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Before you can get good at projecting fantasy points, you need to understand how fantasy points are scored.  And there’s probably no better place to start than in the passing game.

I used the following scoring system to determine passing fantasy points: 1 point per 25 yards passing (this is gross passing, so if you look at team passing data, you need to add back in sack yards), 4 points per touchdown pass, and -1 point per interception.  That’s it.

The average team in 2015 scored 16.1 fantasy points per game; to make life a bit more intuitive, I am going to convert fantasy point numbers into a plus/minus average number. So the Patriots passing attack, which scored 329.5 fantasy points in 16 games, and averaged 20.6 FP/G, gets credited as +4.5. That was the best average in football. On defense, the Patriots were slightly better than average, at +0.3 points per game (here, positive is good for defense; if you forget, just check the Saints line). Using New Orleans as an example, the Saints get a +4.2 offensive grade (ranked 2nd) and a -6.5 defensive grade (32nd). I put all 32 teams into the table below with their respective offensive and defensive grades and ranks: [click to continue…]


Footballguys.com – Why Subscribe?

Regular readers know that I’m one of the writers at Footballguys.com. If you are a hardcore fantasy footballer (or daily fantasy sports player), you probably already know that Footballguys.com is the single best source for fantasy football information. If you are a more casual fantasy football player, you’ll find that the tools available at Footballguys will make life much, much easier for you to win your league(s). Either way, I think a Footballguys Insider PRO subscription is a fantastic value for $32.95. Also fantastic values: the Footballguys Draft Dominator for mobile devices, which costs $4.99.

I don’t make extra money if more people sign up for Footballguys or buy an app, but I hope my readers subscribe because I think a subscription is a really good deal. If you play fantasy football and want to win your competitive league or save hours doing research for your local league, a Footballguys subscription is well worth it. For $32.95, you get: [click to continue…]

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An alternate uniform for the greatest tight end ever

An alternate uniform for the greatest tight end ever

Over the last three days, we’ve looked at the most dominant fantasy quarterbacks, running backs, and wide receivers. Today, we look at tight ends, using the methodology described over the three previous days.

I am using the following scoring system throughout this series: 1 point per 20 yards passing, 1 point per 10 yards rushing/receiving, 4 points per passing TD, 6 points per rushing/receiving TD, 0.5 points per reception.

You probably expect to see Rob Gronkowski’s 2011 season grade as the best fantasy season by any tight end. But, as it turns out, an AFC West tight end had one season that was ever so slightly more dominant.

You might think I’m talking about Tony Gonzalez, who has an unreal eleven seasons in the top 200. Or Kellen Winslow, who has eight top-200 seasons, half of which rank in the top 25. And if not one of those two, then surely Antonio Gates, who has nine top-200 seasons, including two in the top twenty. Or Shannon Sharpe, of course, who also has nine top-200 seasons, with six of those being in the top 70.

In fact, AFC West teams1 have 14 of the top 25 seasons by a tight end in fantasy history, and and 19 of the top 35 years. No division has dominated this position like the AFC West, but the best tight end season in fantasy history came from someone else: Oakland’s Todd Christensen. [click to continue…]

  1. And we don’t even need to include Seattle, which has 0 entries in the top 200 []



On Wednesday, we looked at the most dominant quarterbacks in fantasy history. Yesterday, we did the same for running backs. Today, we look at wide receivers, using the methodology described over the two previous days.

I am using the following scoring system throughout this series: 1 point per 20 yards passing, 1 point per 10 yards rushing/receiving, 4 points per passing TD, 6 points per rushing/receiving TD, 0.5 points per reception.

There are four seasons that have topped 200 points of VBD in wide receiver history: Elroy Hirsch, 1951; Wes Chandler, 1982; and Jerry Rice, 1987 and 1995. In ’95, Rice set the still-standing record with 351.5 fantasy points, courtesy of 122 catches, 1,848 receiving yards, and 15 touchdowns (he also rushed for 36 yards and a touchdown). Rice averaged 21.97 FP/G that year, while the baseline of WR32 was 9.15 FP/G. Therefore, Rice was 12.82 FP/G above the baseline for 16 games, which comes out to 205.1 points of VBD. [click to continue…]


The fantasy GOAT

The fantasy GOAT

Yesterday, we looked at the most dominant quarterbacks in fantasy history. Today, the running backs, using the methodology described yesterday. Let’s look at the three best seasons in fantasy history, since all shed light on the formula here. Those three are LaDainian Tomlinson, 2006, which is easy to argue as the best year ever as Tomlinson shattered the record for fantasy points scored. But O.J. Simpson in 1975 (not ’73) was also dominant, and did so in a 14-game season and when the baseline was lower. The darkhorse candidate is Priest Holmes, 2002, who put up insane numbers but missed two games due to injury.

I am using the following scoring system throughout this series: 1 point per 20 yards passing, 1 point per 10 yards rushing/receiving, 4 points per passing TD, 6 points per rushing/receiving TD, 0.5 points per reception.

In 2006, Tomlinson rushed for 1,815 yards with 28 TDs, caught 56 passes for 508 yards and 3 touchdowns, and even threw for 20 yards and two touchdowns. He totaled a still mind-boggling 455.3 fantasy points. On a per game basis, Tomlinson averaged 28.46 FP/G, while the baseline — which for these purposes is RB241 — was at 10.75 FP/G. Therefore, Tomlinson averaged 17.71 FP/G over the baseline, and he did it for 16 games, giving him a VBD of 283.3 fantasy points (17.71 x 16). [click to continue…]

  1. Baselines used in this series: From 1968 to 2014, RB24. In ’66 and ’67, RB20, and from ’61 to ’65, RB16. In the 1960 AFL, the baseline is RB6, while it is RB8 in the NFL. From 1950 to 1959, the baseline used is RB8. []

What was the most dominant fantasy season of all time? You might think Peyton Manning 2013, but let me throw out another candidate: Steve Young, 1998.

I am using the following scoring system throughout this series: 1 point per 20 yards passing, 1 point per 10 yards rushing/receiving, 4 points per passing TD, 6 points per rushing/receiving TD, 0.5 points per reception.

In 2013, Manning threw for 5,477 yards and 55 TDs with just 10 interceptions, while rushing for -31 yards but with one TD. That comes out to 486.75 fantasy points. In 1998, Young threw for 4,170 yards with 36 TDs and 12 INTs, but also ran for 454 yards and 6 TDs. That is equal to 421.90 fantasy points. So, advantage Manning.

But we measure fantasy dominance “not by the number of points he scores[, but] by how much he outscores his peers at his particular position.” Those are the words of Joe Bryant in his famous VBD article, and I’ll make an appendix to that for historical purposes: the key is how much a player outscores his peers at his particular position in that particular year.

When calculating VBD scores, the standard is to use the 12th-ranked quarterback. In 2013, the 12th=-ranked QB scored 309.2 fantasy points, which means Manning outscored him by 177.55 fantasy points (or we could say that Manning produced 178 points of VBD). In 1998, the 12th-ranked quarterback scored just 235.6 fantasy points, which means Young finished with 186.3 points of VBD. So, advantage, Young.

But there’s another piece of the puzzle that tips the scales even more towards the 49ers quarterback. In 1998, Young missed one game. For fantasy purposes, it’s more valuable to have a quarterback produced X points in 15 games than it is for him to produce X points in 16 games, because you can play someone else during that 16th game. [click to continue…]


Prompted by Le’Veon Bell’s remarkable stretch towards the end of last season, I took a look at the greatest four-game stretches by a fantasy running back over at Footballguys.com:

In the Steelers 11th game of the year, LeVeon Bell rushed for 204 yards and a touchdown.  In his next game, he totaled 254 yards from scrimmage against the Saints and ran for another score.  In Pittsburgh’s 13th game of the season, Bell scored three times against the Bengals while gaining 235 yards from scrimmage.  Finally, against the Falcons, Bell totaled 119 yards and ran for two touchdowns.

Over that four-game stretch, Bell scored seven touchdowns, gained 830 yards from scrimmage, and caught 21 passes.  If we use a scoring system that provides 0.5 points per reception and the standard 1 point for 10 yards rushing/receiving and 6 points for touchdowns. That translates to 135.5 fantasy points over such period, which is obviously an insane amount of points.  But how insane?  Only six other running backs since 1960 have had greater four-game stretches.  Let’s go to the list.

You can read the full article here. Suffice it to say, Bell is in some pretty rare company.


Fantasy: New Extra Point Rule (FBG)

Over at Footballguys.com, I provided my thoughts on what the new PAT rule means for fantasy players.

What does that mean in practical terms? Instead of there being one missed extra point every 2-3 weeks, there will be about two missed extra points per week. For fantasy owners, that means you might wind up losing a point a couple of times during your regular season, but, of course, you are just as likely to benefit from your opponent missing out on that point, too. In general, kickers are often an afterthought in many fantasy leagues; this rule is not going to change that, although it will make the best kickers (and kickers who play in friendly conditions) imperceptibly more valuable than before.

You can read the full article here.


FanDuel Lineups – Week 12, Thursday Night

Daily fantasy football is pretty sweet, and I’ve become very active in it this year. I’ve only played on FanDuel (affiliate link, here), so my analysis will be limited strictly to that site.

At FanDuel, you start 1 QB, 2 RBs, 3 WRs, 1 TE, 1 K, and 1 defense, with a salary cap of $60,000. The scoring system is pretty standard, with 0.5 points per reception being the most notable feature to keep in mind. There are generally two that I play: 50/50s, or what people refer to as cash games, where you say, pay $25 to enter a tournament of 50 people, and the top 25 people win $45. The house gets roughly the same cut of ~10% in most games, so the 50/50 is the low-variance play.

The other option is to play in tournaments, which can range from large, to very large, to absurdly large. Anyway, enough minutia. I have limited my play to 50/50s this week, although I did enter one tournament lineup which I’ll explain at the end. [click to continue…]


FanDuel Lineups – Week 11, Thursday Night

Daily fantasy football is pretty sweet, and I’ve become very active in it this year. I’ve only played on FanDuel (affiliate link, here), so my analysis will be limited strictly to that site.

At FanDuel, you start 1 QB, 2 RBs, 3 WRs, 1 TE, 1 K, and 1 defense, with a salary cap of $60,000. The scoring system is pretty standard, with 0.5 points per reception being the most notable feature to keep in mind. There are generally two that I play: 50/50s, or what people refer to as cash games, where you say, pay $25 to enter a tournament of 50 people, and the top 25 people win $45. The house gets roughly the same cut of ~10% in most games, so the 50/50 is the low-variance play.

The other option is to play in tournaments, which can range from large, to very large, to absurdly large. Anyway, enough minutia. I have limited my play to 50/50s this week, although I did enter one tournament lineup which I’ll explain at the end. [click to continue…]

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Fantasy: Running Back Workload Part II (FBG)

Last week, I began my analysis of how to measure workload for running backs. Today brings Part II, another attempt to analyze workload and fantasy production.

Last year, Joique Bell finished as the 15th best running back in fantasy football. Prior to 2013, Bell had just 82 career carries, all of which came in 2012.  Meanwhile, Marshawn Lynch finished as RB5, but he had 1,452 carries prior to the 2013 season. Both players were 27 years old last year, but they had drastically different career workloads.

One obvious issue that comes up when comparing high-workload to low-workload players is that there is often a large talent gap, and Bell and Lynch present that quite clearly. Bell was an undrafted free agent out of Division II Wayne State, while Lynch was a first round pick who played in the Pac-10. What I’ll try to do today is control for “player ability” by looking at the player’s VBD in the prior season. For example, Lynch had 125 points of VBD in 2012, while Bell had 0.

From 1988 to 2013, there were 77 running backs who had a top-24 finish during their age 27 season. One thing we can look to see is whether these players “benefited” from having low mileage up to that point in their careers. I performed a regression analysis using three inputs — Carries in the player’s age 26 year (for example, 315 for Lynch), his career carries as of the end of his age 26 season (1,452 for Lynch), and his VBD in his age 26 season (125).  My output was VBD in the player’s age 27 year.  Here was the best-fit formula:

You can read the full article here. And if you have thoughts on how else to study this issue, leave them in the comments.


Fantasy: Running Back Workload (FBG)

Over at Footballguys.com, I try to unravel the relationship between workload and age. Eight years ago, Doug wrote three articles on the topic; sadly, I’m not sure we’ve come very far since then. So I decided to at least begin the process of measuring how much of an impact “mileage” really has on running backs.

Conventional wisdom suggests that, all else being equal, running backs with “low mileage” are more likely to age gracefully than running backs who have accumulated a significant number of carries.

This, unfortunately, is a very complicated issue to test. For example, new Giants running back Rashad Jennings is 29 years old, but he has just 387 career carries.  This makes Jennings a “young” 29, but is that better than being an “old” 28? The best way to test this question is to analyze running backs of similar quality as Jennings — but who had a lot of carries by the time they were 28 years old — and see how the rest of their careers unfolded.  The problem is that the list of running backs with a lot of carries through their age 28 season bear no resemblance to Jennings. The players with the most carries through age 28 are Emmitt Smith, Edgerrin James, Jerome Bettis, Barry Sanders, LaDainian Tomlinson, Curtis Martin, and Walter Payton, which basically serves as a who’s who of running backs who are not comparable to Rashad Jennings.

Generally speaking, the best running backs get the most carries: did you know that Jim Brown is the only player to lead the NFL in carries more than 4 times? He did it six times in his nine-year career. Along the same line of thinking, the running backs with the most carries are generally among the best running backs.  Running backs who haven’t had a lot of carries through age 28 generally either aren’t very good or have suffered multiple injuries, which makes it tough to find players who feel like true comparables to a player like Jennings.

One could argue that running back workload and running back quality are so inextricably tied that it’s impossible to accurately measure whether age or workload is more important.  But today, I want to take a step back from examining the specifics of a player like Jennings and look at the big picture.  There are some examples that appear to support the “running back mileage” theory.  Shaun Alexander had a significant number of carries through age 28, and was excellent at age 28; the fact that he then declined so significantly, so quickly, could be a sign that workload really mattered. After all, few players suffer such sharp declines when turning 29. But that’s just one data point.  What if we can bring in many more?

You can read the full article here.


Over at Footballguys.com, I looked at which running backs have produced the most extreme fantasy splits in wins and losses.

With few exceptions, running backs generally score more fantasy points in wins than in losses.  For example, Adrian Peterson has averaged 22.2 FP/G over the last four years in wins, and 14.8 FP/G in losses, in a 0.5 PPR scoring system.  Those numbers rank Peterson in the top four in both categories, but obviously he’s been much more valuable in wins.

Some players, however, have particularly extreme splits. As Jason Lisk points out, Alfred Morris is one of those players.  Since Morris isn’t much of a receiver, he gets his value from carries and touchdowns, and both of those tend to be higher in wins. Over the past two seasons, Morris has averaged 17.1 FP/G in wins and 11.1 FP/G in losses. Marshawn Lynch is another player who is more valuable in wins: fortunately for him, those are more prevalent in Washington state than Washington, D.C. Since 2010, Lynch has averaged 17.3 FP/G in wins and 9.7 FP/G in losses.

So which running backs are most impacted by their team’s fortunes? I looked at the top 50 running backs in Footballguys.com rankings, and then excluded rookies and others players with small sample sizes.  I was left with 37 running backs, and I calculated their FP/G (using 0.5 PPR) in wins and losses since 2010.  Here’s how to read the table below. No running back fared so much better in wins relative to losses as Doug Martin.  The Tampa Bay back has played in seven wins and averaged 24.5 FP/G in those games, the highest average among the 37 running backs in this study.  Martin has played in 15 losses, and averaged just 12.1 FP/G in those games, the 10th best ranking. That’s a difference of 12.4 (24.5 – 12.1) FP/G.

You can read the full article here.


For the eleventh straight years, I’ve written an Quarterback By Committee article for Footballguys.com. Here’s a quick peak at this year’s article:

The general rule for QBBC fans is that the first six rounds of your draft should be used to assemble a wealth of talent at running back, wide receiver, and, if the draft unfolds in such a way, tight end. By going the QBBC route, you can save those high picks in your draft and still get solid fantasy production by grabbing two QBs who face bad defenses nearly every week of the year. That’s what the QBBC system is all about.

Of course, in some leagues, QB10 can now be had as late as the seventh round, and your fifth-ranked quarterback could still be available that late. One could argue that the best strategy is 2014 is to wait until the first ten quarterbacks are off the board and then draft a couple of quarterbacks at a nice discount. Colin Kaepernick, Tony Romo, and Russell Wilson have ADPs of QB11, QB12, and QB13, and all have high upside for 2014. That’s one option, but another option is to wait even longer and implement a quarterback-by-committee strategy.

The first key, of course, is to rank the defenses. I always start by adjusting last season’s data on defenses for strength of schedule. I started with the adjusted FP rankings for each defense listed in the Rearview QB article. Then, I made some adjustments to the defenses based on their efficiency numbers from 2013 and what’s happened since the end of last season. The table below lists my rating for defenses for fantasy quarterbacks, listed from the toughest (the Seahawks) to the easiest (Dallas).  Quarterbacks facing Seattle should expect to produce about five fantasy points below average, while passers facing the Cowboys will be projected to score three more points than average.

You can check out the full article here, which includes rankings of each defense and each quarterback’s strength of schedule.


Fantasy Football: Quarterback Rearview FP/G (FBG)

Every year, I adjust quarterback statistics — both fantasy and traditional — for strength of schedule. Today, a look at my article at Footballguys.com where I adjust the 2013 numbers for each quarterback for the quality of the opposing defenses. On Monday, I’ll be doing the same for quarterbacks using Adjusted Net Yards per Attempt.

For the ninth straight season, I’m advising fantasy football owners about a good starting point for their quarterback projections/rankings. My Rearview QB article analyzes the production of every quarterback from the prior season after adjusting his performance for partial games played and strength of schedule. If you’re a first time reader, here’s my argument in a nutshell: using last year’s regular end-of-year data is the lazy man’s method. When analyzing a quarterback, many look at a passer’s total fantasy points or fantasy points per game average from the prior season and then tweak the numbers based on off-season changes and personal preferences. But a more accurate starting point for your projections is a normalized version of last year’s stats.

The first adjustment is to use adjusted games (and not total games), which provide a more precise picture of how often the quarterback played. Second, you should adjust for strength of schedule, because a quarterback who faced a really hard schedule should get a boost relative to those who played easy opponents most weeks.

To be clear, this should be merely the starting point for your quarterback projections. If you think a particular quarterback carries significant injury risk, or is going to face a hard schedule again, feel free to downgrade him after making these adjustments. (And it should go without saying that if you think a quarterback will improve or decline – or, in the case of Colin Kaepernick or Cam Newton his supporting case will improve or decline – you must factor that in as well.) But those are all subjective questions that everyone answers differently; this analysis is meant to be objective. The point isn’t to ignore whether a quarterback is injury prone or projects to have a really hard or easy schedule in 2014; the point is to delay that analysis.

First we see how the player performed on the field last year, controlling for strength of schedule and missed time; then you factor in whatever variables you like when projecting the 2014 season. The important thing to consider is that ignoring partial games and strength of schedule is a surefire way to misjudge a player’s actual ability level. There’s a big difference between a quarterback who produced 300 fantasy points against an easy schedule while playing every game than a quarterback with 300 FPs against the league’s toughest schedule while missing 3.6 games. Here’s another way to consider the same idea: Jay Cutler ranked 25th in fantasy points in 2013, but the quarterback position for the Bears (i.e., Cutler and Josh McCown) ranked as the 4th highest team QB last year.

You can read the full article here.

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Last year, I provided a starting point for my running back projections. The idea is pretty simple: some fantasy statistics are much more repeatable, or sticky, than others. Over at Footballguys.com, I used the following formula to help isolate those factors:

1) Rushing Yards (R^2 = 0.47). The best-fit formula to predict rushing yards is:

-731 + 3.73 * Rush Attempts + 180 * Yards/Rush

2) Receptions (R^2 = 0.42). The best-fit formula to predict receptions is:

11.1 + 0.39 * Receptions + 0.032 * Receiving Yards

3) Receiving Yards (R^2 = 0.38). The best-fit formula to predict receiving yards is:

83.7 + 1.65 * Receptions + 0.46 * Receiving Yards

4) Rushing Touchdowns (R^2 = 0.29). The best-fit formula to predict rushing touchdowns is:

0.1 + 0.0037 * Rushing Yards + 0.35 * Rushing Touchdowns

5) Receiving Touchdowns (R^2 = 0.23). The best-fit formula to predict receiving touchdowns is:

0.1 + 0.0022 * Receiving Yards + 0.25 * Receiving Touchdowns

Using these formulas, we can come up with a good starting point for your 2014 running back projections.

You can read the full article here.


Green is poised for another monster year

Green is poised for another monster year.

Last year, at Footballguys.com, I looked at the best starting point for wide receiver projections. Well, I’ve re-run the numbers and come up with the best starting point for wide receiver projections in 2014.

The general philosophy is that receiving yards can be re-written using the following formula:

Receiving yards = (Receiving Yards/Target) x (Targets/Team_Pass_Att) x Team_Pass_Att.

Since each of those variables regress to the mean in different ways, we can get a more accurate projection of future receiving yards by projecting each of those three variables than by simply looking at past receiving yards. For example, here are the best fit formulas for each of those metrics:

Future Pass Attempts = 36 + (450 x Pass_Attempts/Play) + (0.255 x Offensive Plays)

Future Percentage of Targets = 6.2% + 71.3% x Past Percentage of Targets

Future Yards/Target = 5.5 + 0.29 x Past Yards/Targets

If you take a look at the three coefficients, the number of offensive plays run from year to year and the yards per target averages are not very sticky; both have coefficients of less than 0.3, which indicates a significant amount of regression to the mean. Meanwhile, percentage of targets is much, much sticker, at 71%.1

As a result, this regression really likes players like A.J. Green (5th in receiving yards in 2013, projected to be 1st in 2014), Andre Johnson (7th, 2nd) and Vincent Jackson (14th, 6th). To find out who else this metric likes and dislikes, and for a more thorough analysis, you can read the full article here.

  1. Pass attempts per play can’t be analyzed the same way, at least using the formulas presented here, but it does look as though the pass-heaviness of an offense is moderately sticky, too. And that would be even more true if we accounted for game scripts, I suppose. []

Don't worry, this will all make sense by the end. I think.

Don't worry, this picture's presence will make sense by the end. I think.

Two years ago, I wrote this post on running back aging curves. One conclusion from my research was that age 26 was the peak age for running backs, which was immediately followed by a steady decline phase until retirement. In that study, I only wanted to look at very good-to-excellent running backs in the modern era; as a result, I was forced to limit myself to just 36 players. I’ve been meaning to update that post, but wasn’t quite sure what methodology to use.

Last year, Neil wrote a very interesting post on quarterback aging curves. In it, Neil computed the year-to-year differences in Relative ANY/A at every age. While reviewing that post, a lightbulb went off. We can greatly increase the sample size if we only look at running backs from year-to-year, and not just the best running backs on the career level.

There are 723 running backs since 1970 who had at least 150 carries in consecutive seasons and who were between 21 and 32 in the first of those two seasons. For each running back pair of seasons, I calculated how many rushing yards the player gained in Year N and many yards he gained in Year N+1. Take a look:

[click to continue…]


Just above these words, it says “posted by Chase.” And it was literally posted by Chase, but the words below the line belong to Steve Buzzard, who has agreed to write this guest post for us. And I thank him for it. Steve is a lifelong Colts fan and long time fantasy football aficionado. He spends most of his free time applying advanced statistical techniques to football to better understand the game he loves and improve his prediction models.

The way to win fantasy football games is to have players that score a lot of points.  Players tend to score more points when they get more touches.  One of the most important factors in determining how many touches each player is going to have is to determine the Game Script ahead of time.  As we all know positive game scripts result in more passing attempts and negative Game Scripts result in more rushing attempts.  But I am going to try to project the pass ratio using two key stats, Pass Identity rating and the Vegas spreads. We can use these projected pass ratios to build our own projections or at least look for outliers and figure out how to adjust players from their year to date averages.

Regular readers know what Pass Identity means. For newer readers, you can read here to see how Pass Identities are calculated.  But the quick summary is that Pass Identity grades allow us to predict the pass ratio of any game where the point spread is zero. This is because Pass Identity tries to eliminate the Game Script from the pass ratios.  For example since the Bears/Cowboys game is a pick’em this week, we can predict the pass ratio of the Bears by using the following formula.  League average pass ratio + (A + B) *C, where

    (A) = number of standard deviations above/below average the Bears are in Game Script (-0.49);


    (B) = number of standard deviations above/below average the Bears are in Pass Ratio (+0.53); and

(C) = the standard deviation among the thirty-two teams with respect to Pass Ratio (5.3%)

Of course, the product of (A) and (B) is the Pass Identity grade for each team; once we determine that, we multiply that number by the standard deviation of the pass ratios of all teams to get us a prediction for the pass ratio in a game with a Game Script of 0.0. Since the Bears have a Pass Identity of basically 100, the projected Pass Ratio for Chicago against Dallas is 58.9%.

We can then compare this projection to Chicago’s year-to-date pass ratio of 61.5% and predict that all else equal Jay Cutler and the passing game should score about 4%1 less this week than their average week where as Matt Forte and the run game would score about 4% more.

[click to continue…]

  1. Since 58.9% is 96% of 61.5%. []

Trent Richardson and 400 carries

Richardson powers through for three yards

Richardson powers through for three yards.

Trent Richardson has been a frequent topic of discussion at Football Perspective. In about 14 months, I’ve written the following articles:

  • How often does the first running back selected in the draft become the best running back from his class? The field is always a better bet than one player: Only about 40% of the highest-drafted backs led their class in rushing yards as a rookie, with that number dropping to about 33% on a career basis. On the other hand, that’s better than the production of the first-drafted wide receiver.
  • In 2012, the field won, as both Doug Martin and Alfred Morris rushed for more yards than Richardson. I then tried to project the number of yards for all three players for 2013 based on their draft status and rookie production; as it turns out, draft status remained extremely important, and Richardson projected to average the most yards per game in year two out of that group (a projection that doesn’t look very good right now).
  • In July, I continued to voice my disdain for the use of yards per carry as the main statistic for running backs, when I argued that Richardson’s 3.6 average last year was not important. More specifically, I said if you loved Richardson as a prospect, his 3.6 YPC average in 2012 was not a reason to downgrade him (of course, if you didn’t like Richardson, that’s a different story). Richardson still received a huge percentage of Cleveland carries and had a strong success rate, and I argued that his low YPC was simply a function of a lack of big plays. For a more in-depth breakdown of his rookie season, Brendan Leister compiled a good film-room breakdown of some of Richardson’s mistakes in 2012. Leister noted that Richardson had some mental mistakes, which isn’t atypical of a rookie, and still fawned over the former Alabama star’s physical potential.
  • After the trade to Indianapolis, I wrote that Richardson’s ability as a pass blocker was tough to analyze, and advised you to view some of the numbers thrown around in support of Richardson with skepticism. Believe it or not, I still have thoughts on that trade that I just haven’t gotten around to finishing, so look for my hot take on the Richardson deal to be published in say, March.

In 75 carries with the Colts, Richardson is averaging just 3.0 yards per carry. Even though I find yards per carry overrated, there is a certain baseline level of production needed for every running back, and 3.0 falls well short of that number. For his career, Richardson now has 1,283 yards on 373 yards, a 3.44 YPC average. He’ll reach 400 career carries in a couple of weeks, so I thought it might be interesting to look at the YPC averages of all running backs after their first 400 carries.

We can’t measure that exactly through game logs, but what we can do is calculate the career YPC average of each running back after the game in which they hit 400 career carries. The table below shows that number for all running backs who entered the league in 1960 or later and is current through 2012. Let’s start with the top 50 running backs:
[click to continue…]


This guy's 1982 Chargers sure come up a lot when we do lists like these.

This guy's 1982 Chargers sure come up a lot when we do lists like these.

More than a decade ago (on a side note: how is that possible?), Doug wrote a series of player comments highlighting specific topics as they related to the upcoming fantasy football season. I recommend that you read all of them, if for no other reason than the fact you should make it a policy to read everything Doug Drinen ever wrote about football, but today we’re going to focus on the Isaac Bruce comment, which asked/answered the question:

Is this Ram team the biggest fantasy juggernaut of all time?

“This Ram team,” of course, being the 1999, 2000, & 2001 Greatest Show on Turf St. Louis Rams. At the time, Doug determined that those Rams were not, in fact, the best real-life fantasy team ever assembled, by adding up the collective VBD for the entire roster. They ranked tenth since 1970; the top 10 were:

1. 1. 1975 Buffalo Bills – 550 Simpson (281) Ferguson (98) Braxton (83) Chandler (44) Hill (42)

2. 1982 San Diego Chargers – 542 Chandler (190) Fouts (126) Winslow (121) Muncie (92) Brooks (10) Joiner (1)

3. 1994 San Francisco 49ers – 514 Young (208) Rice (140) Watters (98) Jones (67)

4. 1995 Detroit Lions – 478 Mitchell (136) Moore (132) Sanders (121) Perriman (87)

5. 1984 Miami Dolphins – 470 Marino (243) Clayton (145) Duper (76) Nathan (6)

6. 1998 San Francisco 49ers – 467 Young (200) Hearst (137) Owens (81) Rice (46) Stokes (1)

7. 1986 Miami Dolphins – 456 Marino (210) Duper (94) Clayton (76) Hampton (61) Hardy (13)

8. 2000 Minnesota Vikings – 452 Culpepper (170) Moss (123) Smith (87) Carter (70)

9. 1991 Buffalo Bills – 449 Thomas (157) Kelly (143) Reed (80) Lofton (51) McKeller (17)

10. 1999 St. Louis Rams – 435 Faulk (184) Warner (179) Bruce (71)

As an extension of Chase’s recent post on the The Best Skill Position Groups Ever, we thought it might be useful to update Doug’s study in a weekend data-dump post. I modified the methodology a bit — instead of adding up VBD for the entire roster, for each team-season I isolated the team’s leading QB and top 5 non-QBs by fantasy points (using the same point system I employed when ranking the Biggest Fluke Fantasy Seasons Ever). I then added up the total VBD of just those players, to better treat each roster like it was a “real” fantasy team.

Anyway, here are the results. Remember as well that VBD is scaled up to a 16-game season, so as not to short-change dominant fantasy groups from strike-shortened seasons (:cough:1982 Chargers:cough:).
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Yesterday, I set up a method for ranking the flukiest fantasy football seasons since the NFL-AFL merger, finding players who had elite fantasy seasons that were completely out of step with the rest of their careers. I highlighted fluke years #21-30, so here’s a recap of the rankings thus far:

30. Lorenzo White, 1992
29. Dwight Clark, 1982
28. Willie Parker, 2006
27. Lynn Dickey, 1983
26. Robert Brooks, 1995
25. Ricky Williams, 2002
24. Jamal Lewis, 2003
23. Mark Brunell, 1996
22. Vinny Testaverde, 1996
21. Garrison Hearst, 1998

Now, let’s get to…

The Top Twenty

20. RB Natrone Means, 1994

Best Season
2nd-Best Season

Big, bruising Natrone Means burst onto the scene in 1994 as a newly-minted starter for the Chargers’ eventual Super Bowl team, gaining 1,350 yards on the ground with 12 TDs. In the pantheon of massive backs, he was supposed to be the AFC’s answer to the Rams’ Jerome Bettis, but Means was slowed by a groin injury the following year and never really stayed healthy enough to recapture his old form. The best he could do was to post a pair of 800-yard rushing campaigns for the Jaguars & Chargers in 1997 & ’98 before retiring after the ’99 season.

19. WR Braylon Edwards, 2007

Best Season
2nd-Best Season

The 3rd overall pick in the 2005 Draft out of Michigan, Edwards seemingly had a breakout 2007 season catching passes from fellow Pro Bowler Derek Anderson. But both dropped off significantly the next season, and Edwards was sent packing to the Jets in 2009. He did post 904 yards as a legit starting fantasy wideout in 2010, but he has just 380 receiving yards over the past 2 seasons, and it’s not clear he’ll ever live up to those eye-popping 2007 numbers again.
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I prefer cooking in a Garrison  Hearst replica jersey

I prefer cooking in a Garrison Hearst replica jersey.

There’s nothing like a truly great fluke fantasy season. Because they can help carry you to a league championship (and therefore eternal bragging rights — flags fly forever, after all), a random player who unexpectedly has a great season will often have a special place in the heart of every winning owner. And even if you only use their jerseys as makeshift aprons to cook in, fluke fantasy greats are a part of the fabric of football fandom. That’s why this post is a tribute to the greatest, most bizarre, fluke fantasy seasons of all time (or at least since the 1970 NFL-AFL merger).

First, a bit about the methodology. I’m going to use a very basic fantasy scoring system for the purposes of this post:

  • 1 point for every 20 passing yards
  • 1 point for every 10 rushing or receiving yards
  • 6 points for every rushing or receiving TD
  • 4 points for every passing TD
  • -2 points for every passing INT

I’m also measuring players based on Value Based Drafting (VBD) points rather than raw points. In a nutshell, VBD measures true fantasy value by comparing a player to replacement level, defined here as the number of fantasy points scored by the least valuable starter in your league. For the purposes of this exercise, I’m basing VBD on a 12-team league with a starting lineup of one QB, two RBs, 2.5 WRs, and 1 TE. That means we’re comparing a player at a given position to the #12-ranked QB, the #24 RB, the #30 WR, or the #12 TE in each season. If a player’s VBD is below the replacement threshold at his position, he simply gets a VBD of zero for the year.
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If you don’t play fantasy football, you probably have no idea what this title means. Of course, it’s 2013, so if you don’t play fantasy football, you’re now the oddball. “PPR” stands for points per reception. About half of all fantasy leagues do not give any points for receptions, while the other half includes some sort of PPR format. And while the value of every player is dependent on each league’s scoring system, few players see their value fluctuate between scoring systems quite like Wes Welker. Or, at least, that’s how it seems. Is there a way to measure this effect?

First, a review of Welker’s numbers since he joined the Patriots:

Games Receiving
Rk Player Year Age Draft Tm Lg G GS Rec Yds Y/R TD Y/G
1 Wes Welker 2012 31 NWE NFL 16 12 118 1354 11.47 6 84.6
2 Wes Welker 2011 30 NWE NFL 16 15 122 1569 12.86 9 98.1
3 Wes Welker 2010 29 NWE NFL 15 11 86 848 9.86 7 56.5
4 Wes Welker 2009 28 NWE NFL 14 13 123 1348 10.96 4 96.3
5 Wes Welker 2008 27 NWE NFL 16 14 111 1165 10.50 3 72.8
6 Wes Welker 2007 26 NWE NFL 16 13 112 1175 10.49 8 73.4

Welker doesn’t get many touchdowns, and while he has respectable yardage totals, he is only exceptional when it comes to piling up receptions. Welker has 672 receptions over the last six seasons, easily the most in the NFL (in fact, it’s the most ever over any six-year stretch). Brandon Marshall (592) and Reggie Wayne (578) are the only two players even within 100 catches of Welker. Over that same time frame, he ranks 4th in receiving yards, but only tied for 17th in receiving touchdowns.

Giselle approves of Welker's form

Giselle approves of Welker's form.

So how can we measure how much more valuable Welker is in PPR-leagues than non-PPR leagues? One way is to use VBD, which is a measure of how much value a player provided over the worst starter (or some other baseline). For example, Welker scored 173 fantasy points and ranked as WR12 in non-PPR leagues last season. If you are in a start-three wide receiver league, the worst starter would be WR36, who scored 111 fantasy points. That means Welker provided 62 points of VBD.
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For eleven straight years, I’ve written an article called “Defensive Team By Committee.” This year’s version is up at Footballguys.com (subscriber only).

Fantasy defenses are inconsistent from year to year, making it difficult to predict which defenses and special teams (D/STs) will excel. And, at least in theory, the teams available at the ends of your drafts should provide less rewards. So how do you get great production out of the position while saving your most important draft picks?

We spend countless hours analyzing team offenses, and relatively few thinking about team defenses. But an average defense against a bad offense will do just as well as a great defense against an average offense. The key to the DTBC system is to find two teams available late in your draft whose combined schedule features predominantly weak offenses. By starting your defense based on matchups, your D/ST will generally face a weak offense, meaning your D/ST position will score lots of fantasy points.

You can read my two picks, along with a ranking of all 496 combinations, here.

For you iPad users our there, I’ll also recommend the $4.99 Footballguys Fantasy Football Magazine Draft Kit, an awesome resource at a super cheap cost. That includes the Draft GM Kit, which you can separately order if (like me) you don’t have an iPad but do have an iPhone. Both products will also be available on Android very soon, if not already by the time you read this. You can receive all Footballguys updates by signing up on the Free Footballguys Daily E-mail list.


Fantasy Football: Expected VBD (FBG)

[Note: For the rest of the year, content over at Footballguys.com is subscriber-only.]

Over at Footballguys.com, I build upon Joe Bryant’s VBD and create the idea of Expected VBD. While VBD is a great way to understand the value of players, Expected VBD explains how we draft. This concept is why even though you may expect some kickers and fantasy defenses to perform well, you don’t take them early in the draft because they have low Expected VBDs. So what is Expected VBD?

Instead of drafting according to strict VBD, you should be drafting to something I’ll call Expected VBD, which is best defined by an example. Suppose Russell Wilson has three equally possible outcomes this year: he has a one-in-three chance of scoring 425 fantasy points, 325 fantasy points, and 225 fantasy points. Further, let’s assume that the baseline number of fantasy points at the quarterback position is 300 fantasy points.

We would project Wilson to score 325 points, which would be the weighted average of his possible outcomes. This means VBD would tell you that he is worth 25 points, because 325 is 25 points above the baseline. Expected VBD works like this: If Wilson scores 425 points, he’ll produce 125 points of VBD. If he scores only 325 points, he’ll be worth +25, and if he scores only 225 points, he’s going to have -125 points of VBD. In real life, players with negative VBD scores can be released or put on your bench. So if Wilson scores 225 points (probably due to injury), you’ll start another quarterback, roughly a quarterback who can give you baseline production.

So when Wilson scores 225 fantasy points, his VBD is 0, not -75. That means his Expected VBD would be (125+25+0)/3, or 50. Wilson’s VBD according to our projections may be only 25, but his Expected VBD is twice as large because Expected VBD does not provide an extra penalty for sub-baseline performances. Not surprisingly, different positions have different amounts of Expected VBD associated with them.

Below is the summary graph — it has quickly become one of my all-time favorite graphs — which shows the Expected VBD by each position according to Average Draft Position.


I go into much more detail in the full article.


In 2008, Larry Fitzgerald had a fantastic regular season capped off by a historically great postseason; in the Super Bowl, he set the record for receiving yards in a season, including playoff games, with 1,977 yards. Of course, 2008 was decades ago in today’s era of what have you done for me lately. The table below shows Fitzgerald’s stats over the past four seasons. The final two columns show the total number of receiving yards generated by all Cardinals players and Fitzgerald’s share of that number.

YearRecYdsYPRTDARI Rec YdsPerc

2009 was the last season of the Kurt Warner/Anquan Boldin Cardinals. The 97 receptions and 13 touchdowns look great, although hitting those marks and not gaining 1,100 receiving yards is very unusual. Fitzgerald was only responsible for 26% of the Cardinals receiving yards that season, although one could give him a pass since he was competing with another star receiver for targets.

Can Fitzgerald rebound in 2013?

Can Fitzgerald rebound in 2013?

In 2010, Derek Anderson, John Skelton, Max Hall, and Richard Bartel were the Cardinals quarterbacks: as a group, they averaged 5.8 yards per attempt on 561 passes. Arizona’s passing attack was bad, but without Boldin, Fitzgerald gained 34.8% of the team’s receiving yards. Steve Breaston chipped in with 718 receiving yards yards while a 22-year-old Andre Roberts was third with 307 yards. In other words, Fitzgerald performed pretty much how you would expect a superstar receiver to perform on a team with a bad quarterback and a mediocre supporting cast: his raw numbers were still very good (but not great) because he ate such a huge chunk of the pie. After the 2010 season, I even wondered if he could break any of Jerry Rice’s records (spoiler: he can’t).

In 2011, Skelton, Kevin Kolb and Bartel combined for 3,954 yards on 550 passes, a 7.2 yards per attempt average (Kolb was at 7.7 Y/A). That qualifies as a pretty respectable passing game and Fitzgerald appeared to have a monster year, gaining 35.7% of the Cardinals’ receiving yards (Early Doucet was second with 689 yards and Roberts was third with 586 yards). It’s always hard splicing out cause and effect, but my takeaway is that with a more competent passing game, Fitzgerald continued to get the lion’s share of the team’s production but unlike in 2010, this led to great and not just good numbers.
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Over at Footballguys.com, I look at a different method to project receiving yards.

The number of receiving yards a player produces is the result of a large number of variables. Some of them, like the receiver’s ability, are pretty consistent from year to year. But other factors are less reliable, or less “sticky” from year to year. I thought it would be informative to look at three key variables that impact the number of yards a wide receiver gains and measure how “sticky” they are from year to year. These three variables are:

  • The number of pass attempts by his team;
  • The percentage of his team’s passes that go to him; and
  • The receiver’s average gain on passes that go to him.

We can redefine receiving yards to equal the following equation:

Receiving yards = Receiving Yards/Target x Targets/Team_Pass_Att x Team_Pass_Att.

You’ll notice that Targets and Team Pass Attempts are in both the numerator and denominator of one of the fractions, and they will cancel each other out: that’s why this formula is equivalent to receiving yards.

By breaking out receiving yards into these three variables, we can then examine the stickiness of each one, which should help our Year N+1 projections. Below are the best-fit equations for each of those variables in Year N+1:

Future Pass Attempts = 36 + (450 x Pass_Attempts/Play) + (0.255 x Offensive Plays)

Future Percentage of Targets = 6.2% + 71.3% x Past Percentage of Targets

Future Yards/Target = 5.5 + 0.29 x Past Yards/Targets

I then used those three equations to come up with a starting point for receiving yards projections for 28 wide receivers. You can read the full article here.


Over at Footballguys.com, I explain my method of how to value a player that we know is going to a certain number of games. You can’t simply use the player’s projected number of fantasy points because that will underrate him. But if you go by his projected points per game average, he’ll be overrated. Using Rob Gronkowski as an example, I explained my method:

First, you need to determine the fantasy value of a perfectly healthy Gronkowski.  Prior to today’s news, David Dodds had projected Gronkowski to record 70 catches for 938 yards and 9 touchdowns… but in only 14 games.  This means Dodds had projected the Patriots star to average 10.6 FP/G in standard leagues, 15.6 FP/G in leagues that award one point per reception, and 18.1 FP/G in leagues like the FFPC that give tight ends 1.5 points per reception.

But those numbers aren’t useful in a vacuum: the proper way to value a player isn’t to look at the number of fantasy points he scores.  Instead, the concept of VBD tells us that a player’s fantasy value is a function of how many fantasy points he scores relative to the other players at his position.  I like to use a VBD baseline equal to that of a replacement player at the position, and “average backup” is a good proxy for that.  In a 12-team league that starts one tight end with no flex option, that would be TE18.  In standard leagues, TE18 on a points per game basis is Brandon Myers, the ex-Raiders tight end now with the Giants.  Footballguys projects Myers to average 5.4 FP/G in standard leagues and and 8.9 FP/G in PPR leagues.  In 1.5 PPR leagues, Martellus Bennett comes in at TE18 in our projections, with an average of 10.6 FP/G.

You can read the full article, which includes a neat table, here.


At Footballguys.com, I explain why fantasy football owners need to understand the concept of regression to the mean. Readers of this blog probably don’t need the long background, but you might enjoy some of the graphs at the end. For example, this is the distribution of yards per carry in Year N and yards per carry in Year N+1:

regression ypc

You can read the full article here.

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