A Scoring Efficiency Model v.2

By Cyril Smith

Last week I described a simple scoring efficiency model based on points per minute. As is not unusual in the financial modeling world it promptly went 0 for 4 on the divisional playoff round games. Other models - the Las Vegas line for example - were better in getting at least one game right.
In reviewing the model (which itself was based on data from the 2005-07 regular season and playoff games) it seemed that the weak point was the assumption that each team was roughly equal and that its scoring potential was based on 30 minutes of possession. While this approach had worked reasonably well on past data as well as the wild card round, it did not perform well in the divisional round. There is in fact a great deal of volatility in each team's points per minute and time of possession - volatility which is obscured by using averages. I therefore looked for a way to incorporate this volatility into the model.

At first blush it is apparent that volatility is inversely related to wins. Teams that showed greater volatility in points per minute and time of possession tended to do worse in results. A reasonable hypothesis is that volatility represents weaknesses which a team may not be able to overcome in the playoffs because the opposing team will zero in on those weaknesses. According I took a first cut at combining volatility of points per minute and time of possession, in each case measured by the standard deviation of the series, into the model. The preliminary results look promising. Using the additional input resulted in two changes for the divisional round: Pittsburgh was now favored over San Diego and Baltimore over Tennessee.

Looking ahead the revised model has Philadelphia over Arizona by a point and Pittsburgh over Baltimore by 4 points.