My friend Ari sent me this link to a NY Times Op-Ed piece about Sadaharu [thanks, Tom] Oh and the debate about the “true” global homerun king. It’s interesting, and I even learned a bit about Japanese baseball and culture. But it also brought a thought to the front of my mind that’s been ready to hatch since Frank and I discussed intuition and statistics. The question is, why mainstream fans intuitively understand concepts like park effects, historical adjustments, and aging curves, but abhor attempts to quantify them? I understand that most people don’t have the math skills to tackle the analysis themselves, but why not trust other people who have done it? Here are some reasons I can think of. What do you think is the most pertinent and what else might be a factor?
- The precision of advanced calculations is often much less than people claim.
- If people don’t understand the calculation, then they don’t trust the result.
- People often only use these types of arguments when they support their own opinion. Quantification is too rational and not open to hyperbole.
- People don’t think these questions can be quantified in the first place.
- Quantification removes any influence by intangibles and immeasurable human factors.
- Much of the new research favors non-traditional choices and strategies. Change is bad.
- People have a difficult time intuitively grasping that a matter of degree can trump something that’s black and white. (For example, walking more often is not a dramatic skill, but stealing second can be a huge event when successful.)
The second part of the question would be what’s the best way to go about bringing more people into the club of trusting quantitative analysis? Beating non-followers over the head with numbers and calling them dumb hasn’t worked very well up to now…
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Sky is a baseball fan and racket sport afficianado living in upstate NY. His favorite color is orange and is just about ready to give up on his life-long dream to become the next Magnus ver Magnuson (World's Strongest Man). His favorite baseball teams are the Yankees and Red Sox, proving that there's hope in the Middle East.
August 13th, 2007 at 6:08 pm
One excellent measure of a starter would be runs saved — how many fewer runs does he give up than a replacement level pitcher in the same number of innings. And using ERA+, you can adjust for ballpark and league, which is nice. I’m calling these ERA+runs. If you hold ERA+runs as the benchmark/goal/ideal stat, then you get these correlations for our “simple” stats:
ERA+runs to Wins: .74
ERA+runs to QS: .80
A few conclusions:
- Comparing Wins to “ideal”, it’s not that close. Getting 75% of the way there in favor of simplicity seems a poor choice.
- Quality starts are only mildly better than Wins.