I wrote an article that was published over at Nikita’s The Tennis Notebook. It dives into a cluster analysis I did using year-end ATP rankings since 1972. You can find the article here: https://medium.com/the-tennis-notebook/who-are-the-greatest-players-in-the-open-era-e7af7f627cc5#.snynwrfqe
Photo by Horia Varlan [CC 2.0] We talk about it all of the time – who is the greatest player of all-time? Is it the player who won the most Grand Slam titles, the player ranked number one for the most weeks or the person with the best record against the premier players of that era? Is it a combination of these three things or more? What factors are important when it comes to this discussion? ...
With the baseball playoffs upon us, I have decided to start building a simulator to determine series outcomes once they start. I decided to make this as generic as possible. This simulator is not specific to baseball or even to a particular series length. Obviously, the first parts to think about I addressed in my previous post relating to home field advantage, ratings and the probability a team would win a single game versus a specific opponent. ...
Today I was enamored with the FiveThirtyEight.com article, Inside the Shadowy World of High-Speed Tennis Betting. The article mentions the courtsiders who would sit court side at a tennis match and try to relay information quicker than the tournament computers to betting partners. Great read. Not sure these courtsiders were really doing anything illegal. Buried deep in the article was a mention of the system this one organization created to predict the outcome of tennis matches for betting purposes. It links to a website, Summer of Jeff, and a post, Python Code for Tennis Markov. If you follow the links to the gitHub site, there is some pretty elaborate Python code for generating probabilities based on Markov Chain theory. The code is pretty easy to use, if you understand Python and statistics, although it needs some cleaning up if you plan on using it for entire match prediction (hint: the matchProbs function needs some fixes to run). ...
It has been too, too long since I have posted anything on here. I have been active on twitter (@TXCollege10s) and keeping up with the season as it progresses, but have not had a whole lot of time to really repost all of the articles. I decided it was time to update the rankings program, so here we go. Please let me know where you see mistakes. NOTE: The records for each team indicate only matches against DI opponents. So please do not e-mail me that the record is wrong, unless you are certain that has been checked. ...