The Right Way to Synchronize Tracking and Event Data: Using Domain Knowledge to Optimize Algorithms

aluable new insights can be obtained by combining tracking and event data in soccer anal- ysis. However, how to synchronize the two data streams, is rarely discussed. Non systematic errors in the timestamps, and synchronizing with cost functions result in suboptimal synchro- nization, which hinders further analysis. Within this proceedings we will introduce a com- putationally optimized implementation of the Needleman-Wunch algorithm, by using domain knowledge about the game. The optimized version is over 70 times more efficient in terms of time constraints and memory usage. On top of that, we show that the properly synchronized approach translates back to practice with better performing xG models. Taken together, this im- plementation is a training-free, high-quality synchronization algorithm, with low computational cost that solves existing issues. On top of that, all data and code used for this proceedings is fully open-sourced and available in the DataBallPy package.