Carson Cistulli's Winter SCOUT Stats
For a couple of years, Carson Cistulli has been looking at the winter leagues through a metric he calls SCOUT. The idea is that a lot of our favorite stats don't really mean that much in the small sample sizes you get in the AFL and winter leagues. But you can look at some statistics that stabilize pretty quickly: strikeout rates and walk rates, as well as home run rates for hitters. Cistulli has put them together in a metric he calls SCOUT.
By this metric, some Bucco prospects have been having pretty decent offseasons:
Robbie Grossman led the league's hitters in SCOUT, by an enormous margin. As if we needed another stat to tell us that he owned this fall. Get well soon, Robbie!
Gerrit Cole was fifth among pitchers -- remember, it doesn't include HR rates for pitchers (or the all-star game). Nathan Adcock was seventh.
Looking at the whole league's stats, Jarek Cunningham was 15th among hitters, virtually tied with Derek Norris and Darin Ruf. Danny Hultzen, in case you're wondering, was 15th among pitchers. The last-ranked hitter was one Mike Trout, which might tell you not to take this too seriously.
In the Dominican Winter League, Matt Hague is third in batter SCOUT, thanks to excellent walk numbers and not great power; which probably won't answer too many questions about him. (He's behind career minor leaguer Ricardo Nanita and SF 1B rookie Brandon Belt.) Chris "Bulletproof" Leroux is seventh in pitcher SCOUT. He's third among starters, behind Everett Teaford and Fernando Abad.
This is a FanPost and does not necessarily reflect the views of the managing editor (Charlie) or SB Nation. FanPosts are written by Bucs Dugout readers.
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Interesting
From the link…. “… allow me to introduce what I’ll call SCOUT. To devise it, what I’ve done is to find the regressed strikeout and home-run rates (xK% and xHR%) for all the qualified batters in the AFL. Then, for each player, I’ve found the z-score (that is, standard deviations from the mean) in xK% and xHR%, and averaged them (i.e. the z-scores) together. SCOUT is the result of that.”
To an extent, this stat seems similar to a qualitative assessment that we do a lot, especially early season in the majors or when a player get promoted mid-season and gets off to a blazing/abysmal start. E.g., "sure player X is off to a “great start” (say a couple home runs, etc), but he’s striking out a lot and he’s being supported by an unsustainable BABIP." Would that be accurate?
sounds about right
All I know is what I read in the link myself, and there’s the caveat that often in those small starts the sample size isn’t even big enough for these stats to mean anything.
Not actually affiliated with whygavs.
by WHYG Zane Smith on Nov 26, 2011 7:25 PM EST up reply actions
I think it would be interesting to do a study on what the average length of a “hot” streak is. For instance, when a player is over-performing based on his underlying K, HR, BABIP, and walk rates, and our sample size is like 80 at-bats, how long should we expect that to last, based on some sort of quantitative analysis. Monthly splits are nice, but they tend to aggregate things to simply I think.

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