It’s widely understood that the best way to make money when betting is to make more informed selections than the bookmaker or the majority of other bettors.
For boxing betting, that means overcoming traders who have over a hundred years of historical analysis to wade through, along with the balancing factor of a large volume of bettors in the market.
In MMA betting, however, there are far fewer historical outcomes or statistics to investigate. This means that informed bettors have access to roughly the same data as the bookmaker. If these statistics are used more effectively than the traders, your MMA betting will yield better results.
And because there isn’t a culture of data tracking in MMA associations, statistical players will also have an advantage over other MMA bettors who are helping shape the markets.
Using statistics for MMA betting
One of the best – and underused – resources for MMA statistics is hosteddb.fightmetric.com, which tracks a whole range of fighter statistics, including:
- Significant Strikes Landed per Minute
- Striking Accuracy (% of strikes landed)
- Significant Strikes Absorbed per minute
- Striking Defense
- Takedown Average
- Takedown Accuracy
- Takedown Defense
- Submissions Average
It also includes a match-by-match analysis of strikes landed, takedowns, submissions attempted and passes.
This information is incredibly useful in determining not just the outcome of the fight, but how the action will unfold. For example, if Fighter A has a high takedown average and Fighter B has very poor takedown defence it’s clear that the former will be looking to – and probably will – score some takedowns over his rival.
Going one stage further, however, we could notice that Fighter A‘s submission defense is terrible – compared with Fighter B’s impressive submission average. If that’s the case, Fighter A will likely change his game plan to avoid high-submission scenarios (such as fighting on the mat), and therefore try something else.
But what? Will he rely on striking? From here, having knowledge of the history of MMA is key.
Analysing match outcomes will provide invaluable data for creating a predictive model. For example, while it’s obvious fighters with an increased reach have a striking advantage, does this benefit overrule another fighter’s striking accuracy? And how greatly does a fighter’s Conclusions from this type of analysis can be generated, and compared with fighters’ statistics into a predictive model that would have a great chance at exploiting incorrectly priced odds.
It’s also important to note that within MMA there are varing levels of competition, with UFC, Strikeforce, Bellator and the women’s MMA presenting varying levels degrees of data. In MMA – as with other sports – the further you move towards the fringe, the greater your edge can become over the bookmaker.