As a player traverses across the court, they break down and process every event that they see: the assertion of defensive players, the alignment of their teammates, and current state of the game. The ability to perceive all three components simultaneously is what I call court vision. It is one of the primary instigators that…
The end goal for all basketball analytics is to gain wins. In order to gain wins, a team must score more points than their opponent. It may seem like a completely obvious and yet, vague statement; but this is the reality: how does this “newfound” intelligence gain wins? In sports, if this intelligence is proprietary,…
When we break down different types of actions on the court, we tend to look at play-by-play as a guide to understanding the play types. The most common break down we see is the shot type for a field goal attempt. From there, we have recently tended to discuss the differences between Klay Thompson and…
On December 31st, James Harden dropped yet another 40+ points triple double on the Memphis Grizzlies in a 113 – 101 victory in Houston. It wasn’t the 43 points, 10 rebounds, and 13 assists that was the most impressive stat of the night, but rather the fact that Harden scored 43 points to spite making…
With the new year coming up, we will be posting our NCAA Rankings based on single-season, non-prior induced, metrics for predicting who should make the NCAA tournament. Every year, we typically score between 65 and 68 teams correct; last year being a bust with 64 teams. As a side note, three of the four missed…
Over the previous couple seasons, I have written extensively about how Regularized Adjusted Plus-Minus (RAPM) is constructed, what the assumptions really mean, and how we interpret the results. If you’re curious for a refresher, feel free to remind yourself here. There’s an example in there that clearly breaks down how various forms of adjusted plus-minus…
A couple years ago, I presented an introduction to the Wilcoxon-Mann-Whitney nonparametric test with respect to identifying whether scoring was indeed increasing in the NBA. This was in 2015; and now that we are a few seasons along, we can start tracking the year-to-year trends. The reason for this popping up once again is primarily…
The usage of an NBA player consists of the number of chances a player takes out of the possible chances a team has when that player is on the court. A chance being the number of possessions that can result in a scoring possession. The higher the usage for a particular player, the more likely…
In possession models and analytics such as RAPM, the ability to count free throws is crucial. Any miscalculation in computing free throws can result in an unintended dire consequence. In the case of a possession, a team’s possession may be calculated with bias and therefore comparing two teams using per possession stats becomes a flawed…
In 2004, Dean Oliver expanded upon his “Four Factors” philosophy from his 2002 book, Basketball on Paper, in an attempt to identify how four important strategies relate to success in basketball. These strategies are nothing new, as these were drilled into my head from coaches dating back to the early 90’s. The novelty of understanding…
Squared Statistics: Understanding Basketball Analytics 