TACTICAL ANALYSIS MODELING THROUGH DATA MINING - Pattern Discovery in Racket Sports

We explore pattern discovery within the game of tennis. To this end, we formalize events in a match, and define similarities for events and event sequences. We then proceed by looking at unbalancing events and their immediate prequel (using pattern masks) and sequel (using nondeterministic finite automata). Structured in this way, the data can be effectively mined, and a similar approach might also be applied to more general areas. We show that data mining is able to find interesting patterns in real-world data from tennis matches.