![]() Although efforts to automatically detect events from video 8 or positional data 9 are undertaken, the most reliable and most widely used approach remains to be manual annotation by expert video analysts, supported by human and computer-based quality control 10– 12. ![]() Event data provides a detailed and ordered sequence of all the player’s actions during the match, such as passes, shots, or tackles 7. The present paper presents a framework for a joint evaluation of both aspects, as well as empirical evidence on the usability of in-play information for forecasting purposes.Įvent data and positional data from football matches aim at capturing all events and movements on the pitch and are comprehensively studied in sports science 5, 6. However, until now, event and positional data have surprisingly not been used in the context of in-play forecasting models in football. ![]() Moreover, the framework presented in the present study has methodological implications for performance analysis in football, as it suggests that researchers should increasingly segment matches by scoreline and control carefully for general team strength.įorecasting of results 1, 2 and performance analysis using event and positional data 3, 4 are two highly relevant and highly topical strands of research with regard to data-driven analysis in the game of football. The present results are relevant to match analysts and bookmakers who should not overestimate the value of in-play information when explaining match performance or compiling in-play betting odds. Performance indicators based on event and positional data have been shown to possess more informative value than goals, but still are not sufficient to reveal significant predictive value in-play. Results suggest that surprisingly goals do not possess any relevant informative value on the further course of a match, if controlling for pre-game market expectation by means of betting odds. Moreover, goals from more than 30,000 additional matches have been analysed. Event and positional data from 50 matches, including more than 300 million datapoints were used to extract a total of 18 performance indicators. Two highly relevant aspects of football, namely forecasting of results and performance analysis by means of performance indicators, are combined in the present study by analysing the value of in-play information in terms of event and positional data in forecasting the further course of football matches.
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