State Transition Modeling in Ultimate Frisbee: Adaptation of a Promising Method for Performance Analysis in Invasion Sports.

Front Psychol

Chair of Performance Analysis and Sports Informatics, Department of Sport and Health Sciences, Technical University of Munich, Munich, Germany.

Published: May 2021

Although the body of literature in sport science is growing rapidly, certain sports have yet to benefit from this increased interest by the scientific community. One such sport is Ultimate Frisbee, officially known as Ultimate. Thus, the goal of this study was to describe the nature of the sport by identifying differences between winning and losing teams in elite-level competition. To do so, a customized observational system and a state transition model were developed and applied to 14 games from the 2017 American Ultimate Disc League season. The results reveal that, on average, 262.2 passes were completed by a team per game and 5.5 passes per possession. More than two-thirds of these passes were played from the mid zone (39.4 ± 6.57%) and the rear zone (35.2 ± 5.09%), nearest the team's own end zone. Winning and losing teams do not differ in these general patterns, but winning teams played significantly fewer backward passes from the front zone to the mid zone, nearest the opponent's end zone than losing teams (mean difference of -4.73%, = -4.980, < 0.001, = -1.16). Furthermore, losing teams scored fewer points when they started on defense, called breakpoints (mean difference of -5.57, = -6.365, < 0.001, = 2.30), and committed significantly more turnovers per game (mean difference of 5.64, = 5.85, < 0.001, = -1.18). Overall, this study provides the first empirical description of Ultimate and identifies relevant performance indicators to discriminate between winning and losing teams. We hope this article sheds light on the unique, but so far overlooked sport of Ultimate, and offers performance analysts the basis for future studies using state transition modeling in Ultimate as well as other invasion sports.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8185146PMC
http://dx.doi.org/10.3389/fpsyg.2021.664511DOI Listing

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