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Great article. Respect the research and "obvious" conclusions from that; but, may I remind you of Simpson's Paradox. If I focus on one seemingly inconsistency; that being runs per game. If home runs are down, wouldn't fewer RPG naturally follow? Perversely, if RPG is up, wouldn't this necessitate fewer innings pitched by SPs. I don't think these conclusions to be circuitous, but maybe a tinge? (I know you were showing the data, as is, without a consideration for any common relatedness or correlation.)d Thanks.
By the by, how can hitters "adjust" to this knowledge? Or, do they?
Which metric do you suggest to measure a pitcher's efficacy? Do you do any correlational measures (such as <span class="statdef"><a href="http://www.baseballprospectus.com/glossary/index.php?search=ERA" onmouseover="doTooltip(event, jpfl_getStat('ERA'))" onmouseout="hideTip()">ERA</span></a> and tunnel ratio)? What are the error stats? Do any MLB teams actually work on "tunnel metrics" with their pitching staff? Great article. Thanks.
Is there a moral question/issue with the protocols described in the article? More speed may provide additional stress on the UCL resulting in more TJSs. So do the teams provide probabilies of the additional strain on the possibility of <span class="statdef"><a href="http://www.baseballprospectus.com/glossary/index.php?search=TJS" onmouseover="doTooltip(event, jpfl_getStat('TJS'))" onmouseout="hideTip()">TJS</span></a>? There is also a test for the UCL and could help with determining the maximum value of the speed attained and the risk of UCL tear (the test has not reached a high validity yet, but will eventually). An "average" career may be better than the risk of TJS and the possibility of ending one's career (probably around 15-20%?).
Do you think in part, that support for this is the rising number of TJSs?
Fascinating stats - how does George Spring and Jon Singleton rate?
I think there is a random variable you are overlooking in your model and will influence the batter and that is the consistency/inconsistency of the plate umpire. If the PU has a high strike count of pitches that are actually balls, the batter somehow accounts for that in his batting approach with the counts. You might want to use a co-variant for that in your analysis.
Why are Cardinals so reluctant to go after the Astros' Castro?
It would be interesting to see if "adjustments" work using this statistical technique or not. I am thinking of JD Martinez. He claims to have made a rather significant (not stat) adjustment to his swing and had really been a hitting machine. Not the usual foot tap or ... but keeping the bat in the zone longer, etc. If your analysis can reverse engineer, maybe more batters would be willing to use "proven" tips to improve their PECOTA/etc.
God's gift to statisticians. Random error. The body's resistance for a repeated behavior to be consistent. Once learned, one RE can enhance or take away another. The statistician is bewildered. Aha, it must be regression. Not the Coach, I say. Bah, Humbug. But it does provide fodder for another article. Enjoyed.
No Houston cleanup hitter has hit a home run this year. Has that phenomenon ever happen previously in the history of baseball for an entire year; that is, no HR by a cleanup hitter for a team for a year? Second part - what is the record for the longest stretch of games for that to happen?