Archive for Buxton

I think there are not one, but many, questions because there are not one, but many, ways Adalberto Mondesi and Byron Buxton are similar.

Here’s one answer to one possible question:

who has the best fantasy season in 2019?

— Alex "Oxlade" Chamberlain (@DolphHauldhagen) August 29, 2018

I can’t say I’m surprised, but I’m kind of surprised. I asked this question very deliberately, its design not remotely accidental, the response options dripping with subtext. Mondesi, with his elite speed, decent power for a speedster, and very questionable contact skills, in 2018 is almost a dead ringer for Buxton in 2017. Mondesi doesn’t quite have Buxton’s baggage — he doesn’t carry the weight of expectations of a No. 1 prospect — but he has his own, continuing a familial legacy. But they do have a lot in common, as aforementioned, which can be summarily boiled down to this great quip from our Eric Longenhagen: “wholly untamed physical abilities.”

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I wrote a feature for a forthcoming fantasy baseball magazine about players with the potential to make or break your season. Due to space constraints, some of the copy lay on the cutting room floor as the magazine shipped to print. Rather than let it go to waste, I figured someone may enjoy reading my leftover snippets for players with volatile outlooks for the 2018 seasons. (The rest you’ll find on physical and digital bookshelves sometime in spring.)

I’ll present each blurb as is and, afterward, provide links to relevant work I’ve written related to that player as well as any final thoughts I couldn’t originally fit into my word count limits. It’s worth noting the target audience includes fantasy baseball enthusiasts of all skill levels, some of which invariably fall short of those of typical RotoGraphs frequenters. Alas, I made my best effort to conduct worthwhile analysis without getting overly technical.

Ordered roughly by expected average draft position (ADP).

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#2: April 24
#1: April 13

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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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.

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