Determining spatio-temporal metrics that distinguish play outcomes in field hockey

Abstract

Determining spatio-temporal metrics that distinguish play outcomes in field hockey Ciarán McInerney A thesis submitted in partial fulfilment of the requirements of Sheffield Hallam University for the degree of Doctor of Philosophy

The influence of possession status on the physical output of male international hockey players

“…This is emphasized by the findings of McInerney et al. 52 who reported that in attacking phases, “39% of circle entries occurred when the possessing player was within 15 m of the goal line with more opponents than teammates in his or her region, at the moment of the outcome” and that a smaller distance between the teams leftmost and rightmost player increased the chance of a circle entry.…”

“…Physical output was relatively similar across match results for both ‘in possession’ and ‘not in possession’ instances. This may be due to the relatively short periods of possession within hockey (Table 3) and that other factors such as player spacing 52 and technical ability may play a larger role in match outcome. In contrast, a clear pattern exists in the Australian Football League – a physically demanding, contact based sport with similar relative physical output to hockey.…”

Field hockey from the performance analyst’s perspective: A systematic review

“…The backward dropping algorithm is a genomic selection method that reduces a large number of variables into a smaller subset that best distinguishes a trait. 30 This method was applied to the analysis of a small sample of games in hockey as it has the advantage of not needing a large number of observations (games) to build the model. 30 This can be an issue in hockey when there is limited international tournaments occurring and consequently limited information available per team.…”

“…30 This method was applied to the analysis of a small sample of games in hockey as it has the advantage of not needing a large number of observations (games) to build the model. 30 This can be an issue in hockey when there is limited international tournaments occurring and consequently limited information available per team. The aim was to identify relationships between spatio-temporal metrics and positive and negative outcomes of play.…”

“…Over 3600 metrics were evaluated, however only passing execution and proximity to goal were able to distinguish between plays ending in a circle entry and those resulting in a turnover. 30 Studying and applying alternative data analysis methods, such as the backward dropping algorithm, will provide new perspectives to analysing strategies and tactics in sport.…”