On Tuesday night, during Kansas City’s improbable 9-8 wild-card defeat of Oakland (box), Royals left-hander Brandon Finnegan recorded undoubtedly the highest-leverage innings of his very brief major-league career in the highest-leverage game of his club’s season. The results were impressive: 2.1 IP, 9 TBF, 3 K, 1 BB, 1 H, 1 R, 63 xFIP-. For those unfamiliar with Finnegan previously, his performance was surely a revelation. Even for those who possessed some intimate knowledge of his college career at TCU, the outcome was likely a minor surprise, too — if for no other reason than it’s rare for any draftee to contribute meaningfully to his organization’s parent club just a few months after having become a professional.
Between his seven regular-season and (now) single postseason appearance, Finnegan is among that frustrating class of pitcher for whom (a) there exists some manner of major-league data but also (b) not so much that the fielding-independent stats which most directly inform run prevention (strikeouts, walks, ground balls) have become reliable yet.
Notably, though, there’s a collection of what one might call intermediary fielding-independent numbers — that is, metrics which (a) inform the metrics which inform run prevention but also (b) become reliable more quickly than either strikeout or walk rate (which require 70 and 170 batters faced, respectively, according to work done by Russell Carleton). Specifically, I’m thinking of these intermediary fielding-independent numbers: fastball velocity (which is useful insofar as it becomes reliable almost immediately), swinging-strike rate (which is predictive of strikeout rate), and first-pitch-strike rate (which is predictive of walk rate). Precisely how much more quickly the latter two become reliable than the stats they inform, I’m unable to say. The object of this brief exercise, however, is less about Ultimate Precision and more about attempting to extract useful information from a limited sample.
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