BP Unfiltered

No, we're still working on the Darvish projection along with other Japanese and Cuban players. We'll have an update on them soon.

Love going through these PECOTA predictions. Any chance there could be another category listed? My league uses batting average against as a counting stat. It would be great if this was included in PECOTA.

Thank you for adding slugging percentage against in the PFM. Your response to my request was great. I believe both batting average & on base percentage against have also been added to the PFM.

I know I'm not the first to point this out, and I'm intentionally bringing this up in a low-traffic thread, but young players are only being compared to major-league players. If you sort the position players on age, every single 19-year old is compared to Robin Yount, Wayne Causey, and Ed Kranepool.

I understand that an immense amount of work must have gone into converting PECOTA from Nate Silver's initial Excel spreadsheet-palooza and in maintaining/updating the process since - and I respect the hell out of everyone at BP who's gone through this every year - but simply put, PECOTA hasn't been "right" since it left Nate's hands. There are a few tangible issues - the one raised here and another I repeatedly raised in a Beta testing page (and over e-mail) a couple of years ago that was ignored - and many more intangible "that just ain't right" issues (e.g. Rockies' position players last year).

At this point I use PECOTA as just another data point to provide a forecast (among the swath of other projection systems), and when PECOTA provides an outlier I assume it's the result of an error rather than some prescient bit of information (e.g. the famous Wily Mo Pena forecast or Brandon Webb's insane comparable list the year he got called up).

I've been pretty patient with the process - at least I think I have been - but at this point I'm just sad. I've given up hope.

Some explanations on how the comps are used:

What we do first is come up with a “baseline projection” that takes into account a player’s past performance, accounting for some regression to the mean. (We break it down based on components, so that a player with a high strikeout rate is treated differently than a player with a low strikeout rate, even if things like batting average are the same.)

Once those baselines are generated, we find comparable players to those baseline forecasts (as well as to some attributes not reflected in the baselines, such as age, position, height and weight). We look at the performance of the comps going from their baselines to the following season to come up with composites-based age adjustments (internally to PECOTA this is referred to as a “cage” forecast). We assess the reliability of the composite-based aging curve, and use that to regress it towards a generic age adjustment for players at that age (we refer to this as a “genage” adjustment). The less reliable a composite-based age adjustment is, the further it’s regressed.

I can trace my loss of confidence in the comparables back to the point where minor leaguers were taken out of the potential comps list.

I'm sure there were valid reasons for doing so, but still -
I'd rather know a guy is comparable to some minor-league shlub I never heard of than have the implication out there that Justin Christian is Manny Mota, or Everth Cabrera is Derek Jeter, or Koby Clemens is Mark Teixeira, or every 19 year old in the minor leagues is Robin Yount (or perhaps Ed Kranepool).

I mean, if a guy walks like a Stubby Clapp and talks like a Stubby Clapp, is it really helpful to have someone tell me the dude's comp is Robin Ventura?

As a keeper-league drafter, I want to know when I'm in danger of getting the Clapp.

Is there a way in PFM to have it just inflate the values based on the following formula?
New$$ = Original$$ x (DollarsRemaining/ValueRemaining)?
I set centric inflation to '0' and inflation 'YES', however, of the remaining players, Closers keep creeping up the dollar value rungs once all my keepers have been added. Originally only one closer was worth more than a certain player, however now 4 closers are. With centric inflation set to '0', shouldn't the ranking of all remaining players in the auction stay constant?

Can Chris Sale's projection be correct? His ERA starting this year will stay the same as it was when he was a reliever in 2011? His k rate will actually increase slightly? I am a huge fan of Sale but this seems like a best case scenario, maybe his 90% performance, not the expected weighted mean. Please take a look at this projection. Thank you!

Where can I find the multi-year projections on the individual PECOTA cards? Is this still a feature? I've searched in vain.

I get it that "the model is the model" but when BP the book comes out and Troy Tulowitzki's comps are Joe Millette and Craig Gerber and Hanley Ramirez, and Justin Upton's are Gene Hiser, Carlos Quintana and Jason Werth, I mean, that is just non-sensical. How is someone supposed to interpret the comps?

And, there seem to be many player comments that are like the one for Ubaldo Jimenez - where the gist of the comments is positive ("Tribe will be glad they locked him up with affordable options!") but the 2012 projections have him regressing from what was a down year in 2011 (yet the author calls him an "ace" with a projection of 10-8, 3.86, WAR 1.5 . . .and comps of Jared Burton, Aaron Heilmann, and Ray Narleski. Jared Burton??? He pitched 164 innings in his entire career . . . Ubaldo is at 916 and counting.

Could someone give me some insight into Marmol. Why does PECOTA rank him so high and his projected numbers are way different than anywhere else?

Thanks in advance for the info.

when is the next PECOTA spreadsheet release? it has been about 2 weeks.

are any PECOTA spreadsheet updates coming? i have a draft approaching and need an ETA