title: The expected value of possession in professional rugby league match-play.
abstract: This study estimated the expected point value for starting possessions in different field locations during rugby league match-play and calculated the mean expected points for each subsequent play during the possession. It also examined the origin of tries scored according to the method of gaining possession. Play-by-play data were taken from all 768 regular-season National Rugby League (NRL) matches during 2010-2013. A probabilistic model estimated the expected point outcome based on the net difference in points scored by a team in possession in a given situation. An iterative method was used to approximate the value of each situation based on actual scoring outcomes. Possessions commencing close to the opposition's goal-line had the highest expected point equity, which decreased as the location of the possession moved towards the team's own goal-line. Possessions following an opposition error, penalty or goal-line dropout had the highest likelihood of a try being scored on the set subsequent to their occurrence. In contrast, possessions that follow an opposition completed set or a restart were least likely to result in a try. The expected point values framework from our model has applications for informing playing strategy and assessing individual and team performance in professional rugby league.
authors.affiliation: a Sport & Exercise Discipline Group, Faculty of Health , University of Technology (UTS) , Sydney , Australia.|b Panthers Rugby League Football Club , Sydney , Australia.
authors.forename: Thomas
authors.initials: T
authors.lastname: Kempton
authors.affiliation: a Sport & Exercise Discipline Group, Faculty of Health , University of Technology (UTS) , Sydney , Australia.
authors.forename: Nicholas
authors.initials: N
authors.lastname: Kennedy
authors.affiliation: a Sport & Exercise Discipline Group, Faculty of Health , University of Technology (UTS) , Sydney , Australia.
authors.forename: Aaron J
authors.initials: AJ
authors.lastname: Coutts
mesh_terms: D054874:Athletic Performance / Q000502:physiology*; D001315:Australia; D003163:Competitive Behavior / Q000502:physiology*; D005538:Football / Q000502:physiology*; D006801:Humans; D008297:Male; D015233:Models, Statistical; D013647:Task Performance and Analysis
keywords: Team sport; analytics; performance analysis; tactics