Spatio-temporal metrics that distinguish play outcomes: A pilot study

Authors

  • Ciarán McInerney Centre for Sports Engineering Research, Sheffield Hallam University, Sheffield, United Kingdom
  • Simon Goodwill Centre for Sports Engineering Research, Sheffield Hallam University, Sheffield, United Kingdom
  • Leon Foster Centre for Sports Engineering Research, Sheffield Hallam University, Sheffield, United Kingdom
  • Simon Choppin Centre for Sports Engineering Research, Sheffield Hallam University, Sheffield, United Kingdom

DOI:

https://doi.org/10.14198/jhse.2017.12.Proc2.03

Keywords:

TEAM INVASION SPORTS, VARIABLE-SELECTION, MARGINAL EFFECTS

Abstract

In team invasion sports, tactical behaviour can be examined using spatio-temporal data, i.e. the position of the players at a given time. A review of the spatio-temporal metrics used in team invasion sports performance analysis indicated that thousands of variations of metrics being used. Information about the distribution of metrics' individual effects can inform us of the best variable-selection method. The aim of this pilot study was to estimate the distribution of strong marginal effects of spatio-temporal metrics of field hockey plays. With institutional ethical approval, the Womens’ and Mens’ gold medal games from the EuroHockey 2015 field hockey tournament were recorded. Best, acceptable and worst-case outcomes for plays were described by 1,837 spatio-temporal metrics. Each metric's marginal effects were estimated using Cramér's V, Mutual Information and the I-score. Values for Cramér's V of 0.2 and 0.4 to mark the boundaries of small, moderate and large effects. Less than 1% of metrics show large effects with > 87% of all metrics showing small effects as per the Cramér's V thresholds. These large effect metrics where all within the 98th percentile of Mutual Information values and within the 96th percentile of the I-score values, which supports the Cramér's V distribution of marginal effects. Therefore, according to the recommendations of Tibshirani (1996), univariate variable-selection methods will be the most appropriate for selecting important metrics.

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Statistics

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Published

2017-08-29

How to Cite

McInerney, C., Goodwill, S., Foster, L., & Choppin, S. (2017). Spatio-temporal metrics that distinguish play outcomes: A pilot study. Journal of Human Sport and Exercise, 12(2proc), S502-S507. https://doi.org/10.14198/jhse.2017.12.Proc2.03