pick in the 1991 Draft, which the Eagles used on Tennessee offensive lineman Antone Davis. Moore was the much better player.

4) You were wondering which player in the last 25 years (and, perhaps, for much longer) saw the most targets in a single season in NFL history. After some searching, you found out that the answer was Rob Moore, with 208 targets for the 1997 Cardinals.

Wait, what? Of all the players in the last 25 years, Rob Moore is the single-season leader in targets? The single-season leaders in receptions, receiving yards, and receiving touchdowns are Marvin Harrison, Calvin Johnson, and Randy Moss, respectively. The most targets (since 1992) that Jerry Rice ever saw was 176, and that was in 1995, when he gained 1848 receiving yards while playing for a 49ers team that threw 644 passes, the 2nd most in the NFL. So how did — just two years later — Rob Moore see 32 more targets than Rice in ’95? [click to continue…]


Guest Post: Passing Volume vs. Passing Efficiency

Today’s guest post comes from Ben Baldwin, a contributor for Field Gulls and Bryan’s site, http://thegridfe.com. You can find more of Ben’s work here or on Twitter @guga31bb. What follows are Ben’s words.

Arguing on the internet

A common argument on the internet (e.g. Twitter, where I spent too much time) is that the efficiency of players like Dak Prescott and Russell Wilson in their rookie seasons (and subsequent seasons, for Wilson) was not impressive because they were not asked to throw the ball as much. Once they are asked to throw more often, the argument goes, we can expect their efficiency to fall off. Here is one of many, many examples:

Do quarterbacks really look good because they throw less? [click to continue…]


Receiving TD Concentration Index (By Passer)

Gronk Smash

On Monday, I looked at the concentration index scores for a number of quarterbacks based on the number of touchdowns thrown to each receiver (more details on the formula available there and here). Today, the reverse: how diverse (or not diverse) were receivers with respect to the number of quarterbacks from whom they caught TDs?

Marques Colston, for example, caught 100% of his touchdowns from Drew BreesRob Gronkowski has caught all but one of his touchdowns from Tom Brady. And Mark Clayton caught 94% of his touchdowns from Dan Marino.

At the bottom of the list are two of the most underrated receivers by modern fans.   Both were superstars in college and very high draft picks, but “disappointed” in the pros.  That’s probably because they were stuck with a revolving door of bad quarterbacks.

Joey Galloway caught 77 career touchdowns and was the 8th pick in the ’95 Draft, but he is chronically underrated due to the bad quarterback play he experienced. He only had double digit touchdowns with one quarterback: an in-his-40s Warren Moon.  His top four quarterbacks were responsible for only 51% of his career touchdowns!  Galloway played with a lot of quarterbacks, and most of them were below-average.

The other receiver with a concentration index of less than 11% was former number one overall pick Irving Fryar.  Regular readers may recall that Fryar is the odd duck who set his career high in receiving yards at age 35 while playing with Bobby Hoying!  Fryar has over 3,000 yards with three franchises, a very rare feat.  He spent his 20s with the terrible Patriots back when that was a thing, and he led New England in receiving yards in ’90, ’91, and ’92, then led the Dolphins in receiving yards in ’93, ’94, and ’95, and then led the Eagles in receiving yards in ’96 and ’97!  It’s pretty impressive to lead your team in receiving yards for eight straight seasons, but it’s really impressive to do it for three different franchises. [click to continue…]


Bell had a lot of valuable yards last year.

All yards gained on special teams are done outside of the context of the series (down and distance) environment that defines most games. A kickoff return from to the 30 or to the 40 represents a difference of 10 yards, but those 10 yards are not as valuable as the difference between a gain of 5 yards and 15 yards on 3rd-and-10. The former are, quite literally, special teams yards. They don’t provide any value in gaining any additional first downs, or keeping a drive alive. This is why we don’t spend a lot of time thinking about all-purpose yardage leaders, or the difference between a kickoff returner who averages 28.0 yards per return or 24.0. Special teams yards, while obviously valuable, are — just as obviously — the least valuable yards possible.

On a 3rd-and-10, a 15-yard pass provides a significant amount of value by providing a first down. But let’s get a bit more precise: the first 10 of those yards were really valuable. The last 5? Well, those were special teams yards. The difference between gaining 10 yards and gaining 15 yards on 3rd-and-10 isn’t that significant: well, it’s about as significant as returning a kickoff for 30 yards or 35 yards. Those last 5 yards don’t help a team move the chains. [click to continue…]


Two years ago, I wrote this post titled “Take Away His X Best Carries and He’s Average.” The idea was simple: Suppose you sort each running back’s carries in descending order by yards gained. How many carries would we need to take away from him to drop his production to at or below average?

Browns running back Isaiah Crowell ranked 9th in yards per carry last year, with an impressive 4.81 average gain. But that number may be a bit misleading, to the extent it made you think that Crowell was consistently churning out big gains. Crowell was responsible for the longest run of the season last year, an 85-yard run in week 2 against the Ravens. And, for what it’s worth, it was one of the easiest long runs you’ll ever see:

In the last game of the year, Crowell had a more impressive 67-yard run against the Steelers. But here’s the thing: outside of those two runs, Crowell averaged just 4.08 yards per carry on his other 196 carries.

There were 42 running backs last year who had at least 100 rush attempts; those players averaged 4.19 yards per carry last year. So if you remove Crowell’s two best carries, he falls below that average.

An impressive Powell movement

On the other hand, Steelers running back Le’Veon Bell averaged 4.86 yards per carry last year, and his six best runs went for 44, 38, 33, 26, 25, and 24 yards. Remove those, and Bell still averaged 4.23 yards per carry, which means you need to remove his seven best runs to drop him below average.

Jets running back Bilal Powell was the star of this metric.  He averaged 5.51 yards per carry last year, but he was a consistent producer of big gains.  He had 12 runs of 13+ yards, and you need to remove all 12 to bring Powell below average.  Remove those 12 carries and his average finally dips to 4.16 yards per carry.

Below are the 19 running backs to exceed that 4.19 yards per carry average last year, and the fewest number of carries you would need to remove to bring their production below average: [click to continue…]


2016 AV-Adjusted Team Age: Overall

On Tuesday and Wednesday, we looked at the average age for each team’s offense and defense in 2016. Today, let’s look at the overall picture (ignoring special teams). By that measure, the Jaguars, Browns, Rams, Bucs, and Texans have the five youngest teams in the NFL. Take a look: [click to continue…]


2016 AV-Adjusted Team Age: Defense

Being young isn’t by itself a virtue: the Browns ranked in the bottom 5 in points allowed, yards allowed, net yards per attempt allowed, net yards per rush allowed, turnovers forced, and first downs allowed. But Cleveland was, by far, the youngest defense in the NFL last season.

Yesterday, we looked at the age-adjusted offenses from 2016. Today we do the same for defenses, and the Browns were the youngest group in the league last year, with an average age of just 25.2 years. [click to continue…]

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2016 AV-Adjusted Team Age: Offense

After each of of the last five 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, and to calculate age using each player’s precise age as of September 1 of the year in question.  Today, we will look at offenses; tomorrow, we will crunch these same numbers for team defenses. The table below shows the average AV-adjusted age of each offense, along with its total number of points of AV. Last year, the Rams, Jaguars, and Titans were the three youngest offenses. Each of those three are still in the top five this year, joined by the Bucs at #1 and the Seahawks at #4. [click to continue…]

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The Colts were 0.2 points per game better than average last year, as measured by the Simple Rating System (which takes the points scored and allowed in each game, and adjusts for opponent strength and home field advantage).

The Vikings were 0.9. points per game better than average in 2016, and hosted the Colts in week 15.  Given those facts, we would expect Minnesota to have won by 3.7 points.  Instead, Indianapolis upset the Vikings, 34-6, beating the expected line by 31.7 points.  That was the least-conforming game of 2016 (you can view the least-conforming games of 2015 here).

The table below shows all 512 regular season games from 2016, and how it differed from expectations. Here’s how to read the first line. The second-least conforming game was came in week 3, and we can use it to help guide us through the table below. The Eagles hosted the Steelers, and Philadelphia had an SRS rating of +3.7, while Pittsburgh had an SRS of +4.7. As a result, we would expect the Eagles to lose by 2 points. Instead, they won 34-3, exceeding expectations by 29 points.
[click to continue…]

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2016 Pythagenpat Records

If you’re not familiar with how to calculate Pythagenpat records, you can read this post.

But the short version is, this is a slight upgrade on using Pythagorean records, which I assume most of you are familiar with. The formula to calculate a team’s Pythagorean winning percentage is always some variation of:

(Points Scored^2) / (Points Scored ^2 + Points Allowed^2)

Here, instead of using 2 as the exponent, we use a dynamic exponent that changes based on how much scoring occurs in each team’s games. Here are the 2016 Pythagenpat records: [click to continue…]


Three years ago, I looked at the single-season leaders in percentage of team rushing yards. Then and now, the top two seasons belonged to Edgerrin James: he had 94% and 92% of the Colts rushing yards in his first two seasons in the league. There were only three other seasons where a running back had at least 90% of his team’s rushing yards: Emmitt Smith in 1991, Barry Sanders in 1994, and … Travis Henry in 2002. In that post, I calculated for each team the percentage of his team rushing yards gained by that team’s top rusher. Then I calculated the league average percentage gained by each team’s top rusher, and plotted how that varied over time. This was intended to measure how running back back committee centric the league was in each year.

For a less rigorous method to measure RBBC-ness, you can see this post, which looked at games with more than 15 carries.

Both methods show RBBC being heavy in the ’70s, and the stud RB era peaking about 10 years ago.  But if you want to measure rushing concentration, a better method is probably to use the formula described yesterday. So for each team, I calculated the percentage of team rushing yards gained by every player on the team, squared that result, and then summed those numbers for each player on the team. You can read yesterday’s post for more info on the methodology, but here were the results for 2016: [click to continue…]


Tyreek Hill was noticeably absent from yesterday’s list of yards from scrimmage leaders. The main reason for that? Hill was a part-time player for the first seven weeks, failing to take the field on even half of Kansas City’s offensive snaps in even a single game.  By the end of the year, he was a more regular part of the offense, although he never participated in 70% or more of the Chiefs offensive plays in any regular season game (and in the playoff loss to Pittsburgh, he was present for 69% of Kansas City’s offensive snaps). The graph below shows the percentage of offensive snaps he was on the field each week of the 2016 regular season:

[click to continue…]


Doug Drinen wrote this article 11 years ago, and it serves as a good reminder to always look at offensive numbers in the context of a player’s team. Yesterday, I looked at tackle leaders as a percentage of team tackles.  Today we will do the same thing with yards from scrimmage.

Arizona running back David Johnson led the NFL in yards from scrimmage last year with 2,118 yards. The Cardinals as a team gained 6,157 yards of offense (before deducting for sack yards lost), which means Johnson gained 34.4% of his team’s total output. That also led the league. However, Steelers RB Le’Veon Bell missed three games due to suspension and sat out a meaningless week 17 game.  Bell averaged 157 yards per game last year, the third-most in NFL history. He was responsible for 30.7% of the Steelers total yards from scrimmage last year, but on a pro-rated basis (i.e., multiplying that by 16/12), that jumps to an insane (although not historically extraordinary) 40.9%.

That’s the column the table is sorted by below. Here’s how to read Bell’s line. He gained 1,884 yards for Pittsburgh, while the Steelers as a team had 6,137 total yards. Bell therefore was responsible for 30.7% of Pittsburgh’s yards, but he only played in 12 games. On a pro-rated basis, he ranks first at 40.9%. The table below shows the top 75 leaders in this metric, minimum 6 games played: [click to continue…]


Positive Air Yards per Attempt: 2017 Update

Adam Steele is back for another guest post. You can view all of Adam’s posts here. As always, we thank him for contributing.

Positive Yards Per Attempt: 2017 Update

If I could only share one thing from my time doing football analytics, it would be the following principle: Positive plays carry more weight than negative plays in determining the winner of a football game. I’ve already written a couple of articles on this subject and hope to further the cause with this update.


For those of you who don’t feel like reading the previous two posts, I’ll give you the basic gist. Since passing has a far greater impact on winning than running, I’ve focused my research on quarterbacks, but the principle applies to the entire offense (defense, not so sure). Despite everyone constantly harping on turnover avoidance, a potent passing offense is usually able to overcome giveaways. Conversely, avoiding turnovers is normally not enough to overcome a weak passing game. Furthermore, turnovers are highly random and situation dependent, so it follows that turnovers are a very poor method of gauging quarterback performance. Even though sacks are largely the quarterback’s fault, they are also very context dependent and only contribute a small amount in determining game outcomes. More importantly, the majority of signal callers trade sacks for interceptions or vice versa, so it’s no really fair to include one but not the other. [click to continue…]


The Jay Schroeder Index

Yesterday, I looked at the quarterbacks who were the biggest checkdown artists: i.e., which players had the best completion percentages and lowest yards per completion averages. I measured this by calculating how many standard deviations above/below average each quarterback was in those two categories in each year.

Today, the reverse. And the big winner is rookie Terry Bradshaw. We all know Bradshaw stunk as a rookie. He had a whopping 11.0% interception rate, which was horrible even for 1970. In fact, he has the second most attempts in history by a player with an 11% or worse interception rate. And since Bradshaw also ranked dead last in completion percentage, he ranked 2nd to last in ANY/A that year.

Of course, you might wonder: how could someone with the worst completion percentage and by far the worst interception rate not rank last (by a mile) in ANY/A? Well, it’s because Bradshaw ranked 2nd in the NFL in yards per completion as a rookie. He was your ultimate boom/bust passer, finishing 2.75 standard deviations below average in completion percentage and 2.18 standard deviations above average in yards per completion.

The top of the list features a bunch of interesting names, but I’m calling this the Jay Schroeder Index for a reason.  Schroeder only had 8 seasons where he threw at least 200 passes, but he makes the top 200 in 6 of those 8 seasons!  Schroeder made the list in ’86, ’87, and ’88 (despite moving from the Redskins to the Raiders this year), and then in ’90, ’91, and ’92.  He only missed the list in 1989 during this run, and that’s because he threw just 194 passes.  But in 1989, of the 34 quarterbacks with at least 150 pass attempts, Schroeder had the lowest completion percentage (46.9%) and by far the highest yards per completion average (17.0, the best of his career).  In other words, Schroeder had a top-200 season in 6 out of 7 straight years, with the lone exception being perhaps his most Schroeder-esque season! Of course, Schroeder’s love of the deep ball isn’t new to readers of this site.

The table below shows the top 200 seasons based on the Schroeder Index, using the same formula as yesterday: [click to continue…]


The most efficient runner in NFL history? That depends.

Jamaal Charles is now a Denver Bronco, making him the second superstar running back in two weeks to join a new team at the tail end of his career. In his prime, Charles was a very good receiver and a player that could be the centerpiece of an offense. However, he will likely be remembered for a singular skill: rushing efficiency.

Charles has a career YPC average of 5.45, easily the best in history among running backs in the NFL. That number is at least a little misleading. While rushing efficiency has not soared the way passing efficiency has, we are currently in a high-YPC environment. Two years ago, I calculated era-adjusted yards per carry: at the time, Charles was at 5.49, while the league average was 4.21. For reference, the league average during the careers of Jim Brown, Gale Sayers, and Barry Sanders was 4.08, 3.95, and 3.93, respectively.

I am not a big fan of yards per carry as a statistic, but hey, it’s still interesting trivia. It’s a little silly and mostly an academic exercise, but let’s pretend that we replaced every Charles rush attempt with a league average rush attempt. How much worse off would Kansas City have been? Well, a whole lot. Let’s use his 2010 season as an example. He had 230 carries for 1,467 yards, producing an incredible 6.38 YPC average. The league average that season was 4.21, meaning he was 2.17 YPC above-average. Given his 230 carries, we would have expected him to rush for just 968 yards, meaning he produced 499 rushing yards above average. And for his career? Charles is at +1657. [click to continue…]


Peterson with a rare cameo by a good quarterback.

After a ten-year career with the Vikings, Adrian Peterson is now headed to New Orleans where he will get to play with Drew Brees.  It will be the second time Peterson has played with a Hall of Fame quarterback, after Brett Favre’s stint with the team beginning in 2009.

In ’09, the Vikings had a Relative ANY/A of +2.05, easily the best passing game the franchise has produced in the last decade.  In fact, the only other time in the last ten years that Minnesota had an above-average ANY/A was last year, when Peterson rushed for just 72 yards in three games.

Most of his time in Minnesota, though, the team’s passing attack has been below-average — or outright bad.  For example, in 2012, Peterson rushed for 2,097 yards.  That represented 17.9% of his career total, and it came when the Vikings had a Relative ANY/A of -0.94.  Overall Peterson has a weighted average RANY/A — i.e., the Vikings RANY/A in each season of Peterson’s career, weighted by the number of rushing yards Peterson had — for his career of -0.52.  Take a look. [click to continue…]

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