We noticed this article on Monte Carlo analysis and our work on sports analytics.
- See more at: http://decision-analytics-blog.lumina.com/monte-carlo-simulations/monte-carlo-analysis-goes-mainstream-with-womens-tennis/#sthash.ybtt9TZe.dpuf
You know something has entered the realms of popular culture when everybody speaks about it in the same breath as Hollywood blockbusters, their tax bills or smartphones. Well, OK… Monte Carlo analysis hasn’t quite made it that far, but it has cropped up in connection with women’s tennis championships, and a number of other sports as well. Carlton J. Chin (portfolio strategist and fund manager when he’s not analyzing sports events) applied Monte Carlo analysis to forecast the results of the 2013 US Open Tennis and the Women’s Singles in particular. So what were his predictions – and, more to the point, was he right?
The Method Behind the Monte Carlo Madness
Chin asserts that sports are often good candidates for Monte Carlo Analysis because they are marked by specific events: in tennis, such events are, for instance, holding or breaking serve. He used the ability of certain players to hold or break serve drawing on statistics from the rest of the year. Then he used a Monte Carlo analysis in a simulation of thousands of games between these players. His forecasts were that Serena Williams had a 62.3 per cent chance of winning, followed by Victoria Azarenka (16.2 per cent) and Li Na (10.8 per cent). In general, his predictions held good, barring some US Open position upsets like Flavia Pennetta (0.5 per cent) beating her fellow Italian Robert Vinci (6.4 per cent) in the quarter finals.