The last few days, I’ve been thinking about different ways to explore the offensive and defensive strength of teams with respect to one another. Some weeks ago I came to learn about a “Motion Chart” gadget provided within Google Docs (thanks to Commodore from the Clutchfans message board for this). I figured this would be a great way to observe trends in team performance. I imported offensive efficiency, defensive efficiency, and pace data for all 30 NBA teams over the course of the season, and created an NBA Motion Map gadget. I’ll describe briefly the various categories you can visualize:
- OFF: offensive efficiency or points scored per 100 possessions
- DEF: defensive efficiency or points allowed per 100 possessions
- PACE: possessions per 48 minutes
- EFF: point differential (per 100 possessions)
- OFF_std, DEF_std, PACE_std, EFF_std: these are standardized statistics, where a value of 0 would be league average, the more negative the worse the team is, and the more positive the better the team is.
- OFF_DEF_std: this indicates how balanced the team is, more positive means the team is offensively-inclined, more negative means the team is defensively-inclined
- And for each of the above, you can choose between 2 weeks (stats over prior 2 weeks) or season (stats from the beginning of the season)
The gadget is fairly customizable. By default, it shows offensive efficiency vs defensive efficiency, though using the standardized versions you might get a better gauge of how “above average” or “below average” a team is along a given metric. Another view I would suggest taking a look at is EFF_std vs OFF_DEF_std. Along one dimension you’ll see how strong or weak the team is overall, and along the other dimension you’ll see their offensive/defensive orientation. You can also set the color and/or size of each point to depend on a specified metric. The Trails check box will control whether a path is drawn for the teams you’ve selected. This is useful if you want to get a stronger visual sense of how a team is trending over time. Here’s a snapshot to illustrate what it can show you:
In the above example, the changing color from one point to the next reflects changes in pace. The size of the points change to reflect overall efficiency (a “-” in the middle indicates periods where the Houston Rockets were getting outscored). You can also zoom in by dragging a rectangle over an area of interest. Opacity of non-selected teams can be adjusted by clicking the wrench in the lower-right corner as well.
Try it out for yourself:
In addition to the motion scatter plot, you may also find the charts in the other two tabs interesting. The bar chart in the middle tab will show you how the ranking of selected teams along specified metrics change over time. The third chart summarizes the fluctuations of specified metrics over time with a line graph. In the near future, I will look to add “four factor” stats as well (i.e., field goal efficiency, rebounding, turnovers, free throws). If you have any suggestions on other numbers that might be interesting to track, please let me know in the comments section.