## The Best FG Kickers

Note: This analysis has been updated. New post can be found here.

Judging who the best field goal kickers are in the NFL is difficult. The kickers with the best range are often sent out to attempt impossibly long field goal tries. Some kickers benefit from circumstance in some years because their team's drives stall closer to the endzone than others.

Using data from the 2003-2006 regular seasons, obtained at profootballweekly.com, I may have a stumbled on a novel approach to solve the problem. My intent was to follow up on an earlier article that suggested that field goal kickers were severely underpaid relative to their impact on winning. A couple of readers (correctly) pointed out that some kickers' performances appear inflated due to luck, so the "best" kicker one year may really only be an average kicker who got lucky. In attempting to isolate the true talent level from other circumstances, including luck, involved in kicking performance, I developed the following approach.

For each kicker from '03-'06, I computed an expected percentage of FGs made based on three kicker stats:

1. Average FG attempt distance
3. Average FG missed distance

To compute the expected FG%, I ran a regression of actual FG percentages based on those three variables. The fitted values of the regression model became expected FG%. In simple terms, it's the average FG% that an NFL kicker would be expected to have given his average attempt, made, and miss distances. Essentially, this establishes a level-of-difficulty score, much like in diving, for each kicker's season.

The difference between each kicker's actual FG% and his expected FG% can therefore be considered a true measure of a kicker's performance in a season, accounting for attempt distances. This method does not yet isolate how much of a kicker's performance was due to luck, but it is the first necessary step to do so.

Here are the best kicking performances of the 2003-2006 period, accounting for attempt distances:

 Year Player Team Avg Att Avg Made Avg Miss Actual % Expected % Act-Exp % 2003 Vanderjagt* Ind. 33.8 33.8 NA 1.00 0.71 0.287 2004 Hanson Det. 38.1 37.9 43.0 0.96 0.88 0.077 2003 Hanson Det. 38.1 37.9 43.0 0.96 0.88 0.077 2006 Kasay Car. 38.9 36.8 56.0 0.89 0.83 0.063 2005 Kasay Car. 38.9 35.2 50.8 0.77 0.70 0.062 2005 Rackers Ariz. 38.1 37.6 48.5 0.95 0.89 0.061 2005 Nedney S.F. 38.5 38.0 45.5 0.93 0.87 0.058 2003 Janikowski Oak. 39.0 37.3 51.3 0.88 0.82 0.056 2006 Longwell Minn. 33.6 30.4 50.0 0.84 0.78 0.055 2003 Graham Cin. 37.2 35.2 51.3 0.88 0.83 0.055 2003 K. Brown Hou. 38.2 35.6 49.8 0.82 0.77 0.047 2003 Brien N.Y.J. 37.3 35.0 49.6 0.84 0.80 0.047 2006 Hanson Det. 36.3 34.4 50.0 0.88 0.83 0.045 2005 Hanson Det. 35.7 32.4 48.2 0.79 0.75 0.045 2006 Rackers Ariz. 37.6 34.0 48.9 0.76 0.71 0.044 2004 Wilkins St.L. 35.9 35.5 41.7 0.93 0.88 0.044 2003 Wilkins St.L. 35.9 35.5 41.7 0.93 0.88 0.044 2006 Lindell Buff. 35.9 35.3 42.5 0.92 0.88 0.043 2006 Stover Balt. 33.2 33.0 35.5 0.93 0.89 0.040 2006 Vinatieri Ind. 36.6 35.5 45.3 0.89 0.85 0.039 2004 Vinatieri N.E. 34.9 34.0 48.5 0.94 0.90 0.038 2006 Graham Cin. 36.9 34.6 48.4 0.83 0.80 0.038 2003 Longwell G.B. 36.2 35.0 44.7 0.89 0.85 0.036 2004 Longwell G.B. 36.2 35.0 44.7 0.89 0.85 0.036 2005 Bironas Ten. 37.4 34.6 48.3 0.79 0.76 0.033 2004 Janikowski Oak. 36.3 35.5 43.0 0.89 0.86 0.030 2003 Stover Balt. 34.7 32.8 47.6 0.87 0.84 0.029 2003 Lindell Buff. 33.9 29.5 44.4 0.71 0.68 0.027 2004 Stover Balt. 34.8 34.1 41.7 0.91 0.88 0.027 2006 Elam Den. 33.3 32.6 43.5 0.93 0.90 0.027 2006 Kaeding S.D. 35.8 35.2 41.0 0.90 0.87 0.027 2003 Andersen K.C. 39.1 36.9 47.5 0.80 0.77 0.027 2005 Wilkins St.L. 39.1 38.4 44.0 0.87 0.84 0.026 2005 Vanderjagt Ind. 32.8 32.2 39.5 0.92 0.89 0.026 2003 Akers Phil. 36.4 34.3 46.4 0.83 0.80 0.026 2004 Akers Phil. 36.4 34.3 46.4 0.83 0.80 0.026 2006 Wilkins St.L. 36.8 35.5 45.2 0.87 0.84 0.025 2005 Reed Pitt. 35.4 33.1 46.8 0.83 0.80 0.025 2005 Stover Balt. 35.9 34.9 43.3 0.88 0.86 0.025 2003 Anderson Ten. 36.5 35.3 44.8 0.87 0.85 0.024 2006 Gould Chi. 36.8 36.2 42.0 0.89 0.86 0.024 2004 Graham Cin. 37.2 36.3 43.0 0.87 0.85 0.023 2005 Dawson Clev. 31.6 31.3 36.5 0.93 0.91 0.022 2005 Vinatieri N.E. 36.4 33.9 46.4 0.80 0.78 0.022 2004 Kasay Car. 36.9 35.3 45.3 0.84 0.82 0.021 2003 Kasay Car. 36.9 35.3 45.3 0.84 0.82 0.021 2005 Kaeding S.D. 36.4 35.5 42.7 0.88 0.85 0.020 2006 Carney N.O. 32.4 32.0 37.5 0.92 0.90 0.020 2005 Peterson Atl. 31.6 31.0 38.5 0.92 0.90 0.018 2004 Elam Den. 36.1 34.7 44.0 0.85 0.83 0.018 2003 Feely Atl. 38.1 34.3 47.1 0.70 0.69 0.018 2004 Feely Atl. 38.1 34.3 47.1 0.70 0.69 0.018 2004 Gramatica T.B. 37.2 31.9 45.6 0.62 0.60 0.017 2003 Gramatica T.B. 37.2 31.9 45.6 0.62 0.60 0.017 2003 Elam Den. 36.2 35.4 41.5 0.87 0.86 0.014 2003 Christie S.D. 35.9 32.7 45.4 0.75 0.74 0.014 2005 Graham Cin. 34.0 32.8 43.0 0.88 0.86 0.011 2006 Feely N.Y.G. 34.4 32.9 43.0 0.85 0.84 0.010 2005 Akers Phil. 39.6 36.5 48.0 0.73 0.72 0.010 2006 Nugent N.Y.J. 33.8 33.2 38.7 0.89 0.88 0.010 2003 Carney N.O. 38.4 35.3 47.0 0.73 0.72 0.009 2004 Carney N.O. 38.4 35.3 47.0 0.73 0.72 0.009 2006 Andersen Atl. 34.3 33.4 40.0 0.87 0.86 0.007 2003 P. Dawson Clev. 33.6 32.1 43.0 0.86 0.85 0.007 2003 Cundiff Dall. 36.0 33.7 45.0 0.79 0.79 0.006 2004 Cundiff Dall. 36.0 33.7 45.0 0.79 0.79 0.006 2005 Gould Chi. 35.0 32.3 44.7 0.78 0.77 0.006 2006 Bryant T.B. 36.7 34.2 45.2 0.77 0.77 0.004 2005 Elam Den. 38.0 35.3 46.0 0.75 0.75 0.003 2004 Vanderjagt Ind. 35.5 33.4 44.2 0.80 0.80 0.000 2005 Tynes K.C. 35.4 33.7 43.0 0.82 0.82 -0.001 2005 Nugent N.Y.J. 35.7 33.5 43.8 0.79 0.79 -0.004 2006 Scobee Jax. 39.0 37.8 44.2 0.81 0.82 -0.004 2005 Janikowski Oak. 37.6 33.6 45.6 0.67 0.67 -0.005 2005 Scobee Jax. 36.4 34.0 44.0 0.77 0.77 -0.005 2003 J. Brown Sea. 39.7 37.1 46.8 0.73 0.74 -0.006 2004 J. Brown Sea. 39.7 37.1 46.8 0.73 0.74 -0.006 2004 Tynes K.C. 37.9 35.2 45.5 0.74 0.75 -0.007 2004 Hall Wash. 38.8 36.6 45.5 0.76 0.77 -0.008 2003 Hall Wash. 38.8 36.6 45.5 0.76 0.77 -0.008 2004 Reed Pitt. 34.0 33.1 38.8 0.85 0.86 -0.011 2004 Scobee Jax. 35.2 32.9 43.1 0.77 0.79 -0.012 2006 Mare Mia. 37.1 34.1 45.1 0.72 0.73 -0.012 2003 Elling Minn. 36.8 33.8 44.4 0.72 0.73 -0.014 2004 Elling Minn. 36.8 33.8 44.4 0.72 0.73 -0.014 2004 Lindell Buff. 29.5 28.1 37.8 0.86 0.87 -0.015 2004 Dawson Clev. 34.7 33.5 40.6 0.83 0.84 -0.016 2006 Nedney S.F. 34.3 33.2 39.5 0.83 0.85 -0.019 2005 Feely N.Y.G. 36.4 35.7 40.0 0.83 0.85 -0.020 2006 Brown Sea. 36.2 34.9 41.8 0.81 0.83 -0.021 2006 Tynes K.C. 36.9 35.1 43.1 0.77 0.80 -0.024 2006 Bironas Ten. 34.4 32.5 41.7 0.79 0.81 -0.025 2005 M. Bryant T.B. 38.4 38.4 38.5 0.84 0.87 -0.026 2005 J. Brown Sea. 41.3 39.1 46.9 0.72 0.75 -0.027 2003 Mare Mia. 37.4 35.5 43.1 0.76 0.79 -0.027 2004 Kaeding S.D. 35.3 34.0 40.6 0.80 0.83 -0.032 2005 Lindell Buff. 35.3 34.7 38.3 0.83 0.86 -0.032 2006 K. Brown Hou. 39.4 37.9 44.0 0.76 0.79 -0.034 2004 K. Brown Hou. 37.5 34.9 43.7 0.71 0.75 -0.039 2004 Brien N.Y.J. 35.9 35.5 38.2 0.83 0.87 -0.039 2003 Vinatieri N.E. 33.0 30.4 40.2 0.74 0.78 -0.041 2005 Mare Mia. 34.8 34.6 35.8 0.83 0.88 -0.045 2006 Janikowski Oak. 38.9 36.8 44.4 0.72 0.77 -0.045 2003 Conway Clev. 36.8 34.9 42.0 0.74 0.79 -0.050 2006 Gostkowski N.E. 32.7 30.9 38.7 0.77 0.82 -0.050 2006 Akers Phil. 34.3 33.0 39.0 0.78 0.83 -0.051 2005 Carney N.O. 33.6 32.2 38.4 0.78 0.83 -0.051 2005 K. Brown Hou. 35.6 34.1 40.6 0.77 0.82 -0.051 2006 Rayner G.B. 35.7 33.9 40.9 0.74 0.80 -0.056 2004 Anderson Ten. 37.6 36.7 40.6 0.77 0.83 -0.058 2006 Vanderjagt Dall. 34.0 31.8 39.6 0.72 0.79 -0.064 2006 Dawson Clev. 36.7 34.9 41.5 0.72 0.79 -0.067 2005 Cortez Ind. 35.3 33.3 40.2 0.71 0.79 -0.082 2005 Longwell G.B. 37.7 36.8 40.4 0.74 0.83 -0.088 2005 Edinger Minn. 36.5 35.5 39.4 0.74 0.83 -0.096 2004 Edinger Chi. 38.4 37.7 40.3 0.72 0.83 -0.111 2003 Edinger Chi. 38.4 37.7 40.3 0.72 0.83 -0.111 2006 Reed Pitt. 35.6 35.0 37.4 0.74 0.85 -0.113 2004 Mare Mia. 39.0 39.1 38.8 0.75 0.87 -0.117 2004 Gramatica Ind. 34.6 31.1 39.5 0.58 0.70 -0.122 2003 Reed Pitt. 34.4 33.8 36.1 0.72 0.86 -0.141 2003 Marler Jax. 35.9 33.5 39.5 0.61 0.75 -0.148

Here is a list ranking the kickers from best to worst based on their multi-year performance during the same period. The number of seasons in which each kicker qualified is also listed. (* Vanderjagt's perfect year skews his results strongly. His average miss distance in 2003 was theoretically infinite! Giving him a realistic yet excellent score (+0.10) for '03 would place him between Stover and Nedney.)

 Kicker % Act-Exp Years Vanderjagt* 0.062 4 Hanson 0.061 4 Rackers 0.053 2 Kasay 0.042 4 Wilkins 0.035 4 Graham 0.032 4 Stover 0.030 4 Nedney 0.019 2 Peterson 0.018 1 Andersen 0.017 2 Elam 0.016 4 Gould 0.015 2 Vinatieri 0.014 4 Christie 0.014 1 Longwell 0.010 4 Janikowski 0.009 4 P. Dawson 0.007 1 Feely 0.007 4 Cundiff 0.006 2 Lindell 0.006 4 Kaeding 0.005 3 Bironas 0.004 2 Bryant 0.004 1 Brien 0.004 2 Akers 0.003 4 Nugent 0.003 2 Carney -0.003 4 Scobee -0.007 3 Hall -0.008 2 Tynes -0.010 3 J. Brown -0.013 3 Elling -0.014 2 Anderson -0.017 2 K. Brown -0.019 4 Dawson -0.021 3 Brown -0.021 1 M. Bryant -0.026 1 Gramatica -0.029 3 Conway -0.050 1 Gostkowski -0.050 1 Mare -0.050 4 Rayner -0.056 1 Reed -0.060 4 Cortez -0.082 1 Edinger -0.106 3 Marler -0.148 1

Acounting for Vanderjagt's perfect year, Jason Hanson comes out on top. But to put things in perspective, a +6% accuracy rate above average equates to about 1.75 extra FGs made per season.

### 7 Responses to “The Best FG Kickers”

1. Anonymous says:

You could also perform a logistic regression, using an individual made/missed FG as the response regressed on distance + player, where the player coefficient would be the number of interest. I also think having a distance^2 variable makes sense.

2. Brian Burke says:

Ed-

I agree on both points. But I don't have individual kick-by-kick data for the logistic regression. That would be interesting though.

I tried distance^2 variables, along with other operations to make the relationship between distance and accuracy as linear as possible. Actually using ln(FG%) as the dependent variable worked best, but it did not change the results much at all. Within the narrow range of average distances, the curve is already approximately linear.

3. Tarr says:

- The top 5 kickers all play for warm weather or dome teams. I would suggest including a dome and temperature variable in the regression, or at least testing to see if these have significant effects on accuracy.

- Are blocks included in the data? My suspicion is that blocked kicks are not strongly dependent on the kicker. Of course there's not enough blocked kick data to really test this, but my guess is that blocks should be thrown out.

4. Brian Burke says:

Good point about the indoor/warm weather kickers. I'll see if I can redo the regression with dummy variables for domes/warm climate soon.

Not sure about blocks, but I agree there are too few to effect the data in a meaningful way. I'm not sure kickers can really control that much of most types of blocks anyway. My bet would be that if a kicker puts his foot to the ball and it doesn't go through the posts for any reason, it's considered a miss.

5. Rob Cullin says:

Doesn't this analysis then address your earlier question of whether Kickers are paid enough? If the difference between the best and worst kickers is about 15 points a year vs. average (my math may be wrong there), then pay is supressed because the differential between players is low.

Isn't high pay associated with high differential impact above average. Thus why QBs, RBs, WRs, and Pass Rushers are the highest paid players as the best have a higher differential over the average player?

6. Brian Burke says:

Yeah, I get the same thing.

average FG attempts = 24 per yr

24 att * 20% diff * 3 pts = 15 pts

A couple observations: FG kicker accuracy is fairly steady from year to year. The variance mostly comes from situational variables--attempt distances. Even including variance from luck (small # of reps), the difference among kickers is very small. This is probably why they are underpaid relative to their contribution to game outcomes. They're replaceable.

7. Brian Burke says:

I just redid the regression. I probably don't have time to post everything tonight. But here are a few observations.

1. The perfect Vanderjagt year really threw off the data. His zero miss distance skewed the entire model.

2. By using a natural log of the accuracy as the dependent variable, the relationship between kick accuracy and attempt distance is more linear.

3. But by excluding Vanderjagt's perfect season and by using the ln(accuracy) model, the results are very different. The difference between the best and worst kickers may be several times larger than I previously estimated.

4. Surprisingly, neither warm weather or indoor kickers were significant factors.