Basic form:
PointDiff = HomeCourt + (SRSHome - SRSAway) + HomeDays + AwayDays + HomeDistance + AwayDistance
Travel distance is taken as the distance from the arena of the previous game to the arena of the current game. The games in London and Japan, as well as the ones immediately following, were excluded from the analysis.
Using 14 regular seasons for data, trying to predict the point margin of every game with the average adjusted point differential of each team along with a long set of other variables, travel distance does appear to be a significant predictor, but it's only a weak significance. Surprisingly, the travel distance of the home team is more important, and the total amount of travel in the past week, weighted by recency, is a better predictor. For rest before games, having no rest (playing the day before) is a highly significant disadvantage, while there's some weak evidence having too much rest causes a negative effect -- i.e. rust. What homecourt advantage is depends on what other variables you consider. For example, in one model homecourt advantage is about +3.1, other factors held equal, but this doesn't include the teams with higher than average advantages at home and the higher likelihood of away teams playing the night before.
There are certain teams, however, with a significantly larger than average homecourt advantage. Denver is roughly +1.5 points above the natural homecourt advantage with very high statistical significant, while both Utah and Sacramento have some significance (but not high) with around +1.1 point for hosting a game in their arena. Teams travel vast distances over North America in a matter of hours, traversing the continent to play a game the next day with modern aircraft and luxuries, causing an apparently complicated relationship between homecourt advantage and expectations -- but it's perhaps simpler than we think. Athletes like having at least one day of rest, while distance is only bothersome when it stunts your ability to enjoy your homecourt advantage, rust is perhaps a real issue but only at the extremes, and home is home: the comforts of playing in your own arena are genuine and potent, some arenas more than others.
Homecourt model 3 with k=5 (step regression), st. error = 11.25, and adj. R^2 = 0.2353
Code: Select all
Coefficient St. Error p-value
Intercept 2.80 0.111 < 2e-16
Predicted point diff. 1.00 0.0142 < 2e-16
HomeNoRest -1.32 0.243 6.38e-8
AwayNoRest 1.94 0.189 < 2e-16Code: Select all
Coefficient St. Error p-value
Intercept 3.21 0.167 < 2e-16
Predicted point diff. 1.00 0.0142 < 2e-16
HomeNoRest -1.17 0.253 3.80e-6
AwayNoRest 1.97 0.189 < 2e-16
HomeRestDays^2 -0.0773 0.0351 0.0277
HomeTravelDistance 0.00102 4.30e-4 0.0146
HomeSixDayTravelWtd -0.00102 3.80e-4 0.00293Code: Select all
Coefficient St. Error p-value
Intercept 2.68 0.115 < 2e-16
Predicted point diff. 1.00 0.0142 < 2e-16
HomeNoRest -1.30 0.244 8.70e-8
AwayNoRest 1.95 0.189 < 2e-16
DEN 1.50 0.485 0.00198
SAC 1.16 0.484 0.0167
UTA 1.07 0.486 0.0282It took me a while to get the data prepared and the variables organized. It was frustrating to try to fit travel distance, and then to see it fall out as a predictor. I want to also focus in on Denver and Utah's homecourt advantage and look closely at elevation and adjustments to their altitude. I'll continue to refine this approach and add the playoffs. I'd like to see any thoughts. Thanks.