Below is an excerpt of quantitative analysis performed for this year's tennis U.S. Open, picked up by the New York Times. The piece is entitled, "Using the Monte Carlo Method in Tennis" and is by Carlton Chin, a portfolio strategist and fund manager, and Rose Wang, head of finance for a health care non-profit.
A Monte Carlo analysis uses a random process to assess a complicated problem. In the financial world, Monte Carlo methods can help study the risk of investment strategies or to evaluate derivatives. Sporting events can also show the power of Monte Carlo simulations because sports can be broken down into specific events like an at-bat in baseball, or a possession in football or basketball.
Tennis can be deconstructed into actions like holding serve and breaking serve. The game can be broken down further by analyzing statistics like first-serve percentage and the percentage of points won on first serve or second serve.***
1. Serena Williams (1) 62.3%
2. Victoria Azarenka (2) 16.2%
3. Li Na (5) 10.8%
4. Roberta Vinci (10) 6.4%
5. Ana Ivanovic (13) 1.6%
6. Ekaterina Makarova (24) 1.2%
7. Carla Suarez Navarro (18) 0.8%
8. Flavia Pennetta 0.5%
9. Daniela Hantuchova 0.2%
The piece has Serena Williams as a favorite to win another Grand Slam, and is an official quant fact prediction for the book's blog.
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