NFL

# Measuring and Ranking the Running Back and Wide Receiver Draft Class of 2015

Which backs and receivers, based on their combine metrics and a little math, have a higher probability of hitting in this year's NFL Draft?

Every year in February, a group of NFL front office personnel, scouting organizations, media members, and the nation's top collegiate athletes get together for the NFL Combine. In this weeklong event, players hoping to make the leap to the NFL are measured, analyzed, and scrutinized by the movers and shakers of the league. Yet, many have wondered whether these movement tests performed in sterile conditions -- in shorts and t-shirts, free of helmets and pads -- have any validity in predicting future NFL performance.

With a large coffee in one hand and the combine results for all 1,091 wide receivers and running backs from the past 16 seasons (courtesy of mockdraftable.com) on my computer in front of me, I decided to tackle the task of assimilating the vast metrics measured at the combine for each player and converting this information into an actionable predictor of NFL potential.

### The Math

When we glance at combine numbers, our intuition gives us a general sense of a "good" combine performance versus a "bad" one. But these are subjective measures. Can we define these in a quantitative manner? First, I asked, "What exactly constitutes a 'good' combine performance? What separates the 'good' from the 'great', and the 'great' from the 'elite'?"

I decided to define the quality of an athlete's combine performance as the fold increase above what would be expected for an NFL hopeful of that athlete's size to produce. I chose to normalize everything to size to take into account a condition that makes intuitive sense: if two athlete's both run a 4.4 40-yard dash, but one athlete weighs 265 pounds and the other weights 190 pounds, we would consider the performance by the 265 pound athlete much more impressive. Therefore, I thought that rather than compare performances at face value, our analysis should somehow factor in player size.

So from the large set of historical data at my disposal, I was able to derive a set of equations to determine an athlete's expected combine numbers based on that athlete's size (specifically, weight), which served as the baseline from which I then assessed that player's actual combine performance:

Estimated 40 = (.0022 x Weight) + 4.0726
Estimated Bench = (.1313 x Weight) - 9.825
Estimated Vertical = (-.0102 x Weight) + 37.264
Estimated Broad = (-.0244 x Weight) + 124.08
Estimated 3-Cone = (.004 x Weight) + 6.1036
Estimated 20ss = (.0026 x Weight) + 3.688

So a fair question to ask would be: "Just how valid are these equations in predicting combine performance?" To test this, I took the average weight of all 1,091 running backs and wide receivers (206.6 pounds) and calculated what the combine performances would be for players of this size. I then compared these numbers to the actual average of the combine performances for all players from the last 16 seasons weighing either 205, 206, or 207 pounds (n = 63 players). The results are listed below:

Predicted206.64.52717.30135.157119.0396.9574.225
Actual (Avg.)205.94.53418.86135.402118.9827.0184.215

From the data above, we see that these equations do an excellent job of predicting combine performance for a given player's size. Using these equations, I was then able to assess how well a player's actual performance differed from their predicted performance. Players performing better than their expected combine numbers in a given event received a positive score for that event (weighted according to the dynamic range of the particular skill being measured), and conversely, players performing worse than their expected combine numbers for a given event received a negative weighted score for that event. Specifically, the scores for each player for any particular event was obtained using the following formulas:

40 = -(Observed - Expected)/(Range)
Bench = (Observed - Expected)/(Range)
Vertical = (Observed - Expected)/(Range)
3-Cone = -(Observed - Expected)/(Range)
20ss = -(Observed - Expected)/(Range)

Range is defined as the upper limit of all combine performances for all wide receivers and running backs subtracted by the lower limit for a given event.

### Wide Receiver and Running Back Ranks According to PACE

Taking the average scores across all events, I then obtained what I call my Performance Above Combine Expectations (PACE) score. This allowed me to rank all 1,091 wide receivers and running backs from 1999-2015 on the basis of their combine performances, with some of the notable names at the top five percent of all-time PACE scores listed below:

All-Time Top 50
YearNamePositionPACE ScoreAll-time Rank
2007Calvin JohnsonWR0.4321
2001Chris ChambersWR0.3552
2003Justin FargasRB0.34283
1999Edgerrin JamesRB0.2886
2001Santana MossWR0.2758
2010Demaryius ThomasWR0.24411
2014Jerick McKinnonRB0.24312
2013Christine MichaelRB0.22114
2010Ben TateRB0.21316
2008Chris JohnsonRB0.21217
2015Jaelen StrongWR0.20620
2004Kevin JonesRB0.20524
2015Chris ConleyWR0.20027
2015Ameer AbdullahRB0.19629
2011Julio JonesWR0.18737
2010C.J. SpillerRB0.18638
2008Donnie AveryWR0.18639
2015Sammie CoatesWR0.18540
2003Andre JohnsonWR0.17944
2012Ryan BroylesWR0.17546
2013Cordarrelle PattersonWR0.17448

Not surprisingly, Calvin Johnson was the top performer according to the PACE metric, achieving a score of 0.43, a figure nearly 25% greater than the second-best performer, wide receiver Chris Chambers.

Some other notable names at the top of this list include athletic freaks who have emerged recently as stars in the NFL, including Demaryius Thomas, Julio Jones, and C.J. Spiller, veterans that have shown long-term productivity in the league including the Colts franchise leader in rushing yards, Edgerrin James, Pro Bowl wideouts Santana Moss and Andre Johnson, and 2014 breakouts including Jerick McKinnon.

### Predictive Value of the PACE Metric

To further test the validity of the PACE metric as a predictor of on-field success, I decided to do a case study of the 2011 rookie class. I chose this class because we have four seasons worth of statistics for this group of players that we can then use to assess the relationship between NFL productivity and combine metrics. I ranked every wide receiver and running back participating in at least four events of the 2011 combine by PACE score, and assessed their productivity for the past four seasons using Total Net Expected Points (NEP).

Below is the list of the top 25 players of the class of 2011 as ranked by the PACE metric, along with their total NEP for each season from 2011-2014, their average NEP per season, and their positional rank (percentile) according to NEP per season:

YearNamePosPACE Score'11 NEP'12 NEP'13 NEP'14 NEPAvg NEPRB RkWR Rk
2011Greg LittleWR0.190555.9254.7230.498.1637.32-77.8%
2011Julio JonesWR0.187581.10105.5539.34141.7291.93-94.4%
2011Torrey SmithWR0.159375.3676.4597.7380.9682.63-91.7%
2011Jordan TodmanRB0.15630.00-2.021.906.891.6972.4%-
2011Aldrick RobinsonWR0.15030.0024.1631.450.4814.02-61.1%
2011Anthony AllenRB0.1460-0.452.440.000.000.5065.5%-
2011Edmond GatesWR0.14402.4520.766.830.007.51-38.9%
2011DeMarco MurrayRB0.130522.513.2139.4523.5422.1896.6%-
2011Delone CarterRB0.1190-25.368.460.000.00-4.2324.1%-
2011Jon BaldwinWR0.113921.4625.172.140.0012.19-55.6%
2011Terrance ToliverWR0.1056------0.0%
2011Ryan WhalenWR0.10331.924.890.000.001.70-22.2%
2011Ricardo LocketteWR0.09088.520.006.5512.156.81-36.1%
2011Mario FanninRB0.0811-----0.0%-
2011Ryan WilliamsRB0.07710.00-16.200.000.00-4.0527.6%-
2011Cecil ShortsWR0.07694.6785.4162.4337.1947.42-83.3%
2011Kendall HunterRB0.073510.7813.00-4.130.004.9182.8%-
2011Niles PaulWR0.07354.3210.013.3334.1012.94-58.3%
2011Greg SalasWR0.069216.200.0011.4817.1711.21-52.8%
2011Austin PettisWR0.058117.9430.6146.5113.7427.20-75.0%
2011Derrick LockeRB0.0567-----0.0%-
2011Roy HeluRB0.05524.050.6513.5725.2910.8989.7%-
2011A.J. GreenWR0.0529100.46111.17127.4978.94104.52-97.2%
2011Shane VereenRB0.05222.4018.2737.5529.6121.9693.1%-
2011Dane SanzenbacherWR0.045127.171.017.216.0110.35-50.0%

10 out of the top 25 players as ranked by PACE score had four-year NEP averages that placed them in the top 25th percentile of the 2011 class, including Pro Bowlers Julio Jones, A.J. Green, and DeMarco Murray, along with established starters such as Torrey Smith, Shane Vereen, and Cecil Shorts.

Conversely, 16 out of the bottom 25 players as ranked by PACE score had four-year NEP averages that placed them in the bottom half of the 2011 class:

YearNamePosPACE Score'11 NEP'12 NEP'13 NEP'14 NEPAvg NEPRB RkWR Rk
2011Owen SpencerWR0.0013------0.0%
2011Graig CooperRB-0.0074-----0.0%-
2011Stephen BurtonWR-0.01113.363.873.730.002.74-25.0%
2011Stevan RidleyRB-0.01302.4413.11-13.28-1.380.2258.6%-
2011Titus YoungWR-0.015056.5535.310.000.0022.96-69.4%
2011Darren EvansRB-0.0355-----0.0%-
2011Tori GurleyWR-0.03860.000.003.240.000.81-19.4%
2011Shaun DraughnRB-0.03990.002.59-1.54-4.11-0.7644.8%-
2011Jerrel JerniganWR-0.04550.001.8033.470.598.97-47.2%
2011Vincent BrownWR-0.048429.500.0041.057.7419.57-63.9%
2011Vai TauaRB-0.0494-----0.0%-
2011Evan RoysterRB-0.049518.681.50-2.290.004.4779.3%-
2011DeAndre BrownWR-0.0510------0.0%
2011Tandon DossWR-0.05110.0010.9822.500.008.37-41.7%
2011Armon BinnsWR-0.05180.0019.820.000.004.96-30.6%
2011Dion LewisRB-0.05451.625.100.000.001.6869.0%-
2011Johnny WhiteRB-0.0557-4.50-1.230.000.00-1.4341.4%-
2011Dwayne HarrisWR-0.06320.0017.398.888.378.66-44.4%
2011O.J. MurdockWR-0.0714------0.0%
2011Randall CobbWR-0.073031.4698.0440.95118.0372.12-88.9%
2011Jacquizz RodgersRB-0.11613.906.477.973.535.4786.2%-
2011Lestar JeanWR-0.13020.0014.067.850.005.48-33.3%
2011Mark IngramRB-0.14410.27-6.87-2.997.10-0.6248.3%-
2011Matt AsiataRB-0.18770.00-2.00-1.8411.451.9075.9%-

Only four players, Randall Cobb, Matt Asiata, Jacquizz Rodgers, and Evan Royster, had four-year NEP averages placing them in the top 25th percentile of the 2011 class. To further emphasize the predictive value of the PACE metric to player performance, six of the players from this group actually failed to ever see regular season playing time in the NFL.

A closer look at the data reveals that 17 out of the top 25 players as ranked by the PACE metric ranked in the top half of their class according to their four-year average NEP score. In contrast, only 9 of the bottom 25 players achieved this same feat. For these bottom 25 players, there was instead an enrichment for those ranking in the bottom half of their class according to NEP per season, with 16 of these players clustering into this group:

Percentile Rank (Pos)
100-75th75-50th50-25th25-0
PACE Score Top 2510735
PACE Score Bottom 254597

In addition, the average NEP scores over the 2011-2014 seasons for the top 25 players as measured by PACE nearly tripled the average NEP scores for the bottom 25 players (23.7 vs. 8.7):

GroupFour Year Avg. of Total NEP
PACE Score Top 2523.7
PACE Score Bottom 258.7

Through this analysis of the 2011 rookie class, we can see at multiple levels that players ranking near the top of the list according to PACE score have a strong tendency to have productive NFL careers, whereas players ranking near the bottom of this list (with a few rare exceptions) have a strong tendency to have either lackluster or even non-existent NFL careers.

### Using the PACE Score to Assess the Incoming Class of 2015

So how does the running back and wide receiver class of 2015 stack up when we rank them based on the PACE metric? Below is the list of players clustering into the top 20 (or roughly top 25% of all skill position players) according to PACE score:

Rookie Class of 2015 Top 20
YearNamePosPACE Score2015 Rk
2015Jaelen StrongWR0.2060647021
2015Chris ConleyWR0.1999886652
2015Ameer AbdullahRB0.1959709323
2015Sammie CoatesWR0.1848313384
2015David JohnsonRB0.1630483635
2015Tevin ColemanRB0.14928756
2015Kevin WhiteWR0.1243248997
2015Antwan GoodleyWR0.1215789478
2015Kenny BellWR0.1106324429
2015Geremy DavisWR0.10512304810
2015Amari CooperWR0.10414853811
2015Rannell HallWR0.1035031512
2015Ty MontgomeryWR0.08829435113
2015Tre McBrideWR0.08291908614
2015DeVante ParkerWR0.0816259715
2015Phillip DorsettWR0.08114809316
2015Melvin GordonRB0.06345959417
2015Jay AjayiRB0.05670806418
2015Devin SmithWR0.04759330519
2015Michael DyerRB0.04238485720

We see the appearance of some familiar, highly-touted NFL draft prospects on this list including Fred Biletnkoff Award winner Amari Cooper, Doak Walker Award winner Melvin Gordon, and projected first-rounders Kevin White and Jaelen Strong. But where it gets interesting is the presence of names on this list projected to be drafted in the fifth round or later, including Georgia Bulldog wideout Chris Conley and Louisville running back Michael Dyer. These players represent excellent value picks for NFL teams willing to take a chance on them in the upcoming draft.

If history serves as a guide for us, the players on this top 20 list have a high probability of being impact players for the NFL teams that draft them this upcoming April. And, in particular, a few of these aforementioned players -- who have all the athletic skills necessary to succeed at the NFL level -- may represent overlooked candidates with the potential to have careers that vastly outperform their NFL draft position.