On the Randomness, or Lack Thereof, of a Baseball Linescore

Last night, the Texas Rangers beat the Baltimore Orioles by a score of 30 to 3. In a baseball game. The last major league baseball team to score 30 or more runs in a game was the Chicago Colts, in 1897.

If you had to guess when the Rangers scored their runs over 9 innings (the game was in Baltimore, so Texas batted in the top of the 9th), how would you distribute the runs? If I had to do it, my linescore would probably look about like this:

1 2 3 4 5 6 7 8 9

4 3 1 0 5 6 3 5 3

But here is the actual linescore:

1 2 3 4 5 6 7 8 9

0 0 0 5 0 9 0 10 6

The Rangers scored 30 runs in just 4 innings! It’s a good reminder, once again, that the way data plays out in real life is often nowhere near as orderly, predictable, or consistent as you might imagine it to be. Even though runs scored per inning isn’t quite a matter of random distribution, this linescore did call to mind the common exercise of predicting coin flips. Levitt wrote about this topic a while ago: if you ask most people to predict how a sequence of 100 coin flips would come out, they would rarely have long streaks of heads or tails. Their answer, in other words, would end up just as fake as my imagined linescore above.