Statistics and Baseball

Today I passed out some batting data for the 30 Major League teams for the current season. We were focusing on differences between the two leagues. Here are some observations we made:

• The big difference between the two leagues is the AL's use of the designated hitter who bats for the pitcher.
• The use of the DH does affect one baseball strategy -- the use of the sacrifice bunt to move a runner from 1st base to 2nd base.
• We saw that there was a significant difference in the number of sacrifice bunts between the two leagues. By use of 5-number summaries and parallel boxplots, we saw that NL teams tended to have ??? more sacrifice bunts than AL teams. (Sorry -- I forget what the number was.)
• Some teams like the Blue Jays and the Athletics rarely sacrifice. These two teams believe in the useful of sabermetrics, so I wonder if the small number of sacrifice bunts means that these two teams understand that the sacrifice bunt is really an overrated strategy.

We started to look at relationships.

• We begin by constructing a scatterplot of two quantitative variables and making a statement about the direction and strength of the association. For the AL teams, we saw there was a strong positive relationship between batting average (AVG) and runs scored per game.
• Once we see a relationship, it is helpful to summarize the relationship by fitting a line. We fit a line by eye to the (AVG, RunsPerGame) data. Using this fitted line, we can predict how many runs per game a team will scored given its batting average.