  Mixed martial arts (MMA) has been one of the fastest-growing sports in recent
years and has become a mainstream sport on the global stage. The growth of MMA
has been driven by the Ultimate Fighting Championship (UFC), which is currently
the largest MMA promotion organization in the world. However, data collection
and statistical modeling in MMA are still in their infancy. We developed
FightTracker, a data-driven solution that delivers real-time predictions for
UFC fights. We first conducted regression analyses on the data provided by the
UFC and MMA Decisions and built two predictive models of UFC fight outcomes.
One model predicts the judges' majority score by round while the other predicts
whether the red fighter will win the fight or not in 3-round fights that go
beyond the second round (53% of all UFC fights). Both models use in-round fight
statistics as explanatory variables and achieve 80% accuracy. We then designed
an R shiny app that delivers these two predictions in real-time based on the
ESPN live data. This information is valuable for fans, coaches, athletes, and
especially bettors. Indeed, a live betting strategy based on FightTracker
proved to generate large profits over an 8-week period against the bookmaker
Unibet (90.17% ROI).
