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• I assembled the results of all NBA games between the 1992 and 2003 seasons, for each game noting the number of days rest each team had heading into the game,
Message 1 of 1 , Aug 7 7:38 PM
I assembled the results of all NBA games between the 1992 and 2003 seasons,
for each game noting the number of days rest each team had heading into the
game, and each team's winning percentage heading into the game (with a small
adjustment, noted below). I regressed these variables against the
Pythagorean score of each game and found to my surprise that the days rest
variable was not statistically significant. This struck my as odd, and
caused me to wonder if I have done something wrong -- I am not really used
to multiple regressing, and perhaps I am not doing it right, or am
misinterpreting the results.

I present the results below in hopes that someone can point out my error.

Variables:

PythScore - Winning team's Pts^14 /
(Winning team's Pts^14 + Losing team's Pts^14)
WHome - Winning team Home = 1 or away =0
Win%_W - Winning team win% leading into game
Win%_L - Losing team win% leading into game
Rest_W - Winning team's rest days leading into game
Rest_L - Losing team's rest days leading into game
Rest_W2 - Rest_W squared
Rest_L2 - Rest_L squared
days minus Losing team's rest days
was negative, RestAd2 would also be negative)

Note:
For the Win%_W and Win%_L variables, I added 1.5 games to the win and loss
columns. That is, at the first game of every season, every team has a
1.5-1.5 record going into their first game.

Here are the regression results for the home/away, winning percentages, and
days rest variables:

Predictor Coef SE Coef T P
Constant 0.747300 0.006284 118.92 0.000
WHome 0.041848 0.002387 17.53 0.000
Win%_W 0.129275 0.007726 16.73 0.000
Win%_L -0.127516 0.007206 -17.70 0.000
Rest_W 0.001036 0.001235 0.84 0.402
Rest_L -0.002776 0.001253 -2.21 0.027

I don't know if I'm interpreting this correctly -- the losing team days rest
is significant, but the winning team's is not? That would be very strange.

Here is the results, raising each team's days rest to the second power:

Predictor Coef SE Coef T P
Constant 0.744968 0.005616 132.64 0.000
WHome 0.042559 0.002361 18.03 0.000
Win%_W 0.128975 0.007726 16.69 0.000
Win%_L -0.127359 0.007206 -17.67 0.000
Rest_W2 0.0000105 0.0002082 0.05 0.960
Rest_L2 -0.0002954 0.0002229 -1.33 0.185

Neither of the day's rest variables are significant, contradicting earlier
results, I think.

How about if we just look at the wining team's advantage in days rest, ie
how many more days rest the winning team had over its opponent:

Predictor Coef SE Coef T P
Constant 0.743772 0.005544 134.17 0.000
WHome 0.042971 0.002321 18.51 0.000
Win%_W 0.128795 0.007725 16.67 0.000
Win%_L -0.127331 0.007206 -17.67 0.000

And the same thing, but squaring the rest advantage term:

Predictor Coef SE Coef T P
Constant 0.743741 0.005473 135.88 0.000
WHome 0.043011 0.002322 18.53 0.000
Win%_W 0.128690 0.007725 16.66 0.000
Win%_L -0.127316 0.007205 -17.67 0.000