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Positional Averages

Maybe these are posted elsewhere every year, and I just never found them. But if not, here you go. People always talk about "average production" from various positions, and I never know what they mean.

I'm going to look closer at these numbers and a different way of calculating positional averages for my next Hardball Times column, but in the meantime, here are the raw numbers. They are calculated across the AL and NL for all 2006 games--thus, for 1B, that includes everybody from starters like Prince Fielder to one-game fill-ins, like Corey Hart.

Position AVG OBP SLG OPS
Catcher 0.269 0.329 0.416 0.745
First Base 0.285 0.363 0.489 0.851
Second Base 0.276 0.334 0.410 0.744
Third Base 0.276 0.347 0.458 0.805
Shortstop 0.275 0.332 0.408 0.740
Leftfield 0.278 0.354 0.464 0.818
Centerfield 0.269 0.335 0.427 0.761
Rightfield 0.277 0.347 0.460 0.807
Designated Hitter 0.263 0.347 0.463 0.811

0 recs | Comment 8 comments

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The thing that stuck out most to me
was the average catcher bats .269 This makes me all the happier that now have a .300 batting catcher and a nice backup.

by Tim on Jan 29, 2007 6:08 PM CST reply reply actions actions   0 recs

OBP differences
Jeff, I was curious about how you calculated the averages. I keep my own spreadsheet of league averages and my OBPs are slightly different than yours. I just compile all the stats from ESPN's stat pages and was wondering why that causes mine to be a bit off from your method.

by Jim Wisinski on Jan 30, 2007 2:39 PM CST reply reply actions actions   0 recs

Jeff makes his up
"C'mon, boys, let's get 'em some RUNS!" --- Daron Sutton, pretty much every game of the 2005 season.

by roguejim on Jan 30, 2007 2:48 PM CST to parent up reply reply actions actions   0 recs

He knows he's still great, though
"C'mon, boys, let's get 'em some RUNS!" --- Daron Sutton, pretty much every game of the 2005 season.

by roguejim on Jan 30, 2007 2:49 PM CST to parent up reply reply actions actions   0 recs

I used Pinto's day by day database
I took the positional averages from each team's splits pages, added up all the counting stats, and that's how I generated my averages.

If the only difference is with OBP, it might be because we are calculating it differently.  I used (H+BB+HBP)/(AB+BB+HBP+SF)  I know there are a couple of different ways to do it.

by Jeff Sackmann on Jan 30, 2007 3:12 PM CST to parent up reply reply actions actions   0 recs

Gorillas!
Mine is the same, must be slight differences in the stat providers.

by Jim Wisinski on Jan 30, 2007 3:52 PM CST to parent up reply reply actions actions   0 recs

My best guess
is that the systems differ by how they define an at-bat as first-base or pinch-hit or something.  

by Jeff Sackmann on Jan 30, 2007 5:02 PM CST to parent up reply reply actions actions   0 recs

Nice data, here's what I do
I've been doing something like this for some years now.  I also use the ESPN data, like the commenter above, there is a team data section where you can select by position and I compile the list of NL teams (since I follow the Giants) and create a table for each position showing the production by position for each team.

I figure since data is lumpy, I thought it would be more interesting, like your fellow poster did by comparing projections with the positional averages, to see where each Giants player would have ranked in the previous year ranking if you took out the Giants and inserted in the Giants player for the upcoming season.  From looking at the data that way, sometimes there are positions that are skewing the averages, but by ranking then the player look better, relatively.

I never used public projections before, I would typically use the 3 year average or adjust for what I thought were extenuating factors (like a new player who played at a good or bad hitters park, for example, I would have used his 3 year road rates) and then insert the Giants starter into the ranking again, to see where he would fit in.  So just because Durham had a good year, the Giants would not just keep the same ranking, as his 3 year is lower, so it could go down.

I would get a ranking for each player then average it across the team to see what the average is and then compare them against the year before, to give me some idea how good, relatively, the Giants of the upcoming season is compared to the Giants of the previous season.

I will have to compile all the projections and use them this year instead.

by obsessivegiantscompulsive on Jan 31, 2007 8:06 PM CST reply reply actions actions   0 recs

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