Saturday, 30 March 2013

Regular Season Predictions for 2013

I can estimate the head-to-head performance of two teams from their win percentages.

If a is the win percentage for Team A and b is the win percentage for Team B, then the probability of Team A beating Team B in one game can be estimated as a * (1 – b) / [ a * (1 – b) + (1 – a) * b ] .

In my last post, I estimated the win percentage for the 7 teams in the league based on the expected runs for and against for each team.

I can now estimate the probability of each team winning in head-to-head competition.

The table below shows these calculations.



0.765 0.562 0.521 0.456 0.429 0.425 0.364


A B C E G D F
0.765 A 0.500 0.717 0.749 0.795 0.812 0.815 0.851
0.562 B 0.283 0.500 0.541 0.605 0.631 0.634 0.692
0.521 C 0.251 0.459 0.500 0.565 0.592 0.596 0.656
0.456 E 0.205 0.395 0.435 0.500 0.527 0.531 0.595
0.429 G 0.188 0.369 0.408 0.473 0.500 0.504 0.568
0.425 D 0.185 0.366 0.404 0.469 0.496 0.500 0.564
0.364 F 0.149 0.308 0.344 0.405 0.432 0.436 0.500

Assuming a balanced 18 game schedule, the win-loss record for the 7 teams would be as follows


A B C E G D F Wins
A 0 2 2 2 2 2 3 14
B 1 0 2 2 2 2 2 10
C 1 1 0 2 2 2 2 9
E 1 1 1 0 2 2 2 8
G 1 1 1 1 0 2 2 8
D 1 1 1 1 1 0 2 7
F 0 1 1 1 1 1 0 6
Losses 4 8 9 10 10 11 12

Thus team G would be tied with team E for 4th place at the end of the regular season.

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