Learn sports analytics using probability, statistics and machine learning
This is our fourth post about home court advantage in the NBA. If the home team has a higher win probability, that advantage should be evident in at least some of the box score statistics. Home court advantage could result from better offense, better defense, or a mix of the two.
In this post, we’ll examine how basic box score statistics vary between home and away games.
Continue reading “Which Box Score Stats Contribute to Home Court Advantage?”
This post looks at whether particular NBA teams have demonstrated significantly different amounts of home court advantage over time. This is challenging, since team quality varies significantly over time.
The punchline? There is only very weak statistical evidence that teams have persistent and measurable differences in home court advantage relative to the league average.
Continue reading “Do NBA Teams Have Different Home Court Advantages?”
In this post, we are going to take another look at scraping NBA team information from Wikipedia. We will also see how generate a map of NBA arena locations.
Continue reading “Scraping NBA team information from Wikipedia (Revisited)”
In our our previous post about NBA home court advantage, we saw that home court win percentages varied over the past 21 seasons, but have averaged around 60%.
In this short post, we’ll try to drill a little deeper into the distribution of home court win percentages.
Continue reading “A Deeper Look at NBA Home Court Win Percentages”
Data is central to any analytics project. In Python, by far the most commonly-used package to manage data is pandas. In this short post, I will offer a few suggestions for those of you who want to get up to speed using pandas or take your skills to the next level. There are a huge number of resources out there. Hopefully this will help you choose where to start.
Continue reading “Learning (or Improving at) pandas”
In a previous post, we scraped NBA matchup data for the 1996-97 through 2016-17 seasons. We also noted that, during that time period, on average the home team won roughly 60% of home games during the regular season.
This is a big deal. An average team should win 50% of the time on a neutral court, but history shows that home court is worth a roughly 10% boost in win probability during the regular season. We’ll focus on the playoffs in a later post. Home court clearly matters a lot in the NBA post-season as well.
In this post, we’ll start by reviewing some of the main explanations for home court advantage in the NBA. Then, we’ll take a quick look at how the advantage has varied since the 1996-97 season. We’ll also look at how the advantage shows up in point differentials.
Continue reading “A First Look at NBA Home Court Advantage”
