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An expectation-based metric for NFL field goal kickers

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  • Pasteur R. Drew
  • Cunningham-Rhoads Kyle

    (Mathematics and Computer Science, College of Wooster, 311 Taylor Hall, 1189 Beall Ave., Wooster, OH 44691, USA)

Abstract

The standard metric for American football field goal kickers is simply the percentage of attempts successfully converted. Due to variance in distance of attempts and other conditions (weather, altitude, defense, etc.), we argue that field goal percentage is an insufficient measure of kicker performance. Using three seasons of NFL data, we construct a multivariate logistic regression model for the success probability of a given attempt. This leads naturally to metrics in which a kicker’s performance is compared to model expectations, if a replacement-level player was attempting the same kicks. Player salaries correlate only weakly with our measures of field goal kicking success. We find that those kickers selected to the Pro Bowl and All-Pro teams were rather mediocre by our metrics, over the seasons studied. The relative difficulty of kicking in various stadiums is also considered. Finally, we discuss the degree to which field goal kicking is a skill that can be maintained over multiple seasons.

Suggested Citation

  • Pasteur R. Drew & Cunningham-Rhoads Kyle, 2014. "An expectation-based metric for NFL field goal kickers," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 10(1), pages 49-66, January.
    • Handle: RePEc:bpj:jqsprt:v:10:y:2014:i:1:p:49-66:n:1
    DOI: 10.1515/jqas-2013-0039
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    References listed on IDEAS

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    1. David Romer, 2006. "Do Firms Maximize? Evidence from Professional Football," Journal of Political Economy, University of Chicago Press, vol. 114(2), pages 340-365, April.
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    Cited by:

    1. Michael William Gmeiner, 2019. "History-Dependent Mixed Strategies: Evidence From Major League Baseball," Journal of Sports Economics, , vol. 20(3), pages 371-398, April.
    2. Yurko Ronald & Ventura Samuel & Horowitz Maksim, 2019. "nflWAR: a reproducible method for offensive player evaluation in football," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 15(3), pages 163-183, September.

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