In terms of model accuracy, April was a decent month for The Fight Predictor. Over the 22 fights predicted, our prediction record was 13-9 and we made a profit at 3/4 events. Unfortunately, UFC on Fuel TV: Mousasi vs Latifi went terribly as we were wrong on all 4 fights and all 4 bets. We spent the rest of the month trying to scrape back the money we had lost, but came out just negative on the month. 13 out of 22 fights won puts us at an accuracy of around 60%. Our tests on historical data show we should be hitting close to 80% accuracy. Therefore, since we have added significant amounts of data since our last model update (Prior to UFC 157 in February) we decided it’s time for another update.
One thing that we felt was important to consider is the differences between weight classes. For example, we have seen that takedown accuracy is an extremely important variable in determining who is going to win a fight. By splitting it up into weight classes and holding all other variables constant, our results show that in heavier weight classes (above lightweight), each 1% increase in takedown accuracy increases a fighters chance of winning by 0.1%. In the lighter weight classes, each 1% increase in takedown accuracy increases a fighters chance of winning by 0.4%. Our analysis shows other differences between the lighter and heavier weight classes as well as specific relationships in certain weight classes. For example, both heavyweight and middleweight have unique height explanatory variables.
Another couple variables that have become significant in this model, but weren’t before are “is the fighter a southpaw?” and “is the fighter fighting in their home country?” What we see from these variables is that a left handed fighter fighting a right handed fighter is 5% more likely to win. Fighting in your home country, on the other hand, actually makes a fighter 8% less likely to win. This is likely due to the complacency that comes with being around friends and family. Frank Mir spoke before his fight vs Daniel Cormier about how leaving home really allowed to train to what he felt was his maximum potential.
We tested our model by going back in time and removing observations. Then we recalculate the model to see whether its predictions are accurate to what actually happened in the fight. Over 10,000 observations, here is our output:
Total Correctness: 78.71%
This can be compared to our calculations in our article on parlays back in February. It is worth noting however, that even though our accuracy dropped slightly overall, the additional fights in our data should help with our future accuracy.
It is also interesting to note that in our Georges St Pierre vs Anderson Silva super fight article the model had Georges St Pierre as the heavy favourite to defeat “The Spider.” With our new model however, the output is 50.07% for St Pierre. That means this fight is basically as close as it could possibly get and adds more intrigue to the potential match-up.
Next event is UFC on FX: Belfort vs Rockhold coming up in 3 weeks on May 18. We will have our early picks for that event as well as our prediction of the main event of UFC 160: Silva vs Velasquez, coming in the next week or so.