Basketball Analytics

The best decisions possible are generally made using the best information possible.

Whether it's scouting, game-planning, player development, or anything in between, you're going to want access to the best information possible.

Basketball analytics provides just that.

My goal in this section is to document (1) what advanced basketball analytics are, and (2) my personal basketball analytics work.

Pace-Adjusted Statistics

Advanced basketball analytics are basketball statistics that are normalized for the pace of play. That's the big innovation.

What does "normalized for the pace of play" mean? Let me give you an example:

Let's say Jordan plays on a really fast-paced team. They full-court press, they run in transition, and they average 100 possessions per game. Jordan averages 10pts per game on 20 minutes played per game.

Taylor, on the other hand, plays on a really slow-paced team. They slow the ball down, they melt the shotclock, and they average only 50 possessions per game. Taylor also averages 10pts per game on 20 minutes played per game.

Who is the better scorer, Jordan or Taylor?

Well, at first glance, they may look equal. Both Jordan and Taylor average 10pts per game on 20 minutes played per game.

But the difference is in their respective teams' pace of play - Jordan plays on a fast-paced team that averages 100 possessions per game, whereas Taylor plays on a slow-paced team that averages only 50 possessions per game.

When you account for the pace of play, the answer is obvious: Taylor is a better scorer than Jordan.

That's because, even though they both score the same amount in the same number of minutes, Taylor does so in fewer possessions played.

So on any given possession, Taylor is more likely to score than Jordan.

As you can see from the above table, even though Taylor and Jordan score the same number of points per minute (0.5), Taylor scores twice as many points per possession (0.2 vs. 0.1). That's a big difference.

This type of example, where accounting for the pace of play gives you better statistical insight, is applicable to every single data point you'd see on a typical basketball box score.

So whether it's assist, steals, blocks, points, or rebounds, you're going to want to take the pace of play into account. That'll allow you to compare apples-to-apples statistics between games and between teams.

"Advanced basketball analytics" in its most basic form is simply a term that describes adjusting for the pace of play to produce better basketball statistics.

If you're not using pace-adjusted statistics, you're missing out on a whole lot of statistical insight.

My Treasure Trove

For D3 Women's College Basketball, pace adjusted statistics weren't systematically available anywhere. So I had to create them myself.

With only one semester's worth of Computer Science under my belt, I taught myself how to code well enough to create a database I'm very proud of. It is, to my knowledge, the first-ever of it's kind.

You can access that work at my Tableau Public page. I hope you like it, and feel free to reach out with any questions!