42 1. Streaks
0 20 40 60 80 100 120 140
Game number
0.2
0.4
0.6
0.8
1
Winning
percentage
Figure 23. Windowed winning percentage for 1984 Baltimore Orioles
parameter Black is easy to describe in terms of this figure; it is the
area of the black region.
It is clear that if a team is consistent, then Black will be very
small, while if a team is streaky, Black will probably be large. Thus,
this parameter might be able to distinguish between the block-Bernoulli
and the Bernoulli models. To decide which model fits a given team
better, Albert and Bennett compute the winning percentage of the
team. Then they obtain, by simulation, the distribution of the pa-
rameter Black under both models. The actual value of Black for the
team is computed and compared with the two distributions. For each
distribution, a p-value is reported. If the first p-value of the observa-
tion is larger than the second p-value, then they claim that the first
model fits the team’s performance better than the second model.
In fact, they go further and use the ratio of the p-values as the
odds that the team is consistent (or streaky). For example, if the p-
values for a given team, under the consistent and streaky models, are
.08 and .30, respectively, then they say that the probability that the
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