Quick Post on MLB Probabilities (100k Monte Carlo Simulations)

I just did a quick run of 100,000 playoff simulations and wanted to share the quick results. I will try to get some finer detail or maybe look into a few changes, but here are the raw World Series champion results. Detroit — 4950 Baltimore — 18592 LA Angels — 31876 Kansas City — 9058 Washington — 19768 San Francisco — 4246 St. Louis — 1662 LA Dodgers — 9848 ...

October 1, 2014 · 1 min · sixmanguru

Oakland, Pittsburgh slight favorites in Wild Card probabilities

With the MLB Playoffs beginning this evening, I figured it was time to test my rankings and pull out the old probability calculator. I created the MLB Ratings based on a simple least squares NLP Optimization that I have discussed before. Oakland at Kansas City The Royals are in the playoffs for the first time in ages and they get to host a game. Unfortunately, they didn’t seem to have a home field advantage during the regular season, so I am not sure how much this helps (although in reality we can assume it does, at least a little). The numbers say the A’s are the better team by almost 0.7 of a run (per game, for the season). I show them as a 63.5% favorite. ...

September 30, 2014 · 2 min · sixmanguru

Generic Sports Series Probability Calculator

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. ...

September 16, 2014 · 3 min · sixmanguru