2007 FG Kicker Ranking

There aren't many positions in team sports as lonely as the place kicker. Alone on the sidelines all game long, he's asked to make the game-winning field goal in overtime to send his team to the Super Bowl. Or maybe his head coach doesn't have enough faith in his leg to attempt a 48 yard try, and instead goes for it on 4th and 13 only to ultimately lose the Super Bowl by 3 points.

When we grade field goal kickers, we need to account for attempt distance and other factors. And attempt distance is complicated--it's non-linear. A 40 yard attempt is not twice as difficult as a 20 yd attempt. In fact, here is a graph of the average accuracy rates for field goals of various attempt distances.

So based on the analysis described here, I calculated the expected FG percentage for every NFL kicker based on his average attempt distance and home stadium environment. The difference between his actual FG% and his expected FG% can be considered his true performance given the difficulty of his attempts.

The table below lists all FG kickers from 2007 who had at least 10 attempts. It's sorted from best to worst. Click on the headers to resort as desired.

Kicker	Team	Avg Yds Att	# Att	Actual FG%	Exp FG%	Act-Exp %
Feely		36.6	23	91	83	9
Bironas		36.7	39	90	81	9
Reed		34.1	25	92	84	8
Nedney		36.1	19	89	81	8
Graham		33.4	34	91	85	6
Longwell		41.2	24	83	77	6
Gould		37.9	36	86	80	6
Brown		38.3	29	86	80	6
Scobee		33.5	13	92	86	6
Lindell		35.0	27	89	83	6
Elam		36.4	31	87	81	6
Andersen		34.3	28	89	84	5
Kaeding		35.1	27	89	84	5
Kasay		35.9	28	86	82	4
Hanson		38.7	35	83	80	3
Dawson		34.1	30	87	84	3
Gostkowski		32.9	24	88	85	2
Brown		37.5	34	82	80	2
Suisham		36.8	35	83	81	2
Stover		35.2	32	84	83	2
Folk		36.1	31	84	82	1
Bryant		35.0	33	85	84	0
Tynes		33.5	27	85	85	0
Carney		32.9	14	86	85	0
Crosby		38.2	39	79	80	0
Nugent		35.5	36	81	82	-2
Janikowski		42.7	32	72	75	-3
Wilkins		38.7	32	75	80	-5
Akers		35.3	32	75	83	-8
Rackers		39.1	30	70	79	-9
Vinatieri		30.4	29	79	89	-10
Rayner		38.0	22	68	80	-11
Mare		34.7	19	53	84	-31

Congratulations to Jay Feely and the Dolphins, who at least have bragging rights to something in 2007. And jeez, what happened to Mare down in New Orleans? Only 19 attempts, but still that's significantly bad to say the least. Rackers seemed to have a down year. He was one of the top FG kickers over the last two years.

(Except for Mare) kickers are mostly bunched together in performance. Although according to raw accuracy percentage they appear separated by a wide disparity, in reality the difference in performance among field goal kickers is not large. In my previous analysis, I estimated that one stadard deviation in true accuracy is 7.7%. And for every standard deviation difference, a kicker would yield on average an additional 2.3 field goals worth 6.7 points in a season. Whether that's considered a lot or not depends on your perspective.

Coaches and Risk

Recently I've been looking at risk and reward in the NFL using financial portfolio theory, a branch of math that analyzes and optimizes various risk-reward strategies. I've been building on previous research that applied the utility function to analyze each team's run/pass balance. In the last post, I calculated what each team's risk level (α) was for the 2006 season.

Risk was calculated as a level of risk aversion (or tolerance) based on the relative expected yardage gains and volatility of a team's running plays and passing plays. This method considers not only the simple ratio between run plays and pass plays, but the variance of each as well. For example, it considers whether a passing game is a short, high-percentage game or an aggressive down field game. Positive α means a team was risk averse, and negative α means a team was risk tolerant.

But grading play callers as risk tolerant or averse is slightly more complicated. I noted that winning teams were often the more conservative teams, but that conservative play calling was likely the result of having a lead. In other words, winning leads to conservative play calling, not the other way around.

I also noticed a clearly linear relationship between team wins and risk level. Below is a graph of risk aversion vs. team wins. We can see that teams with a lot of wins generally are the teams that can afford to be conservative.

The upward sloping line is the regression best-fit line. It suggests the typical level of risk for each number of season wins. For example, a team with 12 wins should have a fairly conservative profile, an α of about 0.02. And a team with 8 wins should have been more aggressive, with an α of about 0.01.

The distance above or below the best-fit line could be considered the excess risk beyond that which is appropriate for each number of wins. This value is the "residual" of the regression. Note that I said "could be considered." Keep in mind that an 8-win team that appears "too risky" may really be a 6-win team that gambled often and got lucky. There is an unquantified part of the equation that is random luck.


Now we have a way to score teams and coaches as risk averse or risk tolerant. The table below ranks each coach in terms of his excess risk, from the most risky to the most conservative. (I excluded Atlanta from the analysis because they were severe outliers in 2006. Vick's boom and bust scrambling style defied convention. The Falcons appeared to be over 20 times more aggressive than the next riskiest team due to their relatively very high variance in their running game.)

Team	Coach	Wins	Risk	Excess Risk
	Fisher	8	-0.013	-0.0232
	Cowher	8	-0.011	-0.0206
	Shanahan	9	-0.001	-0.0137
	Smith	13	0.008	-0.0131
	Shell	2	-0.016	-0.0122
	Holmgren	9	0.002	-0.0101
	Coughlin	8	0.002	-0.0075
	Nolan	7	0.002	-0.0059
	Jauron	7	0.003	-0.0046
	Reed	10	0.011	-0.0040
	McCarthy	8	0.006	-0.0037
	Fox	8	0.007	-0.0034
	Billick	13	0.020	-0.0016
	Del Rio	8	0.009	-0.0013
	Gruden	4	0.000	-0.0006
	Mangini	10	0.016	0.0015
	Childress	6	0.008	0.0030
	Edwards	9	0.016	0.0039
	Shottenheimer	14	0.029	0.0049
	Kubiak	6	0.011	0.0057
	Saban	6	0.011	0.0059
	Crennel	4	0.008	0.0068
	Dungy	12	0.026	0.0071
	Parcells	9	0.019	0.0072
	Linehan	8	0.018	0.0077
	Gibbs	5	0.011	0.0078
	Lewis	8	0.019	0.0090
	Green	5	0.013	0.0094
	Marinelli	3	0.009	0.0107
	Payton	10	0.030	0.0151
	Belichick	12	0.039	0.0197
	Mora	7	-0.438	na

Another way of looking at excess risk is presented in the graph below. The teams are sorted from most to fewest wins. Click to expand it.

Notice how many below-average teams were risk averse. Oakland was the only team to display a high degree of risk tolerance. But this is likely due to their incredibly inconsistent passing game and inability to protect their quarterbacks.

Also notice how many teams that are considered "pass first" teams, such as IND, STL, CIN, and NO, show up on the risk averse side. They aren't considered too risk averse because they run too much, but because their passing games were so consistent. This result suggests they should have thrown even more, or thrown deeper to riskier routes more often.

Of course we really could be talking about offensive coordinators rather than head coaches. But with few exceptions, it's the head coach that really sets his team's overall strategy. We're also only looking at one year--because it's the one year of data I have. It would be really interesting to see if some coaches consistently show the same level of risk aversion or tolerance over several seasons. But to get the data requires a play-by-play NFL database, something not readily available...yet.