This article is a proof-of-concept. I’m going to outline a methodology, then use it to write about a few interesting storylines. I’m hoping you will improve on the methodology, and use it to tell better stories.
Everything below follows from the question, “How much of Elvis Andrus’ offensive production is from walks?” His batting average isn’t spectacular and he hits for no power, so why walk him? And yet, he still walks a fair amount. Weird question, perhaps.
My approach is to add up the linear weights values of basic, positive hitting events (BB, HBP, 1B, 2B, 3B, HR), each multiplied by the frequency they occur. Then find the percentage of the total for each event. And there’s one twist — I subtract the value of an out, a la wOBA, except I subtract the out value according to total runs created, not the out value relative to average.
Here’s an example. In his career, Elvis Andrus has 232 walks. Each walk is worth .33 runs above the average offensive event (including outs). The out is worth -.1 runs, so each walk nets out at +.43 runs. 232 times .43 = 100 runs created via walk. Repeating the process for other major events yields 9 runs by HBP, 329 runs by single, 86 by double, 30 by triple, and 21 by HR. That’s 576 total runs, so the 100 runs from walks is 17% of the total package.
Is that high? I don’t know, we need some context. In the 2012 American League, walks were 17% of offensive production. So, Andrus is typical. Where he isn’t typical is in his lack of power. Whereas the 2012 AL has a full 20% of production from home runs and 41% from singles, Andrus is at 4% and 57%, respectively.
How about some other examples? Barry Bonds, in 2004, hit .362/.609/.812. Those 232 walks (Andrus’ career total, by the way), account for 42% of his offensive production. Singles, 19%. And home runs, 29%. While Bonds certainly had a good eye, his walking skill wasn’t necessarily greater than his home run skill. It’s just that pitchers chose to get beaten by his walks rather than mess with his power. (You know this, I just wanted to point out that I’m measuring what happened, not trying to describe skills. Accounting, not prescribing)
Speaking of power, we can split offensive production between hitting for power, hitting for average, and walks/HBPs. For power, I like to subtract a hitter’s production pretending all hits were singles from his total production across all hits. Sort of like isolated power, but with linear weights. For Miguel Cabrera in 2013, his production is 23% due to power. To measure the hit tool, I pretend all hits are singles. Cabrera 2013 is at 60%. And walks/HBPs make up the other 16%. As a comparison, Joey Votto 2013 is at 14% power, 58% hit tool, and 26% BBs.
Finally, because no good saber article is complete without a list, here’s a breakdown of some other 2013 hitting profiles, picking out the highest and lowest rates in each of the three categories. I really enjoy comparisons like Sal Perez and Alex Gordon. They have somewhat similar relative profiles, but Gordon has been way better across each category.
Player Hit Pow Walks Jeff Keppinger 87% 9% 3% Salvador Perez 81% 14% 5% Alex Gordon 72% 18% 10% Adam Dunn 42% 33% 25% Josh Willingham 42% 23% 35% J.P. Arencibia 62% 34% 4% Chris Davis 51% 29% 20% Bryce Harper 51% 27% 21% Dustin Ackley 71% 8% 21% Ben Revere 81% 6% 13% Shin-Soo Choo 48% 20% 32% Ike Davis 54% 16% 29% B.J. Upton 52% 19% 29% Manny Machado 71% 22% 7% Adam Jones 69% 24% 7%
Ok, your turn. How could you improve on this?
Account for additional skills, like avoiding strikeouts, BABIP, baserunning, etc…
Do something with IBBs (I suggest ignoring them or else giving them the average runs/PA value of a hitter overall.)
Get the whole “subtracting the value of an out” thing right — maybe find a number between -.1 (total runs created) and -.3 (runs above average) that represents runs above position-neutral replacement level?
Customize the linear weights for year, league, and park.
Do something similar for pitchers.
Produce a file with values for tons of players and seasons and careers.
Create a spreadsheet tool to plug and chug any values.
Create a useful, intuitive visual way to represent this info (personally, I like the trio of hit tool, walks, power.)
To be honest, I didn’t really figure out any of this methodology. I mixed some ideas from Colin Wyers, Patriot, Matt Klaassen, and Lee Panas. They get any credit this idea deserves.
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