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Performance profiles of football teams in the UEFA Champions League considering situational efficiency

Author

Listed:
  • Hongyou Liu
  • Qing Yi
  • Jesús-Vicente Giménez
  • Miguel-Angel Gómez
  • Carlos Lago-Peñas

Abstract

Performance of football teams varies constantly due to the dynamic nature of this sport, whilst the typical performance and its spread can be represented by profiles combining different performance-related variables based on data from multiple matches. The current study aims to use a profiling technique to evaluate and compare match performance of football teams in the UEFA Champions League incorporating three situational variables (i.e. strength of team and opponent, match outcome and match location). Match statistics of 72 teams, 496 games across four seasons (2008-09 to 2012-13) of this competition were analysed. Sixteen performance-related events were included: shots, shots on target, shots from open play, shots from set piece, shots from counter attack, passes, pass accuracy (%), crosses, through balls, corners, dribbles, possession, aerial success (%), fouls, tackles, and yellow cards. Teams were classified into three levels of strength by a k-cluster analysis. Profiles of overall performance and profiles incorporating three situational variables for teams of all three levels of strength were set up by presenting the mean, standard deviation, median, lower and upper quartiles of the counts of each event to represent their typical performances and spreads. Means were compared by using one-way ANOVA and independent sample t test (for match location, home and away differences), and were plotted into the same radar charts after unifying all the event counts by standardised score. Established profiles can present straightforwardly typical performances of football teams of different levels playing in different situations, which could provide detailed references for coaches and analysts to evaluate performances of upcoming opposition and of their own.

Suggested Citation

  • Hongyou Liu & Qing Yi & Jesús-Vicente Giménez & Miguel-Angel Gómez & Carlos Lago-Peñas, 2015. "Performance profiles of football teams in the UEFA Champions League considering situational efficiency," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 15(1), pages 371-390, March.
  • Handle: RePEc:taf:rpanxx:v:15:y:2015:i:1:p:371-390
    DOI: 10.1080/24748668.2015.11868799
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    Citations

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    Cited by:

    1. Fabíola Zambom-Ferraresi & Belén Iráizoz & Fernando Lera-López, 2019. "Are football managers as efficient as coaches? Performance analysis with and inputs in the Premier league," Applied Economics, Taylor & Francis Journals, vol. 51(3), pages 303-314, January.
    2. Toni Modric & Sime Versic & Damir Sekulic & Silvester Liposek, 2019. "Analysis of the Association between Running Performance and Game Performance Indicators in Professional Soccer Players," IJERPH, MDPI, vol. 16(20), pages 1-13, October.
    3. Julen Castellano & Miguel Pic, 2019. "Identification and Preference of Game Styles in LaLiga Associated with Match Outcomes," IJERPH, MDPI, vol. 16(24), pages 1-13, December.
    4. Rubén Maneiro & José Luís Losada & Mariona Portell & Antonio Ardá, 2021. "Observational Analysis of Corner Kicks in High-Level Football: A Mixed Methods Study," Sustainability, MDPI, vol. 13(14), pages 1-19, July.
    5. Changjing Zhou & William G. Hopkins & Wanli Mao & Alberto L. Calvo & Hongyou Liu, 2019. "Match Performance of Soccer Teams in the Chinese Super League—Effects of Situational and Environmental Factors," IJERPH, MDPI, vol. 16(21), pages 1-13, November.
    6. Qing Yi & Miguel-Ángel Gómez-Ruano & Hongyou Liu & Shaoliang Zhang & Binghong Gao & Fabian Wunderlich & Daniel Memmert, 2020. "Evaluation of the Technical Performance of Football Players in the UEFA Champions League," IJERPH, MDPI, vol. 17(2), pages 1-12, January.

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