Bigger data, better questions, and a return to fourth down behavior: an introduction to a special issue on tracking datain the National football League
Lopez Michael J. ()
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Lopez Michael J.: National Football League and Skidmore College, New York, NY, USA
Journal of Quantitative Analysis in Sports, 2020, vol. 16, issue 2, 73-79
Abstract:
Most historical National Football League (NFL) analysis, both mainstream and academic, has relied on public, play-level data to generate team and player comparisons. Given the number of oft omitted variables that impact on-field results, such as play call, game situation, and opponent strength, findings tend to be more anecdotal than actionable. With the release of player tracking data, however, analysts can better ask and answer questions to isolate skill and strategy. In this article, we highlight the limitations of traditional analyses, and use a decades-old punching bag for analysts, fourth-down strategy, as a microcosm for why tracking data is needed. Specifically, we assert that, in absence of using the precise yardage needed for a first down, past findings supporting an aggressive fourth down strategy may have been overstated. Next, we synthesize recent work that comprises this special Journal of Quantitative Analysis in Sports issue into player tracking data in football. Finally, we conclude with some best practices and limitations regarding usage of this data. The release of player tracking data marks a transition for the league and its’ analysts, and we hope this issue helps guide innovation in football analytics for years to come.
Keywords: causal inference; fourth downs; National Football League; player tracking (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (3)
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DOI: 10.1515/jqas-2020-0057
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