Last week, I unveiled the first iteration of my . This week, I’ll revise and expand on it. The main thing I didn’t like about the chart was the 5-game moving averages. The games dropping off the far end of the moving average add just as much movement as the newest game adds. The solution? … [Read more…]
The study of football is much more tricky than that of basketball–there are more players on the field and fewer plays and games to study. The links in the sidebar list a few of the sites that have done good work studying football statistics. Since the players are hard to analyze, I have confined myself … [Read more…]
The concept of With-or-Without-You is very basic. If you are playing, is our team better or worse? If the team is worse with you available, then that’s a really bad sign! It’s the core concept behind such basketball metrics as +/-, Statistical Plus/Minus and Advanced Plus/Minus. In baseball, Tom Tango and MGL work with it … [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…]
There are many ways to rank NBA teams; some better than others. This method runs as follows…
Hi, I’m Daniel (known as DSMok1 elsewhere), and this will be my first attempt at some fancy Google Visualizations. On my fancy new website.
This viz plots the 5-game TRAILING moving averages for each team in the NBA up through January 4th. It’s a bunch of data; we’ll see if the Google API can handle it.