Most Predictable Running Back Stats (2019 Update)

Jul 29, 2019
Most Predictable Running Back Stats (2019 Update)

This is the final installment of my series on which stats are the most predictable from year to year for each position.

More Predictable Stats: TE | QB | WR

This study will shed light on which commonly cited previous-year stats for running backs are reliable indicators of future performance—and which stats can be misleading.

This article has been updated to reflect data through 2018.

The Methodology

In order to keep this study somewhat controlled, only running backs from 2010 on who saw at least 100 touches and remained on the same team in consecutive years were considered. Many variables change from year to year in the NFL, and since a study like this can be inherently sensitive to outliers, eliminating something as drastic as a team change should remove some noise. One hundred touches is an arbitrary cutoff, but an average of 12 or more touches per game over half of a season should be sufficient enough of a sample to reflect a player's true performance level.

This methodology offers us a sample of 201 instances in which a running back met the volume threshold in consecutive seasons for the same team.

The One Type of Stat With the Strongest Correlation

The following table gives the correlations for 17 statistics that are commonly cited when trying to project a running back's upcoming season:

Year-to-Year Statistical Correlations for RBs on Same Team in Consecutive Seasons (since 2010, min. 100 touches)
Stat Correlation
Attempts/Game 0.58
Touches/Game 0.56
Rush Yards/Game 0.56
Total Yards/Game 0.51
PPR FP/Game 0.48
Targets/Game 0.48
Total Attempts 0.44
Rushing Yards 0.40
Total Targets 0.39
Total Receptions 0.39
Total Touches 0.38
Total Yards 0.32
Total PPR FP 0.31
Total TD 0.29
Yards/Touch 0.15
Yards/Carry 0.01
Games Played -0.02

As with the other positions in this series, it's no surprise per-game stats have the strongest year-to-year correlations when you consider they simply represent a player's average performance. On the other hand, volume stats will fluctuate if a player misses a handful of games (and how many games a player plays has virtually no correlation from one year to the next).

Running Backs Need the Ball

A running back’s per-game usage is the most reliable data when trying to project his current season based on the previous year's stats. Running back production is mostly volume-driven—the year-to-year correlation for yards and fantasy scoring is only moderately strong. PPR scoring somewhat mitigates the effect of touchdowns on the bottom-line in fantasy scoring, so it makes sense a running back can have a consistent year-to-year fantasy output despite almost no correlation in touchdowns from one year to the next.

Although there is some correlation in per-game production overall from year to year, the correlation isn’t so strong that we can look at the previous season and think that a running back can easily replicate his numbers.

Per-Play Efficiency Can Fool You

The unreliability of efficiency metrics (yards per touch and yards per carry) is perhaps the biggest data point to note.

Touchdowns are generally known to be the most volatile stat (and therefore the hardest to predict), but we should also exercise caution when using a back's previous-year per-touch data as a reference point for projections.

Consider Ezekiel Elliott—one of the more consistent fantasy running backs since entering the league—and his yearly yards per carry:

Ezekiel Elliott Year-to-Year Yards Per Carry

Year Yards Per Carry
2016 5.07
2017 4.06
2018 4.72

Elliott's range of outcomes may seem relatively small, but assuming a 300-carry season, the difference between his best and worst yards per touch figure would result in a gap of roughly 300 yards—in fantasy terms, this could be the difference between four to five spots in end-of-season ranks and could have an even bigger impact in leagues that offer yardage bonuses. Even the most consistent fantasy scorers are susceptible to large swings in efficiency from season to season.

Efficiency metrics, as I've mentioned in my previous work, are perhaps best used to compare a player's end-of-season numbers to the league average, or to his individual average (if the sample is large enough). You can then decide to what extent regression to the mean should be expected.

The Bottom Line

When analyzing the previous season's running back stats, here's what to keep in mind:

  • The most predictable year-to-year stats for running backs are their usage numbers (touches, rushing attempts, targets, receptions).
  • A running back's yardage is much more likely to carry over from year to year than this touchdowns.
  • A running back's previous-year efficiency is a poor predictor of his future efficiency—don't put much stock into yards per touch and yards per carry.

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