A quick update to , using a newer ASPM regression. The data here includes only data from 1978 to 2014, so players who started their careers before 1978 will be underrepresented. Kareem Abdul-Jabbar, for instance, was already 30 in 1978–and he had a hall of fame career after that! Hall Rating, as currently constituted, is … [Read more…]
Well, everyone else has an All-Star post up already: The actual All-Stars Mike G at APBR, with his eWins selections (also PER shown) (his thread inspired me to write this up) EvanZ, with his ezPM on the West and East All-Stars Kevin Pelton, with his WARP All-Stars John Hollinger’s look at ESPN Zach Lowe’s take … [Read more…]
The ASPM spreadsheet (download here) has a sheet for estimating a game’s results, based on team rest, location, and the rotation of players expected to play. For a quick example, I’ll look at the Magic vs. Heat game this evening. Here’s the sheet: I estimated the minutes each player would play based upon the rotations … [Read more…]
Yesterday’s Thunder-Heat game was a fun game to watch and a great game to investigate. Oklahoma City started out with a significant advantage in this game: OKC was at home (worth 3.24 pts/100 poss) and was playing on 1 day of rest (+1.94), while Miami was playing their 3rd game in 4 days, and on … [Read more…]
Last week, I unveiled a Google Motion Chart that included a large number of advanced stats comparing point guards. This week, we’ll start at the other end: centers. I actually am including players classified as either C or PF/C by BasketballValue, where I got the position information.
Most people feel that the position of center is changing, morphing into something different than it once was. The presence of numerous “centers” that hang around on the perimeter shooting 3’s is an indicator of this phenomenon. Still, there is a defined way a center plays–and to define it, let’s turn to the lovely tool known as K-Means Clustering.
So, what else can Google Motion Charts be used to visualize? Well, this application doesn’t actually *move*, but it does visualize a ton of point guard advanced statistics at once. That’s quite a few advanced stats in one place! Play around with the chart and see what can be revealed. I have 4 player evaluation … [Read more…]
Recently, I developed a method for analyzing single games through the Advanced Statistical Plus/Minus (ASPM) lens. Basically, in order to keep the data in the range where the weights for the stats makes sense (some of the weights are nonlinear), I add several games worth of average stats to the player’s stat line. I then … [Read more…]