<abstract xmlns="http://www.w3.org/1999/xhtml">

In the past 20 years, performance analysis in soccer has accumulated a wide variety of key performance indicators (KPI’s) aimed at reflecting a team’s strength and success. Thanks to rapidly advancing technologies and data analytics more sophisticated metrics, requiring high resolution data acquisition and big data methods, are developed. This includes many position-data-based KPI’s, which incorporate precise spatial and temporal information about every player and the ball on the field.
The present study contributes to this research by performing a large-scale comparison of several metrics mainly based on player positions and passing events. Their association with team’s success (derived from goals scored) and team’s strength (estimated from pre-game betting odds) is analysed.
The systematic analysis revealed relevant results for further KPI research: First, the magnitude of overall correlation coefficients was higher for relative metrics than for absolute metrics. Second, the correlation of metrics with the strength of a team is stronger than the correlation with the game success of a team. Third, correlation analysis with team strength indicated more positive associations, while correlation analysis with success is most likely confounded by the intermediate score line of a game and revealed more negative associations.
</abstract>

In the past 20 years, performance analysis in soccer has accumulated a wide variety of key performance indicators (KPI’s) aimed at reflecting a team’s strength and success. Thanks to rapidly advancing technologies and data analytics more sophisticated metrics, requiring high resolution data acquisition and big data methods, are developed. This includes many position-data-based KPI’s, which incorporate precise spatial and temporal information about every player and the ball on the field.
The present study contributes to this research by performing a large-scale comparison of several metrics mainly based on player positions and passing events. Their association with team’s success (derived from goals scored) and team’s strength (estimated from pre-game betting odds) is analysed.
The systematic analysis revealed relevant results for further KPI research: First, the magnitude of overall correlation coefficients was higher for relative metrics than for absolute metrics. Second, the correlation of metrics with the strength of a team is stronger than the correlation with the game success of a team. Third, correlation analysis with team strength indicated more positive associations, while correlation analysis with success is most likely confounded by the intermediate score line of a game and revealed more negative associations.

Systematic Analysis of Position-Data-based Key Performance Indicators

German Sport University Cologne Am Sportpark

International Journal of Computer Science in Sport

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Systematic Analysis of Position-Data-based Key Performance Indicators"}

In the past 20 years, performance analysis in soccer has accumulated a wide variety of key performance indicators (KPI’s) aimed at reflecting a team’s strength...

Systematic Analysis of Position-Data-based Key Performance Indicators

Online veröffentlicht: 16. Juni 2023

Seitenbereich: 80 - 101

DOI: https://doi.org/10.2478/ijcss-2023-0006

Schlüsselwörter
POSITIONAL DATA, EVENT DATA, KEY PERFORMANCE INDICATORS, SOCCER, MATCH ANALYSIS

© 2023 Justus Schlenger et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Systematic Analysis of Position-Data-based Key Performance Indicators

Online veröffentlicht: 16. Juni 2023

Seitenbereich: 80 - 101

DOI: https://doi.org/10.2478/ijcss-2023-0006

SchlüsselwörterPOSITIONAL DATA, EVENT DATA, KEY PERFORMANCE INDICATORS, SOCCER, MATCH ANALYSIS

© 2023 Justus Schlenger et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
POSITIONAL DATA, EVENT DATA, KEY PERFORMANCE INDICATORS, SOCCER, MATCH ANALYSIS