Sep 11 2008

A Theoretical Model for The Probability of Winning a Basketball Game – Part 2

Tweet This is the second in a 3 part series where I will present a theoretical model for the probability of winning a basketball game. The 3 parts will break this model down at the team, unit, and player level. In part one of this series I presented a way to break down the probability […]

Sep 5 2008

A Theoretical Model for The Probability of Winning a Basketball Game – Part 1

Tweet This is the first in a 3 part series where I will present a theoretical model for the probability of winning a basketball game. The 3 parts will break this model down at the team, unit, and player level. Before diving right into the data and trying to build new models of the game, […]

Aug 30 2008

Tracking the 2008 NBA Playoffs: What the Data Represents

Tweet In my post where I detail my data collection goals for the 2008 NBA playoffs, I spell out the sort of data that I’m tracking and adding to the play-by-play. This post will expand on that and describe exactly what you’ll see in the data. First, a quick reminder of the four types of […]

Aug 22 2008

Analytics is the End Game

Tweet Analytics, at the end of the day, is … going to be the end game. – MC Hammer The quote above is taken from this video, where MC Hammer lays it all out in the open about analytics. If you just replace the music references with those from the basketball world, then you end […]

Aug 21 2008

Data Pet Peeve #2: Offensive Rebounds & In-Air Shots

Tweet It didn’t take long for me to find my 2nd data pet peeve. This pet peeve is related to the first data pet peeve in that it involves rebounds and play-by-play ordering. This peeve is because offensive rebounds are credited after in-air shots. This makes me sad. An Example With 7:54 left in the […]

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