Last week, I reintroduced my Small Sample Normalization Services (SSNS), analyzing strong starts by Dylan Bundy, Jose Berrios, and Patrick Corbin in the context of other small samples within their respective careers or recent histories. This time, I discuss three more odd starts among starting pitchers and their implications.
Every time an analyst uses the caveat “small sample size, but,” an angel gets its wings. And then that angel takes flight and also analyzes a small sample size.
I preach patience when it comes to the first few weeks of a Major League Baseball season, and I try to practice it, too, regarding both early-season breakouts and duds. Aside from transactions related to the disabled list, I have yet to drop any player I drafted who wasn’t legitimately dead weight (like my decaying shares of Melky Cabrera and John Lackey) or, in ottoneu, a roster burden, such as a hapless $7 share of a helpless Alex Cobb.
That said, I can’t simply wait until mid-May or whatever to make meaningful analyses of players. But I also can’t make knee-jerk reactions about 30 innings or 90 plate appearances. I try to reconcile this cognitive dissonance by engaging in what I called last year Small Sample Normalization Services (SSNS). The intent: first, to attempt to find similarly long and (un)productive streaks in a player’s past; second, to evaluate how similar or comparable those streaks actually are; and, last, to slap an appropriate level of excitement or panic to the performance in question. If we can’t say with absolute certainty that we’re watching a player do something sustainable, then maybe it helps to know if he had done something similar in the past. If not, what befell him afterward? And if so, how should we move forward with him?
#3: May 3
#2: April 24
#1: April 13
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It’s episode No. 4 of my Small-Sample Normalization Services, which, in Star Wars terms, means this will be, like… the 3rd-best post of the series? Is that how that works? I know to nothing about what’s believed to be the consensus on the merits of each film. I already regret making this stupid comparison.
Allow me, then, to touch upon (and revisit) some players whose performances through six weeks are worth critiquing. Six weeks is still a considerably small sample when it takes hundreds of plate appearances (or, for ball-in-play metrics, batted balls) for certain standard and advanced metrics to become reliable (or, in common but sometimes misused parlance, “to stabilize”). Check previous posts for the rules, but know that a rating of 1 means Hype City and a rating of 5 means, uh, Alarm City. A 3, therefore, would be neutral.
All graphs pulled prior to yesterday’s games.
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Name: Masahiro Tanaka, NYY SP
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If you’ve tuned in before, you know what this is about. If not: the Small-Sample Normalization Service (SSNS) seeks to, ah, normalize a player’s performance in the context of his own previous achievements (or lack thereof). Most of us are human, and our humanity leaves us vulnerable to the biases that cloud rational thought and critical analysis. Such vulnerability is eagerly exploited by the small sample size, never more so than in April. While midseason small samples cower under the cover of hundreds more plate appearances, April performances have no such luxury.
A month’s worth of playing time is certainly more worthwhile to assess than one week’s worth, but 30 innings or 100 plate appearances can still be pretty volatile. Here are a few still-small samples that recently caught my eye.
All graphs pulled prior to yesterday’s games.
Name: Byron Buxton, MIN OF
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Last week, I inaugurated RotoGraphs’ Small-Sample Normalization Services, or SSNS. Said services attempt to contextualize good and bad starts within a particular player’s history of achievements (or lack thereof). Assessing player performance based on small samples seems distinctly difficult in April, when, for whatever reason, we perceive players with tattered histories as blank slates. Occasionally, there’s merit to these perceptions. More often, we find out a player’s April is no different than his May or June or July, for example, when a small-sample performance might go less noticed than it would when starting from zeroes.
Here are a handful of players that have caught my eye lately.
Name: Jason Vargas, KCR SP
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By clicking this link, you (“Reader”) have opted into an agreement (“Contract”) with FanGraphs, Inc. (“Handsome Author”). Handsome Author agrees to provide Small-Sample Normalization Services (SSNS) to Reader in the following post (“Post”). In return, Reader, presumably interested in Handsome Author’s analysis or merely intrigued by Handsome Author’s curious Post title, shall appreciate said services no matter what.
SSNS seeks to normalize good and bad performances witnessed in the first two weeks of the 2017 Major League Baseball (MLB) season. Handsome Author has noted previously, here and elsewhere, that small-sample booms and busts in March and April would go largely unnoticed in other months in which the sport of professional baseball is played, such as May, June, July, August, or even September.
Accordingly, SSNS looks at a player’s past performance as a benchmark for current performance using FanGraphs’ (and not Handsome Author’s) very nifty player graphs. It answers the question, “Has a player done this before?” Perhaps, Reader. Perhaps. But perhaps not. SSNS then assigns an Excitement-to-Panic Level (EPL) on a 5-point scale from 1 to 5 as well as an Adjusted Excitement-to-Panic Level (AEPL) once Handsome Author has properly assessed the historical significance of the player’s performance — within the context of the player’s self.
In this inaugural edition, Handsome Author will use SSNS to evaluate five hitters primarily in terms of their strikeouts (K%) and walks (BB%) through their first X number of games, with some other statistics incorporated as well. SSNS is not the be-all, end-all of player performance, but knowing we’ve seen a player “do this before,” as they say, is enough to calm one’s turbulent heart and mind.
