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Related Experiment Video

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An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field

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In-play forecasting in football using event and positional data.

Maximilian Klemp¹, Fabian Wunderlich², Daniel Memmert²

¹Institute of Training and Computer Science in Sport, German Sport University Cologne, Am Sportpark Müngersdorf 6, 50933, Cologne, Germany. m.klemp@dshs-koeln.de.

Scientific Reports

|December 18, 2021

Summary

Goals in football matches surprisingly offer little predictive power for future outcomes when considering pre-game betting odds. Performance indicators from event and positional data show more value but lack significant in-play predictive power.

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Area of Science:

Sports Analytics
Football Performance Analysis
Predictive Modeling in Sports

Background:

Forecasting football results and analyzing team performance are crucial for analysts and bookmakers.
In-play data, including event and positional information, is increasingly utilized for match insights.

Purpose of the Study:

To evaluate the informative value of in-play data (event and positional) for forecasting football match outcomes.
To compare the predictive power of goals versus performance indicators derived from in-play data.

Main Methods:

Analysis of event and positional data from 50 football matches (over 300 million data points).
Extraction of 18 performance indicators from the collected data.
Analysis of goals from over 30,000 additional matches, controlling for pre-game betting odds.

Main Results:

Goals showed no significant informative value in predicting match progression when controlling for pre-game expectations (betting odds).
Performance indicators derived from event and positional data were more informative than goals.
In-play performance indicators, however, did not demonstrate sufficient predictive value on their own.

Conclusions:

Bookmakers and analysts should exercise caution in overestimating the predictive value of in-play information.
The study highlights methodological implications for football performance analysis, emphasizing scoreline segmentation and controlling for team strength.