There has been a lot of talk about the surge in home run hitting in the 2017 season. I was curious — who are really hitting these additional home runs? So here is a quick R look comparing the 2016 and 2017 seasons.
- Using my BAPredict package, I was able to quickly pick up the 2017 season HR and AB counts from the SI website for the “top 200” hitters. I am assuming that these represent the players with the most at-bats.
- Using 2016 Retrosheet data, I collected the HR and AB counts through 11 weeks of the 2016 season. I choose 11 weeks since we have currently played 11 weeks of the 2017 season. To make a fair comparison, I select the 200 players in the 2016 season with the most at-bats.
- Here are summaries of the total number of home runs hit, total number of at-bats and home run rates for these top 200 hitters for the two seasons.
The key stats to look at are the rates — the 2017 home run rate is 4.13% which represents a 6.7% increase over the 2016 home run rate. - To see who are hitting these home runs, I construct parallel density plots of the home run rates for these top 200 hitters for the two seasons.
This is interesting. Usually we associate high home run hitting with the leaders (Bonds, McGwire, Sosa, etc). But this graph indicates that the 2017 home run surge is due to the increase in home run hitting among the non-sluggers — the players who generally don’t hit many home runs. Everyone is hitting home runs in this current baseball season. This suggests that the reason for the home run surge is not more big sluggers, but rather some change that is impacting the home run hitting for many players.
Exploring Baseball Data with R 