claydavenport.com
Although things don’t look much different, if we dive down under the hood you will be able to see that I have been a lot of work in the background. And I guess one of the best ways to demonstrate is to look at this page here:
http://www.claydavenport.com/ht/TORKELSON19990826A.shtml
I am now able to provide a stat-based projection on 2020’s #1 overall pick, Spencer Torkelson, based off of his college statistics. Without them I had literally nothing on Torkelson to base any stats. With them – that is a projection that makes him a very legitimate callup.
And he is not alone. Adley Rutschmann jumps from a .240 eqa projection to .284 – on the basis of his college pedigree. Andrew Vaughn likewise goes from the mid-230s to the mid-270s – because now I know he had a pair of .300 translated seasons in college.
I’m still early in my use of college stats – haven’t gotten fielding info in yet, which is going to make bring Rutschmann’s drop once it knows he’s a catcher – but it seems to work as well as minor league numbers, with a couple of caveats.
I haven’t backed these up with a formal study yet, but it certainly looks like there is a very tendency for a player’s final year in college to be a lot better than his prior years. Rutschmann and Torkelson both fit that pattern. I think that pattern will be especially pronounced for 2020 – play was interrupted typically before in-conference games started, meaning that teams (from the major conferences, at least) played unusually weak schedules. The way that I calculate the difficulties, averaging across different years, is going to mask that weakness.
The second caveat is that players appear to underperform their college numbers in their first taste of pro ball, but tend to recover towards their college averages in later seasons. There is this double whammy of a player’s final college year coming in too hot, and his first pro year too cold, that creates a LOT of distortion.
About the difficulty ratings. So the ratings I am using here see the top three college conferences as the Southeastern, the Pac-12, and the ACC. This is in line with the number of players who have gone on from these conferences to play in Organized Baseball. I counted 761 SEC players in OB ranks since 2011, 611 ACC players, and 565 from the Pac-12. Their ratings, of .498, .458, and .478 are comparable to the short-season Northwest (.469) and New York-Penn (.514) leagues (all of these numbers area average from 2015-2019). Your Midwest and Sally leagues in the .55-.57 range, the high A leagues are .63 give or take, with the majors sitting at just above 1.00 right now.
Here’s how the top 16 conferences, ranked by number of OB players, rank:
Conference Players Diff
--> NY-Penn .514
Southeastern 761 0.498
Atlantic Coast 611 0.458
Pacific 12 565 0.478
--> Northwest .469
--> Pioneer .464
--> Appalachian .462
Big 12 464 0.432
Conference USA 364 0.443
Big West 347 0.433
Big 10 340 0.415
--> Gulf Coast .423
--> Arizona .418
Sun Belt 274 0.407
West Coast 263 0.420
Southland 258 0.388
Big East 266 0.432
Western Athletic 242 0.372
Missouri Valley 219 0.432
Mountain West 217 0.435
American Athletic 214 0.413
Atlantic Sun 205 0.411
There is a .81 correlation between the number of players taken from each league and its quality, so the draft appears to be resosnably efficient The ratings do tend to keep dropping from there. By the time you get to, say, the Wisconsin Intercollegiate League, made up of the smaller schools of the University of Wisconsin system (like Oshkosh, Stevens Point, or Whitewater), the rating is coming in at just .130.
Hat tip to baseballreference.com, who really pulled these collegiate numbers together. My task was just to pull them together in a sensible fashion
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