How NFL Statistics Lead to Wins, Pt. 2: Quantifying Player Stats into Wins

(Photo by Elsa/Getty Images)

 
Fantasy football owners will recognize Pierre Thomas’s name at No. 7. Thomas had a touchdown in each game and over 100 total yards in all but one from Weeks 11 to 16. He averaged 17 touches for 113 total yards per game, with a total of nine touchdowns and one fumble during the stretch.

Adrian Peterson and his league-leading 1,760 rushing yards rank No. 30 and below average. Let’s go through each stat one-by-one to see why.

Yards per carry: Peterson had a 4.85 YPC, good for 1.31 wins. The average of the 49 backs with 100 attempts was 4.21, or 1.14 wins. Peterson is +0.17 wins so far.

Rushing touchdowns per carry: Peterson had 10 rushing touchdowns in 363 attempts; the league average, prorated to 363 attempts, was just over 12 touchdowns. But including the fact that the Vikings had less rushing touchdowns than the average, Peterson gained 0.24 wins over the average. He’s now at +0.41 wins.

Fumble rate: Peterson fumbled nine times in 384 attempts and receptions. In that many fumble chances, the league average back would have fumbled 4.1 times, half of Peterson’s total. Peterson’s minus-0.78 wins from his fumble rate means he was 0.42 wins less than the league average. He’s at minus-0.01 wins.

Receiving: Peterson averaged just 3.9 receiving yards per target, had no receiving touchdowns, and caught 54 percent of his targets. His receiving game earned him just 0.35 wins, or 0.27 wins below league average. All combined, Peterson was 0.28 wins below average in 2008.

DeAngelo Williams (worth $5.45 million more than his actual salary last year), Pierre Thomas ($4.80 million), and Maurice Jones-Drew ($4.74 million) were the three most underpaid running backs last year.

The three most overpaid were Michael Turner (whose production was worth $11.3 million less than he actually received), Marion Barber III ($8.90 million), and Steven Jackson ($8.04 million).

The standard deviation of the 49 running back’s wins above average is 0.78, while for quarterbacks it is 1.27. That suggests that running back production is more tightly packed than quarterbacks, and that there’s a steeper drop-off for quarterbacks than running backs.

 
WIDE RECEIVER

Wide receivers were explained in greater detail above. Here’s how the 59 wideouts with at least 40 catches rank.

 
According to their wins above average, the most underpaid receivers last year were Roddy White (paid $6.31 million less than what he actually “earned”), Greg Jennings ($4.98 million), and Vincent Jackson ($4.75 million).

Larry Fitzgerald (deserved $11.3 million less than his actual salary), Randy Moss ($9.33 million), and Terrell Owens ($8.81 million) were the three most overpaid.

Now, that isn’t to say those three were actually that bad. If you graph actual salaries against worth, you find that actual salary drops three times faster than worth. For instance, the fifth-highest salary was $11.82 million, but Larry Fitzgerald—who was No. 5 in WAA—was worth only $5.73 million. This is because deserved salary based on WAA is linear (in that you multiply WAA by a constant to get worth) and not exponential.

In addition, Fitzgerald is hurt by the fact that wins are found by adjusting for team pass attempts. If every wideout’s team had 516 attempts (the league average), Fitzgerald would have ranked No. 1 in wins above average, but would have been worth only $6.91 million because of linear calculation.

 
In Part III of this series, I’ll apply individual wins and worth to the team level to see which teams are the most cost-efficient and get the most production out of their payroll.

 
How did I come up with 34.5 points?

The simple answer: Take a team that both scores and allows 21 points per game. Using the Pythagorean formula—which estimates a team’s record based points scored and allowed—they’d be expected to win eight games no matter what exponent you use (2.37, 2.64, or a floating exponent based on total points per game).

Now, if you add 34.5 points to that team’s points scored, you get about 23.16 points scored and 21 points allowed per game. Run them through the Pythagorean formula, and you exactly nine wins.

(In the second scenario, the exponent I used was (total points scored and allowed per game)^0.25, which yields better results than any other exponent.)

The complex answer: The formula to find points per win is PPW = 2 x (Pts-PtsAll) x (Pts^x + PtsAll^x) ÷ (Pts^x — PtsAll^x), where x is the floating exponent as given above and points and points allowed are per game. That equation comes from David Smyth and Patriot.

I applied this equation to every team season since 1994, and the average points per win was 34.3; the median was 34. I stuck with 34.5 after performing the test above.

You're currently logged into Facebook

Do you want to share your Bleacher Report activity on Facebook?