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Assigning goal-probability value to high intensity runs in football

Author

Listed:
  • Sam Gregory
  • Sam Robertson
  • Robert Aughey
  • Bartholomew Spencer
  • Jeremy Alexander

Abstract

High intensity run counts—defined as the number of runs where a player reaches and maintains a speed above a certain threshold—are a popular football running statistic in sport science research. While the high intensity run number gives an insight into the volume or intensity of a player’s work rate it does not give any indication about the effectiveness of their runs or whether or not they provided value to the team. To provide the missing context of value this research borrows the concept of value models from sports analytics which assign continuous values to each frame of optical tracking data. In this research the value model takes the form of goal-probability for the in-possession team. By aligning the value model with high intensity runs this research identifies positive correlations between speed and acceleration with high value runs, as well as a negative correlation between tortuosity (a measure of path curvature) and high value runs. There is also a correlation between the number of players making high intensity runs concurrently and the value generated by the team, suggesting a form of movement coordination. Finally positional differences are explored demonstrating that attacking players make more in-possession high intensity runs when goal probability is high, whereas defensive players make more out-of-possession high intensity runs while goal probability is high. By assigning value to high-intensity runs practitioners are able to add new layers of context to traditional sport science metrics and answer more nuanced questions.

Suggested Citation

  • Sam Gregory & Sam Robertson & Robert Aughey & Bartholomew Spencer & Jeremy Alexander, 2024. "Assigning goal-probability value to high intensity runs in football," PLOS ONE, Public Library of Science, vol. 19(9), pages 1-27, September.
  • Handle: RePEc:plo:pone00:0308749
    DOI: 10.1371/journal.pone.0308749
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    References listed on IDEAS

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    1. Marcelino, Rui & Sampaio, Jaime & Amichay, Guy & Gonçalves, Bruno & Couzin, Iain D. & Nagy, Máté, 2020. "Collective movement analysis reveals coordination tactics of team players in football matches," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    2. Toni Modric & Sime Versic & Damir Sekulic & Silvester Liposek, 2019. "Analysis of the Association between Running Performance and Game Performance Indicators in Professional Soccer Players," IJERPH, MDPI, vol. 16(20), pages 1-13, October.
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