5 Conclusion

At its core, Pitch Control model provides a quantitative framework using tracking data to assess player movement, spatial control, and decision making on the football field. Based on such a framework, we introduced the concept of Offside Control to analyze the performance of players with respect to the danger created behind the offside line of the opposing team.

The introduction of the OC parameter, derived from the modification of the Potential Pitch Control Field methodology, has provided a framework for studying the dynamics of pitch control beyond the offside line. By identifying attacking players within permissible boundaries and calculating the OC metric, this study has characterized the effectiveness of teams or individual players in exerting control beyond the offside line.

The results demonstrated the practical application of OC in various dimensions, from spatial distribution to temporal dynamics during matches. We also effectively characterized the distinction between effective and ineffective offside control, delineating between real surface control and ineffective control.

Furthermore, the versatility of OC was highlighted by its applicability at both the team and player levels. From tracking team-level OC performance over multiple matches to characterizing individual player behavior, OC emerged as a multifaceted metric capable of capturing diverse aspects of football.

The findings further underscored the potential utility of OC in assessing player efficiency and effectiveness near the offside line. The relationship between Offside Time Efficiency Ratio (OTER) and Offside Control Efficiency Ratio (OCER) provided insight into the interplay between player positioning and the generation of effective offside control. While a positive correlation between OTER and OCER was observed, the analysis also suggested the influence of additional variables, suggesting that the OC framework should be refined to capture such external influence.

Further work to develop this metric would include consideration of external factors, as well as improvements in tracking data collection and pitch control models. One of the major drawbacks of this methodology is that it cannot be performed in real-time during the game, due to the lack of real-time tracking data and the computational cost of calculating a Potential Pitch Control Surface.

We think that the development of both computer vision and the Pitch Control methodology will enable real-time analysis using tracking data, which is currently not possible. This will revolutionize data analysis in football, as all metrics and analyses previously defined in the literature for tracking data could be performed in real time, allowing for a broader understanding and control of football.

Overall, our study contributes to the ongoing discourse on tactical analysis in football by introducing a novel metric that enriches our understanding of the dynamics of the offside play. By revealing the intricacies of offside control and its implications for team and player performance, this research lays the groundwork for future investigations aimed at improving strategic insight and decision-making in football.