For our analysis, let’s pretend that Yogi was wrong—that is, let’s say that the games are independent of one another (what happens in one game has no effect on what happens in other games).
Now, what probability should we assign to pitching a perfect game? Pitcher David Cone pitched a perfect game in 1999. There have been approximately 32,000 games played since that game in 1999, and seven of them have been perfect games. So it seems reasonable that we can think of the probability of a perfect game as p = 7/32000 (or about 0.00022). Using this value of p, we can calculate that the probability of seeing three or more perfect games in a single season is around 0.017. That is, there is a 1.7 percent chance of seeing three or more perfect games in a single season (under our assumptions). Pretty special, we’d say!
Each major league regular season includes n = 2430 games (over all teams). Using n = 2430 and p=.00022, we can compute the expected number of perfect games in a single season to be np = (2430)(.00022) = .5346. This would translate to about one perfect game every two seasons. This number is a bit high, since, on average, there has been one perfect game every five years since 1900.
Perhaps there is a reason for this, though. Maybe the game is evolving in an interesting way. If the 2013 season is a multiple perfect game season, it will be interesting indeed.
Posted: March 30, 2013 at 06:23 AM | 2 comment(s)
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