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Fractional Tackles: Leveraging Player Tracking Data for Within-Play Tackling Evaluation in American Football (2403.14769v2)

Published 21 Mar 2024 in stat.AP

Abstract: Tackling is a fundamental defensive move in American football, with the main purpose of stopping the forward motion of the ball-carrier. However, current tackling metrics are manually recorded outcomes that are inherently flawed due to their discrete and subjective nature. Using player tracking data, we present a novel framework for assessing tackling contribution in a continuous and objective manner. Our approach first identifies when a defender is in a ``contact window'' of the ball-carrier during a play, before assigning value to each window and the players involved. This enables us to devise a new metric called fractional tackles, which credits defenders for halting the ball-carrier's forward motion toward the end zone. We demonstrate that fractional tackles overcome the shortcomings of traditional metrics such as tackles and assists, by providing greater variation and measurable information for players lacking recorded statistics like defensive linemen. We view our contribution as a significant step forward in measuring defensive performance in American football and a clear demonstration of the capabilities of player tracking data.

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References (23)
  1. Big ideas in sports analytics and statistical tools for their investigation. WIREs Computational Statistics, 15(6).
  2. Burke, B. (2010). Tackle Factor. Advanced Football Analytics. [Accessed 14-Mar-2024].
  3. Burke, B. (2019). DeepQB: deep learning with player tracking to quantify quarterback decision-making & performance. In Proceedings of the 2019 MIT Sloan Sports Analytics Conference.
  4. Bursik, M. (2023). Enhancing Stale Tackling Metrics. StatsBomb.com. [Accessed 14-Mar-2024].
  5. nflfastR: Functions to Efficiently Access NFL Play by Play Data. R package version 4.5.1.
  6. Route identification in the National Football League: An application of model-based curve clustering using the EM algorithm. Journal of Quantitative Analysis in Sports, 16(2):121–132.
  7. Clark, K. (2012). The NFL’s Make-Believe Stat. The Wall Street Journal. [Accessed 14-Mar-2024].
  8. Expected hypothetical completion probability. Journal of Quantitative Analysis in Sports, 16(2):85–94.
  9. Unsupervised methods for identifying pass coverage among defensive backs with NFL player tracking data. Journal of Quantitative Analysis in Sports, 16(2):143–161.
  10. Meta-analytics: tools for understanding the statistical properties of sports metrics. Journal of Quantitative Analysis in Sports, 12(4).
  11. Jahnke, N. (2019). Defensive stops: A more comprehensive metric than tackles. PFF.com. [Accessed 14-Mar-2024].
  12. Kovalchik, S. A. (2023). Player Tracking Data in Sports. Annual Review of Statistics and Its Application, 10(1):677–697.
  13. NFL Big Data Bowl 2024.
  14. Lopez, M. J. (2020). Bigger data, better questions, and a return to fourth down behavior: an introduction to a special issue on tracking datain the National Football League. Journal of Quantitative Analysis in Sports, 16(2):73–79.
  15. McKnight, M. (2015). The farce of tackling: Why is such a fundamental stat so elusive? Sports Illustrated. [Accessed 14-Mar-2024].
  16. Mellor, C. (2019). PFF Signature Statistics – a glossary. PFF.com. [Accessed 14-Mar-2024].
  17. Monson, S. (2012). NFL Team Scorers Are the Most Important People in the League You Don’t Know. Bleacher Report. [Accessed 14-Mar-2024].
  18. NFL Football Operations (2023). 2023 NFL Rulebook. NFL.com. [Accessed 14-Mar-2024].
  19. NFL Football Operations (2024). NFL Next Gen Stats. NFL.com. [Accessed 14-Mar-2024].
  20. Here Comes the STRAIN: Analyzing Defensive Pass Rush in American Football with Player Tracking Data. The American Statistician, page 1–10.
  21. R Core Team (2024). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.
  22. Quarterback evaluation in the national football league using tracking data. AStA Advances in Statistical Analysis, 107:327–342.
  23. Going deep: models for continuous-time within-play valuation of game outcomes in American football with tracking data. Journal of Quantitative Analysis in Sports, 16(2):163–182.
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