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The Value Of Consistency At RB



By Chris Cunliffe | 8/27/09

This article is a continuation of the last two articles where we investigated historical QB and WR performance. Recall that in those articles we dug into the distribution of each player’s historical scores. We noted that if two players both score a lot of points, that in some cases we might prefer the player to be consistent than to not. And we isolated some specific players that stood out as being more or less consistent than their peers. We concluded with practical advice that we hope might be useful to some in upcoming fantasy drafts. This week, we apply the same idea to RB’s.

Approach

We focus on only the last four seasons. Our intention is to consider only games in which a fantasy football manager would have considered starting the player. Prior articles (on QB and WR) go into our subjective method of choosing the games to include in some more detail. This time around we take a similar approach and apply it to RB’s.

The table below shows the sample size we get for each player.

 Sample Of RBs
Player Sampe Size (Games)
Adrian Peterson 28
Brandon Jacobs 37
Brian Westbrook 53
Cedric Benson 36
Chris Johnson 15
Clinton Portis 53
DeAngelo Williams 42
Frank Gore 50
Jamal Lewis 58
Joseph Addai 40
Kevin Smith 15
LaDainian Tomlinson 60
Larry Johnson 49
LenDale White 30
Marion Barber 53
Marshawn Lynch 27
Matt Forte 15
Maurice Jones-Drew 43
Michael Turner 15
Pierre Thomas 7
Reggie Bush 37
Ronnie Brown 48
Ryan Grant 24
Steve Slaton 15
Steven Jackson 52
Thomas Jones 59
Tim Hightower 15
Willie Parker 54

Note that since we look at 4 years of games in Weeks 1 through 16 the maximum possible total is 60 (4 years of 15 non-bye weeks).

LaDainian Tomlinson is the only running back with a sample size of the full 60 games. Thomas Jones and Jamal Lewis are not too far behind with 59 and 58 respectively. Pierre Thomas has the smallest sample size. Sometimes having more information is useful, and we should keep this small sample size for Pierre Thomas in mind when interpreting results.

Scoring

We focus again on a PPR scoring system, consistent with last week’s article on WR’s.

 PPR Scoring
FPts Per Yard
Rush/Rec		 FPts TD
Rush /Rec		 PPR Fumbles Lost
0.1 6 .5 -2

We award points for both rushing and receiving, and we give no credit for special teams or passing.

Totals

Let’s start by looking at the average fantasy points scored per game under this set of assumptions. We look at the points per game rather than the total points, since we don’t want to imply a player has been more valuable just because they have been around for more seasons.

 Running Backs - FPts / Game
Rank Player FPts/G
1 LaDainian Tomlinson 21.5
2 Pierre Thomas 19.7
3 Brian Westbrook 19.5
4 Matt Forte 17.6
5 Larry Johnson 17.5
6 Steven Jackson 17.0
7 Adrian Peterson 16.9
8 Michael Turner 16.7
9 Maurice Jones-Drew 15.4
10 Chris Johnson 15.2
11 Steve Slaton 15.2
12 Clinton Portis 14.8
13 Frank Gore 14.7
14 Joseph Addai 14.0
15 Reggie Bush 14.0
16 Marshawn Lynch 13.9
17 Thomas Jones 13.3
18 Ronnie Brown 13.3
19 Marion Barber 13.1
20 Ryan Grant 12.7
21 Willie Parker 12.5
22 Brandon Jacobs 12.3
23 Kevin Smith 11.6
24 DeAngelo Williams 11.5
25 Jamal Lewis 11.4
26 LenDale White 11.0
27 Tim Hightower 9.4
28 Cedric Benson 8.3

LaDainian Tomlinson is at the top, which probably isn’t going to shock anyone. Pierre Thomas is next, which is probably less expected. Keep in mind, we’re only considering 7 of his games, the last 7 games of last season. So you’ll have to interpret for yourself how meaningful those are. DeAngelo Williams stands out at being close to the bottom, highlighting the fact that last season’s breakout was not a standard performance for him. His value is obviously sensitive to the week-to-week carry split with Stewart, and we assume that a fantasy owner can’t tell in advance who will get more carries, which is probably consistent with reality for the most part.This gives us some perspective on the average fantasy points per game the top RB’s have been scoring over the past few years. We continue our analysis by next investigating the distribution of their scores per game.

Volatility (and Coefficient of Variation)

Volatility is a measure which quantifies how widely a data set varies from its mean. If a player scores about the same amount of points almost every game, his scores will tend to have low volatility. If a player is just as likely to score 40 points in a week as 0, then his scores will tend to exhibit higher volatility. Let’s look at the volatility of the RB scores.

 Running Backs - Volatility
Rank Player Volatility
1 LaDainian Tomlinson 11.4
2 Adrian Peterson 10.8
3 Michael Turner 10.4
4 Larry Johnson 10.3
5 DeAngelo Williams 9.9
6 Brian Westbrook 9.7
7 Joseph Addai 9.4
8 Reggie Bush 8.7
9 Steven Jackson 8.5
10 Willie Parker 8.4
11 Marion Barber 8.3
12 Ronnie Brown 8.2
13 Chris Johnson 8.0
14 Frank Gore 7.9
15 Maurice Jones-Drew 7.9
16 Pierre Thomas 7.8
17 Jamal Lewis 7.6
18 Steve Slaton 7.5
19 LenDale White 7.4
20 Brandon Jacobs 7.2
21 Ryan Grant 6.8
22 Clinton Portis 6.8
23 Thomas Jones 6.6
24 Marshawn Lynch 6.1
25 Kevin Smith 5.2
26 Cedric Benson 5.1
27 Matt Forte 4.7
28 Tim Hightower 4.5

Note the high scoring RB’s tend to have higher volatility and the low scoring RB’s tend to have lower volatility. (two notable exceptions are Matt Forte and Pierre Thomas). Part of this might be due to the higher scoring RB’s being more volatile, but another piece is due to the fact that just looking at the volatility without scaling it for their average scores will tend to effectively overstate the volatility for the high players and understate it for the lower players.

Let’s scale their volatility by their average score. In other words, we’ll look at their coefficient of variation (CV). This will allow us to compare RB’s who average low scores against those who average high scores a little bit better.

 Coefficient of Variation
Rank Player CV
1 DeAngelo Williams 0.86
2 LenDale White 0.68
3 Joseph Addai 0.67
4 Willie Parker 0.67
5 Jamal Lewis 0.66
6 Adrian Peterson 0.64
7 Marion Barber 0.63
8 Reggie Bush 0.62
9 Michael Turner 0.62
10 Cedric Benson 0.62
11 Ronnie Brown 0.62
12 Larry Johnson 0.59
13 Brandon Jacobs 0.59
14 Frank Gore 0.54
15 Ryan Grant 0.54
16 LaDainian Tomlinson 0.53
17 Chris Johnson 0.53
18 Maurice Jones-Drew 0.52
19 Steven Jackson 0.50
20 Thomas Jones 0.50
21 Brian Westbrook 0.49
22 Steve Slaton 0.49
23 Tim Hightower 0.48
24 Clinton Portis 0.46
25 Kevin Smith 0.45
26 Marshawn Lynch 0.44
27 Pierre Thomas 0.40
28 Matt Forte 0.27
  • Matt Forte and Pierre Thomas score a lot of points, and they do it with a low coefficient of variation. That is, in their sample, they not only score a lot but they do it consistently. Matt Forte especially stands out here in that he has a bigger sample and his CV is much lower than anyone else. It’s worth noting that both of these players have a small sample size.

  • Tim Hightower and Kevin Smith don’t score many points, and their CV is low. This means that they do not score many points, and they are pretty consistent at doing it.

  • LenDale White does not score a lot of points on average, but he has a high relative CV.

So does this tell us we should take Pierre Thomas #2 in our fantasy drafts? Not exactly. It does tell us that Matt Forte and Pierre Thomas have scored a lot of points historically and they have done it consistently. Those are favorable characteristics to have and they compare favorably to some of their peers in that regard. Their sample (especially Pierre Thomas’s) is fairly small.

When choosing a running back in the later rounds of a draft, the available options probably will not be scoring a lot of points historically on average. If they were, then they probably would tend to have been picked earlier (Larry Johnson is one exception this year, as views of his future performance tend to be a lot worse than those of his historical performance). When choosing a RB like that, a high coefficient of variation tends to be more attractive than a low one. In other words, if a RB doesn’t score many points on average, then it’s preferable for him to be inconsistent than consistently bad. In some ways when people talk about a player with a low average score with upside, they are indirectly referring to a high coefficient of variation.

Distribution of Scores

Next we investigate the distribution of scoring per game of each running back. The following table shows the maximum, minimum, and percentiles of scores for each player. 90th percentile indicates 90% of the time the player scores less than that score. Median indicates 50% of the time he scores more, 50% of the time he scores less. The table is sorted by the median score.

So 90% of the time Brian Westbrook scores less than 35.7 fantasy points, but 10% of the time he scores more.

 Distribution
Rk Player Max 0.9 0.75 0.5 0.25 0.1 Min
1 Pierre Thomas 30.1 27.4 24.5 22.4 13.9 10.5 8.5
2 Brian Westbrook 42.6 35.7 23.2 18.7 14.1 8.0 1.2
3 LaDainian Tomlinson 46.9 41.0 29.9 17.5 13.1 9.5 5.0
4 Larry Johnson 43.1 31.5 23.7 17.2 10.1 3.9 (0.7)
5 Matt Forte 25.1 23.8 21.1 17.1 13.5 12.9 11.0
6 Steven Jackson 38.2 27.3 22.5 15.7 11.4 6.9 1.7
7 Steve Slaton 31.2 21.9 21.0 15.5 10.0 6.5 3.4
8 Adrian Peterson 48.0 26.9 22.0 15.3 8.1 6.6 0.3
9 Clinton Portis 29.8 22.9 18.7 14.6 8.8 5.9 3.6
10 Chris Johnson 26.4 24.9 22.6 14.0 8.3 5.7 3.3
11 Michael Turner 35.7 32.4 22.7 13.9 8.0 5.6 5.3
12 Marshawn Lynch 28.7 20.3 17.3 13.9 9.1 7.7 4.0
13 Frank Gore 38.9 24.3 20.8 13.8 8.8 4.6 1.6
14 Maurice Jones-Drew 32.4 27.2 21.0 13.2 9.4 6.0 4.5
15 Thomas Jones 32.9 20.3 17.2 12.9 8.0 6.4 3.2
16 Reggie Bush 45.3 25.6 16.4 12.9 7.0 5.8 3.7
17 Marion Barber 33.4 23.7 19.5 12.4 5.5 3.1 (0.1)
18 Kevin Smith 18.9 18.1 15.3 12.3 8.5 5.4 1.4
19 Joseph Addai 45.8 27.8 19.3 11.9 6.6 5.0 0.3
20 Ronnie Brown 42.1 21.7 16.5 11.8 7.9 5.3 0.5
21 Brandon Jacobs 27.7 21.0 17.5 11.3 5.8 3.7 1.6
22 Ryan Grant 23.2 22.3 18.0 11.0 8.9 3.6 0.6
23 Willie Parker 35.5 24.5 17.9 10.6 5.7 2.9 (0.1)
24 LenDale White 34.1 20.6 14.5 10.6 5.6 2.1 (0.1)
25 Jamal Lewis 36.4 20.7 15.9 8.9 5.9 3.7 0.8
26 Tim Hightower 18.5 16.1 10.9 8.3 6.7 4.5 3.5
27 DeAngelo Williams 34.8 26.7 17.7 7.5 3.8 2.2 (0.1)
28 Cedric Benson 19.2 15.8 11.4 7.0 3.8 2.7 0.6

The least points Matt Forte has scored is 11. That’s a lot of points for a worst day. Note that it is higher than the median performance of players including Ryan Grant, LenDale White, DeAngelo Williams, and Cedric Benson.

The following table shows the same ideas expressed as a ranking rather than raw scores (again sorted by the median).

 Ranking
Rk Player Max 0.9 0.75 0.5 0.25 0.1 Min
1 Pierre Thomas 19 6 2 1 2 2 2
2 Brian Westbrook 6 2 4 2 1 4 17
3 LaDainian Tomlinson 2 1 1 3 4 3 4
4 Larry Johnson 5 4 3 4 6 20 28
5 Matt Forte 24 15 9 5 3 1 1
6 Steven Jackson 9 7 7 6 5 6 13
7 Steve Slaton 18 19 10 7 7 8 10
8 Adrian Peterson 1 9 8 8 15 7 22
9 Clinton Portis 20 17 15 9 12 11 8
10 Chris Johnson 23 12 6 10 14 13 11
11 Michael Turner 11 3 5 11 16 14 3
12 Marshawn Lynch 21 24 20 11 9 5 6
13 Frank Gore 8 14 12 13 11 18 14
14 Maurice Jones-Drew 17 8 10 14 8 10 5
15 Thomas Jones 16 25 21 15 17 9 12
16 Reggie Bush 4 11 23 16 19 12 7
17 Marion Barber 15 16 13 17 26 24 24
18 Kevin Smith 27 26 25 18 13 15 16
19 Joseph Addai 3 5 14 19 21 17 22
20 Ronnie Brown 7 20 22 20 18 16 21
21 Brandon Jacobs 22 21 19 21 23 21 14
22 Ryan Grant 25 18 16 22 10 23 19
23 Willie Parker 12 13 17 23 24 25 24
24 LenDale White 14 23 26 24 25 28 24
25 Jamal Lewis 10 22 24 25 22 22 18
26 Tim Hightower 28 27 28 26 20 19 9
27 DeAngelo Williams 13 10 18 27 28 27 24
28 Cedric Benson 26 28 27 28 27 26 19

The table is sorted by the ranking of their median performance from best to worst. The 2 for Brian Westbrook under 0.9 indicates that the 90th percentile score of Brian Westbrook is the 2nd highest 90th percentile score of all the players considered.

The 1 for Adrian Peterson under Max indicates that his highest score is the highest high score of all the players considered. The 22 under Min indicates that his lowest score is lower than all but 6 wide receivers.

Let’s step back and see if anything stands out.
  • Pierre Thomas – there he is again. He has the highest median score. And he scores in the top 6 at all percentiles. This means his good days are better than most other’s good days. And his bad days are better than their bad days too. This is a good combination. Keep in mind (especially in this stat) that his sample size is small. It remains to be seen if he can keep this up, but this is certainly a great start for him.

  • Joseph Addai is in the top 5 at the high end, indicating his good days have been better than most. But they drop quickly and at the middle and bottom his scores range from mediocre to bad, indicating his average days and bad days are worse than most.

  • Adrian Peterson scores well at most percentiles, but lower than some might expect.

  • Maurice Jones-Drew scores in the middle of the pack to above average for the most part, and has no glaring bad points. It will be interesting to see if he is able to break out now that he is moving more towards a primary back role than his traditional shared role with Fred Taylor.

  • Even in this PPR format, Reggie Bush has a profile that is not all that attractive. Note that his 75th percentile good day is just barely ahead of Cedric Benson and Tim Hightower. For a RB known for his “upside” this is a little disappointing to see.

  • Larry Johnson’s profile is better than you might expect, even after last season’s disappointment. He scores in the top 6 of all RB’s at most percentiles.

  • LaDainian Tomlinson has the most attractive profile, scoring in the top 4 at every percentile. If you think about this, this is actually kind of amazing. This means that his good days are better than almost everyone, his average days are better than almost everyone, and even his bad days are better than almost anyone He also happens to have the highest average score too. And on top of that, he’s played in every game in the 4-year sample. It’s no surprise that LaDanian Tomlinson shines through positively every way you look at him historically.

There’s not a lot of shocking stuff in the analysis we presented. The big name RB’s shine through positively for the most part, roughly in line with (at least my) expectations at the start.

Conclusion

We highlighted some wide receivers that have scored well against their peers anyway you look at it. Most of the “top-tier” RB’s score well across the board, but LaDainan Tomlinson really stands out from the crowd. Matt Forte is another RB who stands out favorably among the top RB’s. Pierre Thomas stands out as the biggest surprise in just how favorable he looks, although it’s important to keep in mind he has a small sample. LenDale White stands out favorably against his peers at the bottom end of the top RB’s.

Sometimes having good perspective about the performance of available players historically is useful. This article aims to help build some of that perspective, and I hope you find it useful.

Obviously you would rather have your players score a lot of points and be a little inconsistent than score few and be consistent. When comparing peers who score a similar amount of points, sometimes you are looking for someone a little more consistent, and sometimes you are looking for someone with a little more upside (i.e. volatility). Hopefully this article provides some numbers that help you to do some comparisons like that in practice.

Next Steps

Next week will dig into the difference of PPR and non-PPR leagues, and try to isolate some players who have stood out in the past and might stand out in the future. As always, feel free to contact me with any questions or suggestions. See you next week!




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