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With the start of the NFL season just around the corner and draft season upon us, I thought I would look into what statistic best predicts the future performance of NFL running backs for Fantasy Football.

In the same way that Fantasy Baseball players use FIP to predict the future performance of a pitcher’s ERA, we want to find a statistic that is a better predictor of success than a running back’s Fantasy points scored from the previous season. Whatever the statistic is, it’s ability to be a better predictor of future performance than past performance will result from its ability to strip any noise that is inherent from past production.

By no means did I cover all statistics, so the author of this article is aware of how dogmatic the title of this piece is,  but I tried to cover as many metrics that were readily available through Pro Football Reference as possible.

Population and Methodology

The population of this study consists of all running backs that started a minimum of three games in a single season from 1989 to 2014. It’s necessary to set a minimum level of games started to weed out players that had no opportunity to perform to their true talent level.

In order to test which metric is the best predictor of future success for running backs, we need to look at a player’s previous season total for a particular metric and see how it correlates (r) with their Fantasy points scored for the following season (e.g. we would look at a player’s rushing touchdowns for 2013 and see how rushing touchdowns correlate to a player’s Fantasy points scored for 2014).

This approach gives us 1,229 pairs of seasons in which a running back started at least three games in each.


Previous Season StatisticCorrelation (r)
Fantasy Points (Minus TDs) per Game0.75
Fantasy Points (Minus TDs and Add Fumbles) per Game0.75
Fantasy Points per Game0.74
Fantasy Points (Minus TDs and Add Fumbles)0.73
Fantasy Points (Minus TDs)0.73
Fantasy Points (Add Fumbles)0.72
Fantasy Points (Add Fumbles)0.72
Fantasy Points0.72
Rushing Yards0.71
Rushing Attempts0.70
Rushing Touchdowns per Game0.61
Rushing Touchdowns0.61
Rushing Attempts per Game0.58
Receptions per Game0.45
Receiving Yards per Game0.44
Receiving Yards0.43
Yards per Carry0.35
Receiving Touchdowns0.18
Receiving Touchdowns per Game0.17

Most of the metrics that I tested should be self explanatory, but I’ll go over some of them now. This link provides a good explanation of how these numbers should be interpreted.

There is a common discourse in the fantasy community that “you shouldn’t go chasing touchdowns,” and this research suggests that that narrative is in fact true.

Best Predictor:

The best predictor of future success for running backs proves to be the previous season’s Fantasy points-per-game, with the points gained from touchdowns backed out.

Second Best Predictor:

Just behind that is a player’s fantasy points-per-game, minus points gained from touchdowns and adding points lost from fumbles.

When I started the project, this is the statistic that I assumed would be the best predictor of future performance, however this stat becomes difficult to test because Pro Football Reference only has data on fumbles-lost since 2012.

As a result, when Pro Football Reference lists a player’s Fantasy points scored for a previous season before 2012, they assume that half of a player’s fumbles were lost to the other team and adjust their Fantasy points from there.

In all reality a player may have fumbled five times and never lost the ball to the other team, but Pro Football Reference penalizes him for two-and-a-half fumbles when they calculate his fantasy points. This is actually a fair assumption, because we know that a team’s ability to recover a fumble is entirely random and not a skill, which lead me to want to test this stat in the first place (i.e. because the amount of points a player loses from fumbles is mostly random, I thought that if you added back in the points lost from fumbles, you could better predict Fantasy points scored for the following season).

Instead of fumbles lost to the opposing defense, we are left to test fumbles (that is, fumbles divided by two) in general when we look to weed out variables. Oddly enough we still get the second highest correlation of our group of statistics when we add the points lost from fumbles back into a player’s points per game, minus touchdowns.

Applying What We’ve Learned

PlayerFantasy PointsFantasy Points per GameFantasy Points (Minus TDs)Fantasy Points (Minus TDs) per GameDIFF Points per GameDIFF RK
Le'Veon Bell287.517.97221.513.8-4.132
DeMarco Murray292.118.26214.113.4-4.88-1
Arian Foster235.518.12157.512.1-6.00-1
Matt Forte244.615.29184.611.5-3.751
Marshawn Lynch265.316.58163.310.2-6.37-1
Justin Forsett202.912.68154.99.7-3.002
Eddie Lacy230.614.41152.69.5-4.87-1
LeSean McCoy171.410.71141.48.8-1.878
Andre Ellington131.510.96101.58.5-2.506
Jamaal Charles210.414.03126.48.4-5.60-3
Mark Ingram162.912.53108.98.4-4.15-2
Lamar Miller185.411.59131.48.2-3.38-1
Jeremy Hill183.911.49129.98.1-3.37-1
Giovani Bernard144.911.15102.97.9-3.23-1
Joique Bell166.211.08118.27.9-3.20-1
C.J. Anderson177.311.82117.37.8-4.00-6
Rashad Jennings108.59.8684.57.7-2.183
Alfred Morris170.910.68122.97.7-3.00-1
Fred Jackson122.68.76104.67.5-1.295
Jonathan Stewart1219.3197.07.5-1.852
Tre Mason119.39.9489.37.4-2.50-3
Frank Gore147.79.23117.77.4-1.871
Ryan Mathews57.99.6539.96.7-3.00-2
Jerick McKinnon67.36.1267.36.1-0.009
Branden Oliver109.37.8185.36.1-1.723
Matt Asiata148.29.8888.25.9-4.00-7
Chris Ivory134.48.492.45.8-2.63-2
Steven Jackson121.
Andre Williams127.17.9485.15.3-2.62-2
Shane Vereen113.87.1183.85.2-1.87-
Denard Robinson90.66.9766.65.1-1.85-
Terrance West101.77.2671.75.1-2.14-3
Doug Martin67.86.1655.85.1-1.09-1
Reggie Bush676.0955.05.0-1.091
Chris Johnson91.45.7179.45.0-0.752
Trent Richardson90.86.0572.84.9-1.20-
Darren McFadden84.65.2972.64.5-0.751
Bishop Sankey78.24.8966.24.1-0.751
DeAngelo Williams24.34.0524.34.1-2
Ben Tate67.
Toby Gerhart61.24.3749.23.5-0.86-1
Marcel Reece392.633.02.2-0.40-
Mike Tolbert17.12.1417.12.1-0.00-

The chart above shows what the 2014 scoring leaders at running back look like when we back out their touchdowns and judge their performance on a per game basis.

Obviously, players like Marshawn Lynch and DeMarco Murray—the league leaders in rushing touchdowns—are hurt quite a bit, but, because their total production wasn’t completely dependent on touchdowns (i.e. a large percent of the points they produced came from the yards they gained, and not just touchdowns), their overall rank doesn’t change much.

Players like Matt Asiata and C.J. Anderson are hurt the most, because an appreciable amount of their production came from end-zone celebrations.

(What follows was added to this article on August 27th to account for what some commenters noticed (i.e. that Fantasy points per game  minus touchdowns fails to account for players that were active in games but saw little involvement in the offense for that game))

However, when it comes to C.J. Anderson, the former statement is a half truth, which reveals a shortcoming of Fantasy points-per-game, minus touchdowns. We use games played as a way to adjust player performance to take into account differences in playing time between players, however just because a player played in a game, it doesn’t necessarily mean that a player was heavily involved in the game. For example, C.J. Anderson played in played in 15 games in 2014, but he didn’t see more than five carries in a game until mid-way through the season.

To account for this and have a better proxy for playing time, we can use total touches (rushes plus receptions) instead of games played when we adjust for playing time differences. The table below shows Fantasy points-per-touch, minus touchdown points for all running backs with 120 or more touches in 2014.

PlayerAgeTmFantasy Points per Touch (Minus Touchdowns)Touches
Le'Veon Bell22PIT0.59373
Shane Vereen25NWE0.57148
Justin Forsett29BAL0.56279
C.J. Anderson23DEN0.55213
Ahmad Bradshaw28IND0.54128
Eddie Lacy24GNB0.53288
Arian Foster28HOU0.53298
Jeremy Hill22CIN0.52249
Bobby Rainey27TAM0.52127
Lamar Miller23MIA0.52254
Marshawn Lynch28SEA0.52317
Jamaal Charles28KAN0.51246
Fred Jackson33BUF0.51207
Matt Forte29CHI0.50368
Giovani Bernard23CIN0.49211
Jonathan Stewart27CAR0.49200
Jerick McKinnon22MIN0.48140
DeMarco Murray26DAL0.48449
Joique Bell28DET0.46257
Tre Mason21STL0.46195
Ronnie Hillman23DEN0.45127
Chris Johnson29NYJ0.44179
Frank Gore31SFO0.44266
Alfred Morris26WAS0.44282
Branden Oliver23SDG0.44196
LeGarrette Blount282TM0.43135
Rashad Jennings29NYG0.43197
Chris Ivory26NYJ0.43216
Mark Ingram25NOR0.43255
Matt Asiata27MIN0.42208
Denard Robinson24JAX0.42158
Isaiah Crowell21CLE0.42157
LeSean McCoy26PHI0.42340
Andre Ellington25ARI0.41247
Steven Jackson31ATL0.41210
Toby Gerhart27JAX0.41121
Terrance West23CLE0.39182
Trent Richardson24IND0.39186
Bishop Sankey22TEN0.39170
Darren McFadden27OAK0.38191
Knile Davis23KAN0.38150
Doug Martin25TAM0.38147
Andre Williams22NYG0.36235
Alfred Blue23HOU0.35184
Ben Tate263TM0.32135

As we can see, if we adjust performance by the times a player touched the ball, and not the amount of games they played in, we get a much more accurate depiction of a players true talent (C.J. Anderson ranks fourth in the latter metric).

While we have learned that the best predictor of future performance for Fantasy running backs is fantasy points scored per game, minus touchdowns, we have also learned that this metric tells somewhat of a fib and that total touches is better than games played if we want to adjust for differences in playing time.

Photo Credit: Jeffrey Beall

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