Hitting by Lineup Position, 2012

I devoted a whole post to leadoff hitters, whether justified or not, so it's only fair to have a post about hitting by batting order position in general. I certainly consider this piece to be more trivia than sabermetrics, since there’s no analytical content.

The data in this post was taken from Baseball-Reference. The figures are park-adjusted. RC is ERP, including SB and CS, as used in my end of season stat posts. The weights used are constant across lineup positions; there was no attempt to apply specific weights to each position, although they are out there and would certainly make this a little bit more interesting.



NL #3 hitters retained the highest RG of any league-slot for the fourth consecutive year. AL teams were more balanced between #3 and #4, with the cleanup hitters holding a slight edge in RG built on BA (.275 to .264) but slightly less power (.189 to .193 ISO). NL leadoff me had a lower OBA than any other NL slots except 7, 8, and 9, and the #7 hitters managed to exceed their overall production (if you remove the Reds leadoff hitters, they did muster a higher RG than the #7s). AL teams were much better at leadoff, but gave those gains right back with poor #2 hitters.

Next, here are the team leaders in RG at each lineup position. The player listed is the one who appeared in the most games in that spot (which can be misleading, particularly for the bottom the batting order where there is no fixed regular, or injury cases like Evan Longoria getting stuck with the blame for the Rays’ cleanup hitters):



A few teams had the best production in their league at a pair of slots that are considered particularly important--the Angels at #1/2, the Tigers at #3/4, the Giants at #1/4. But the Cardinals got the best production of their NL rivals from #2, #6, and #8.

And the least productive:



The Astros and Royals both had two black holes in the middle of their order while the Chicago teams each trailed at #2 and a lower lineup position. Note that even in this lousy company, the Reds leadoff hitters had the worst OBA among the other league-worst positions except for the Pirates #9.

The next chart displays the top ten positions in terms of runs above average, compared to the average position for their league. To emphasize that, the RAA numbers here are, for example, the Angels #1 hitters compared to the other AL #1 hitters:



Even when you compare to the average for each slot, the top RAA figures are dominated by the expected slots. Please don’t use the fact that Trout outshone his leadoff peers by more than Cabrera outshone his #3 peers to bolster an MVP case--that would be silly on principle, and the performance of other players are include in the team figures reported here.

And the worst positions:



I wrote enough about Cincinnati’s leadoff hitters in an earlier post, but to pile on: their 2.6 RG was worse than any non-#9 spot for any other major league team. It was worse than the #9 slot of all but one American League team (CHA), making it the second-worst non-pitcher slot in the major leagues. Washington’s #9 hitters outhit Cincinnati’s leadoff hitters (2.7 RG to 2.6). They also had the 13th lowest walk rate of any position (8th lowest excluding NL #9s). Their OBA was 15th lowest of any position--and rock bottom when NL #9s are excluded. I marveled a few times during the season at Dusty Baker’s choices at the top of the order, but I had no idea that it was this bad until digging into the numbers.

I will close this post with a chart showing each team’s rank in RG in their league for each slot. The top and bottom three teams in each league have been highlighted. First the AL:



Last year this chart for Boston was filled with bold--this year they ranked in the bottom half of the AL in six of the nine spots, and only the #6 hitters weren’t borderline. Not much has changed in Seattle, except last year their ineptitude was centered at 4-6 rather than 1-4.

In the NL:



Based on talent or actual performance, Cincinnati had no business finishing fourth last in the NL in park-adjusted R/G. But that outcome starts to make a little more sense when you consider the leadoff disaster coupled with poor production from the cleanup hitters (.263/.323/.428).

Follow this link for the full spreadsheet.