OT
Adjusted SPARQ | Coefficient | P-Value |
Constant | -25.0741 | 0.70 |
Arm Length | 0.725946 | 0.50 |
Weight | 0.349363 | 0.03 |
BMI | -1.36164 | 0.23 |
Forty | -13.9585 | 0.06 |
Bench | 0.218972 | 0.35 |
Broad | 0.223903 | 0.30 |
Adjusted R-Squared
SPARQ = 0.05
Adjusted SPARQ = 0.08
Conclusion
The offensive tackle position is complicated because the best players have a mixture of physicality (Weight, Bench) and speed (Forty). Being lengthy and not overly heavy relative to a tackle’s height are important factors, too. My model surprisingly excluded any agility measurables, which was a surprise to me given their pass-blocking technique, but being big and fast has proven to be more important over the last decade-plus. Offensive tackle prototypes are Nate Solder and Jack Conklin.
iOL
Adjusted SPARQ | Coefficient | P-Value |
Constant | 18.4942 | 0.51 |
Shuttle | -8.34605 | 0.06 |
Speed Score | 0.171192 | 0.06 |
BMI | 0.518003 | 0.33 |
Adjusted R-Squared
SPARQ = 0.02
Adjusted SPARQ = 0.03
Conclusion
From an analytics perspective, it’s almost impossible to predict NFL success for interior offensive linemen. Production metrics are hard to come by and athleticism isn’t a good predictor of rookie contract production. Both traditional SPARQ and my Adjusted SPARQ have proven to be bad, but the weight-adjusted forty (Speed Score) and agility (Shuttle) would be the things to pay attention to if forced to look into interior line athleticism metrics. I guess Nick Mangold and Ryan Kelly are prototypes.
DT
*Updated*
Adjusted SPARQ | Coefficient | P-Value |
Constant | -31.8869 | 0.43 |
| Weight | 0.240573 | 0.00 |
| Ten Split | -4.86816 | 0.77 |
| Broad | 0.434016 | 0.00 |
| Three Cone | -10.5358 | 0.00 |
| Speed Score | 0.139922 | 0.15 |
Adjusted R-Squared
SPARQ = 0.13
Adjusted SPARQ = 0.16
Conclusion
My Adjusted SPARQ model uses a combination of size, speed, burst, and agility while ignoring the bench press. Defensive tackles who are quick and agile are the ones who test the best in my model, making Aaron Donald and Fletcher Cox prototypes.
EDGE
*Updated*
Adjusted SPARQ | Coefficient | P-Value |
Constant | 5.76944 | 0.85 |
| Broad | 0.295998 | 0.03 |
Cone | -6.79204 | 0.04 |
| Speed Score | 0.202388 | 0.02 |
Adjusted R-Squared
SPARQ = 0.13
Adjusted SPARQ = 0.16
Conclusion
Athleticism clearly matters for edge rushers. Explosiveness (Broad, Speed Score) and agility (Three Cone) specifically are key for speed rushers who need to bend around offensive tackles or counter inside to create pressure on the quarterback. Von Miller, Danielle Hunter, and J.J. Watt are prime examples of this type of player.
LB
*Updated*
Adjusted SPARQ | Coefficient | P-Value |
Constant | 59.8817 | 0.20 |
| Weight | 0.0598279 | 0.58 |
10 Yard Split | -30.1829 | 0.12 |
Shuttle | -8.48411 | 0.14 |
Speed Score | 0.240589 | 0.02 |
Adjusted R-Squared
SPARQ = 0.05
Adjusted SPARQ = 0.09
Conclusion
Most of the predictiveness in athleticism for off-ball linebackers can be explained by the weight-adjusted forty (Speed Score). It’s by far the most helpful athletic metric I’ve come across, one that has pinpointed the best linebackers of the 2000s. My model also incorporates agility (Shuttle) and burst (10 Yard Split), but sorting by speed score is nearly as effective. Linebackers like Patrick Willis and Bobby Wagner are prototypes for the position. I won’t be surprised if linebackers continue to become smaller and faster as passing games and sweeps become more popular in NFL offenses.
Safety
*Updated*
Adjusted SPARQ | Coefficient | P-Value |
Constant | 43.7161 | 0.22 |
| Weight | 0.09191 | 0.21 |
| 10 Yard Split | -21.2446 | 0.12 |
| Vertical | 0.374285 | 0.14 |
| Short Shuttle | -7.65368 | 0.11 |
Adjusted R-Squared
SPARQ = 0.03
Adjusted SPARQ = 0.03
Conclusion
Safety is another position that’s difficult to evaluate because college production and athleticism aren’t very predictive of NFL success. Size, speed, agility, and burst all play minor roles in my Adjusted SPARQ model, but none of the available metrics are that important. If forced to pick metrics to look at, I’ll focus on raw speed (Forty, 10 Yard Split) and burst (Vertical). Eric Berry and Eric Reid are safety prototypes.
CB
Adjusted SPARQ | Coefficient | P-Value |
Constant | -27.2002 | 0.67 |
Height | 1.45033 | 0.01 |
BMI | 2.01554 | 0.00 |
10 Yard Split | -24.3512 | 0.12 |
Vertical | 0.348413 | 0.17 |
Cone | -4.18381 | 0.23 |
Forty | -14.6466 | 0.14 |
Adjusted R-Squared
SPARQ = 0.07
Adjusted SPARQ = 0.09
Conclusion
Athleticism matters a little more for corners than it does at safety, but relying on athleticism is a tad problematic. My Adjusted SPARQ model found size (Height, BMI) and speed (Forty, 10 Yard Split) to be the most important factors, while agility (Cone) and burst (Vertical) played minor roles. Jalen Ramsey and Byron Jones are examples of big and fast corners that my model loves.
NFL Combine Cheat Sheet
These are the testing events that actually matter (to some degree) for each type of player:
Offense
RB (under 210 lbs) - Three Cone, 10 Yard Split
RB (at least 210 lbs) - Speed Score (weight-adjusted forty), Broad Jump
WR (under 6’0) - Speed Score (weight-adjusted forty), Short Shuttle
WR (at least (6’0) - Broad Jump
TE - Speed Score (weight-adjusted forty), Three Cone, Vertical Jump
OT - Forty, Broad Jump, Bench Press
iOL - Speed Score (weight-adjusted forty), Short Shuttle
Defense
DT (under 310 lbs) - Speed Score (weight-adjusted forty), Three Cone
DT (at least 310 lbs) - Speed Score (weight-adjusted forty)
EDGE - Three Cone, Broad Jump, Speed Score (weight-adjusted forty)
LB - Speed Score (weight-adjusted forty), Short Shuttle
S - Speed Score (weight-adjusted forty), Vertical Jump
CB - Forty, Vertical Jump, Three Cone
