NBA Analytics With Python: A Tutorial

by Gene Li

 

Students just getting into the world of sports analytics have a lot of questions, and this guide will serve as a starting point for understanding the big picture overview of the data science process for getting data, processing it, visualizing it, and applying interesting learning models to it. Continue reading “NBA Analytics With Python: A Tutorial”

Theory of the Big 3: Predicting NBA Team Win % from Individual Performance (Full Paper)

by Gene Li   Nowhere is the concept of the “Big 3” more relevant than basketball. As a relatively star-dominated game compared to football, soccer, etc., NBA games are determined by the performance of a few players who can deliver offensive firepower. NBA fans often view their team’s success as driven by the top three players on each team. Just last season, we saw the … Continue reading Theory of the Big 3: Predicting NBA Team Win % from Individual Performance (Full Paper)

Does Order Matter? An Analysis of Round 1 vs Round 2 Picks in the NBA

by Alex Vukasin

 

Are teams really making use of their first round picks? Have scouts been able to pinpoint the best talent with their first round picks, or is the draft round not a significant indicator of the talent and future of players in the league? Continue reading “Does Order Matter? An Analysis of Round 1 vs Round 2 Picks in the NBA”

The Hot Hand: NBA Shot Streaks and the Geometric Distribution

by Neil Rangwani   Each year, as the NBA season kicks off, the “hot hand” debate (or, according to Wikipedia, the hot hand fallacy) resurfaces – are streaks of made shots indicative of a player getting hot, or are they just random occurrences? Here at Princeton Sports Analytics, we’re not happy discussing this with just anecdotal evidence (I mean, did you see Steph last night?), so … Continue reading The Hot Hand: NBA Shot Streaks and the Geometric Distribution

There is No Place Like Home

By Jeffrey Gleason

Nine weeks into the NFL season, no teams remain unbeaten. This could’ve actually been said after eight weeks, after seven weeks, and after six weeks as well. Week 5 was the last time an unbeaten team remained, when both the Cardinals and Bengals were sitting at 3-0.

However, after these same nine weeks, five teams remain unbeaten at home. The Patriots, Broncos, Eagles, Packers, and Cardinals have yet to lose on their own turf.

Home field advantage is a phenomenon that gets a lot of traction in sports. Experts often use it to justify their predictions and betting lines usually reflect the perceived advantage of the home side. However, people often generalize home field advantage with a “one size fits all” approach, acknowledging its presence, but assuming it displays a constant impact across different situations.

With five unbeaten NFL home teams and the recent impetus of a road team finally winning Game 7 of the World Series (the Giants topped the Royals on October 29th to capture their third championship in five years), I was interested in how home field advantage was quantitatively different in different situations. How does it vary across sports? Do both good teams and bad teams experience the same advantage? Is it magnified in the postseason? What about differences in earlier eras? These are the questions I set out to resolve.

Continue reading “There is No Place Like Home”

Age in the NBA: Do older teams “find ways to win games”?

By: Patrick Harrel Tune in to any NBA team’s local broadcast, and you will be sure to hear a litany of clichés from the commentators. Most are quick to praise older players, noting on occasion that “veteran teams just know how to win games.” The San Antonio Spurs, for example, are lauded for their ability to defy expectations, winning another NBA title last year despite … Continue reading Age in the NBA: Do older teams “find ways to win games”?