As of the morning of November 20th, the Four Factors line for the 7-9 Dallas Mavericks read off as follows: Effective Field Goal Percentage: 0.527 (8th in the league) Turnover Percentage: 14.4 (28th in the league) Offensive Rebound Percentage: 22.6 (18th in the league) Free Throw Rate: 0.22 (7th in the league) Opponent eFG%: 0.527…
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…
Over the last decade, the subtle changes from offenses revolving around mid-range jump shots to long-range three point attempts have become much more explicit as teams such as the Houston Rockets had come off a 2017-18 campaign launching over 50% of their field goal attempts from beyond the arc. The mathematics is simple: “3 >…
Over the past decade a true emphasis on three point shooting has emerged. This can be credited to the understanding of effective field goal percentage being a better underlying parameter for points per field goal attempt than raw field goal percentage. And it’s become an emphasis for some top-tier teams such as the Houston Rockets.…
A tried-but-true strategy in pick-up (and grade school) basketball is the “dump-and-chase” offense. This offense takes as many jumpers as possible, regardless of capability, fully knowing that the team can either out-hustle their opponent for rebounds; or they have a behemoth of a rebounder on their team. As players become older, or more technically sound…
In our previous post on Stochastic Tracking, we took a look at motivating a Hierarchical Bayesian process in filtering tracking data and producing more robust estimators for the velocity. During the discussion, we limited the data sampled to be of two-dimensions only and had to assume that acceleration was constant between sampled points. Due to…
When we learn about computational mathematics, software engineering, or data science in general, one of the most important questions we have to answer is how many operations are required. The answer isn’t to show the prowess of our algorithm, but rather identify how quickly the algorithm can perform. We need to know if the answer…
Back in 2014, STATS Inc. introduced the notion of gravity, which was explained by Kevin Pelton as a series of two measures: gravity score and distraction score. In Pelton’s explanation, gravity score measures the relative distance a primary defender strays from their offensive counterpart and distraction score quantifies the amount of attention that same defender…
When we measure the defensive impact of a player, typically the first arguments we make are the number of blocks and steals that player has obtained. We celebrate players like Dikembe Mutombo and Maurice Cheeks for their prowess in obtaining blocks (2nd all time) and steals (5th all time), respectively. In the latter case, a…
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…