Literature DB >> 26190577

Modelling relationships between match events and match outcome in elite football.

Hongyou Liu1,2, Will G Hopkins3, Miguel-Angel Gómez1.   

Abstract

Identifying match events that are related to match outcome is an important task in football match analysis. Here we have used generalised mixed linear modelling to determine relationships of 16 football match events and 1 contextual variable (game location: home/away) with the match outcome. Statistics of 320 close matches (goal difference ≤ 2) of season 2012-2013 in the Spanish First Division Professional Football League were analysed. Relationships were evaluated with magnitude-based inferences and were expressed as extra matches won or lost per 10 close matches for an increase of two within-team or between-team standard deviations (SD) of the match event (representing effects of changes in team values from match to match and of differences between average team values, respectively). There was a moderate positive within-team effect from shots on target (3.4 extra wins per 10 matches; 99% confidence limits ±1.0), and a small positive within-team effect from total shots (1.7 extra wins; ±1.0). Effects of most other match events were related to ball possession, which had a small negative within-team effect (1.2 extra losses; ±1.0) but a small positive between-team effect (1.7 extra wins; ±1.4). Game location showed a small positive within-team effect (1.9 extra wins; ±0.9). In analyses of nine combinations of team and opposition end-of-season rank (classified as high, medium, low), almost all between-team effects were unclear, while within-team effects varied depending on the strength of team and opposition. Some of these findings will be useful to coaches and performance analysts when planning training sessions and match tactics.

Keywords:  Notational analysis; performance indicators; situational variable; soccer

Mesh:

Year:  2015        PMID: 26190577     DOI: 10.1080/17461391.2015.1042527

Source DB:  PubMed          Journal:  Eur J Sport Sci        ISSN: 1536-7290            Impact factor:   4.050


  20 in total

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4.  Analysis of team success based on match technical and running performance in a professional soccer league.

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5.  Evolutionary Trends of Players' Technical Characteristics in the UEFA Champions League.

Authors:  Qing Yi; Hongyou Liu; George P Nassis; Miguel-Ángel Gómez
Journal:  Front Psychol       Date:  2020-06-16

6.  Performance profiles of professional female tennis players in grand slams.

Authors:  Yixiong Cui; Miguel-Ángel Gómez; Bruno Gonçalves; Jaime Sampaio
Journal:  PLoS One       Date:  2018-07-19       Impact factor: 3.240

7.  Physical responses of professional soccer players during 4 vs. 4 small-sided games with mini-goals according to rule changes.

Authors:  Jesús V Giménez; Hongyou Liu; Patrycja Lipińska; Andrzej Szwarc; Paweł Rompa; Miguel A Gómez
Journal:  Biol Sport       Date:  2017-10-12       Impact factor: 2.806

8.  Players' Physical Performance Decreased After Two-Thirds of the Season: Results of 3 Consecutive Seasons in the German First Bundesliga.

Authors:  Paweł Chmura; Marek Konefał; Del P Wong; Antonio J Figueiredo; Edward Kowalczuk; Andrzej Rokita; Jan Chmura; Marcin Andrzejewski
Journal:  Int J Environ Res Public Health       Date:  2019-06-10       Impact factor: 3.390

9.  What Frequency of Technical Activity Is Needed to Improve Results? New Approach to Analysis of Match Status in Professional Soccer.

Authors:  Marek Konefał; Paweł Chmura; Kacper Rybka; Jan Chmura; Maciej Huzarski; Marcin Andrzejewski
Journal:  Int J Environ Res Public Health       Date:  2019-06-25       Impact factor: 3.390

10.  Modeling the Keys to Team's Success in the Women's Chinese Basketball Association.

Authors:  Qing Yi; Shaoliang Zhang; Wenxuan Fang; Miguel-Ángel Gómez-Ruano
Journal:  Front Psychol       Date:  2021-06-04
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