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  1. I’m really interested in seeing how this plays out. I do have one question. Should there be some type of discount factor for when a prospect is expected to come up? Should someone who we assume is a 2-WAR player in 2010 be valued differently than someone who would be a 2-WAR player in 2011. Could it be something like 2 / (1 + r)^x, with r being the discount rate and x being # of years away?

    Comment by JoshEngleman — March 9, 2010 @ 11:30 am

  2. Josh: Yes, this is something we’ve talked about internally. 2 WAR in 2010 is a more valuable thing than 2 WAR in 2011, so prospects closer to the show should be valued higher.

    If you want to expand on your formula idea, I’m all ears.

    Comment by Bryan Smith — March 9, 2010 @ 11:32 am

  3. Why does the “rosy” prediction include the “risky” UZR value?

    Comment by Barry Reed — March 9, 2010 @ 11:59 am

  4. Hmm? The rosy prediction is that Brown will improve his defense to what some scouts think it could be.

    Comment by Bryan Smith — March 9, 2010 @ 12:03 pm

  5. Is the WAR you’re projecting here for this year? If so, then in addition to discounting it for later years, wouldn’t you also want to account for improvement during that extra year in the minors?

    If I remember one of your earlier articles on this, are you thinking about doing something with “comparables”? As part of that, would you look at a different groups of comparables? In other words (and I’m just thinking out loud), from the 25 similar top 30 outfielders, the 10 that got regular playing time would form one group of comparables (the 8 with partial time would be another group, and the remaining 7 a third group), which you could use to project when the prospect might reach the majors, playing time, etc…

    Comment by Barry Reed — March 9, 2010 @ 12:06 pm

  6. My bad, I meant positional adjustment and typed UZR…

    Comment by Barry Reed — March 9, 2010 @ 12:07 pm

  7. I honestly have no formula idea whatsoever. I was basically taking the one thing I actually remember from my finance courses in college and applying it here. I wouldn’t know where to begin in terms of figuring out the a good discount rate. I’m guessing it would basically be some type of trial & error which fits the “smell test.” Enough people talking about it would likely bring up number that works, though.

    Comment by JoshEngleman — March 9, 2010 @ 12:09 pm

  8. By the way, here’s the list of BA-ranked tall outfielders from 1990-2004.

    6-3: Juan Gonzalez, Mark Whiten, Tim Salmon, Ray McDavid, Vladimir Guerrero, Richard Hidalgo, Abraham Nunez, Austin Kearns, Delmon Young, Jeremy Hermida
    6-4: Hensley Meulens, Marc Newfield, Mike Kelly, Cliff Floyd, Shawn Green, Ben Grieve, Brian Hunter, Josh Hamilton, Joe Borchard, Rocco Baldelli, Jeff Francoeur
    6-5: Dave McCarty, Jermaine Dye, Alexis Rios
    6-6: Mike Restovich

    Comment by Bryan Smith — March 9, 2010 @ 12:09 pm

  9. Barry: No, these projections are just what his team-controlled years might look like. Josh’s point is that if we have the assumption that he’ll produce 2 WAR per season, it’s more valuable in 2010-2015 than in 2012-2017. And he’s right.

    To your comparables point, if I understand you correctly, I agree. I wouldn’t separate them into groups, per se, but use all the different career paths to model what Brown’s could look like.

    Josh: I hear you, and that’s where I’m at, too. Thanks for the reminder of that finance lesson — I think it might be a good quantitative place to start.

    Comment by Bryan Smith — March 9, 2010 @ 12:12 pm

  10. If you project him to be a 2 WAR player based on the current information and project that he won’t be in the majors for 2 or 3 more years (and hence reduce that value), I presume that you reassess his value the next year to include how he does this year in the minors (progress vs. regress)… My point is that his value appears to be less now the further away he is from the majors, but your assessment of his WAR might go up (or down) as he gets closer to the majors…

    While I agree with the discount rate idea, I think the numerator isn’t fixed…

    Comment by Barry Reed — March 9, 2010 @ 12:19 pm

  11. Wouldn’t statistical analysis of top prospects be better than physical?

    i.e. Dominic Brown had a 12% walk rate last year in A+ ball. How many top-100 prospects have had a rate around that as a 21 year old in A+, and how does that rate move as the player moves up through levels (Make sure to park/league adjust as well, obviously)?

    Do that for BB%, K%, BABIP, HR, 2B/3B and you can then project wOBA.

    Seems to me that that would be better than physical. Physical doesn’t show what kind of batter that’ll actually be.

    Comment by Nny — March 9, 2010 @ 12:27 pm

  12. Of course.

    But I knew this piece was going to run longer than a typical post — both in words and time-to-write — so I went with something quick that would illustrate my point just the same. When we get a more strict understanding of what we want to do, this will get far more scientific.

    Comment by Bryan Smith — March 9, 2010 @ 12:29 pm

  13. Bryan, gotta admit I’m really intrigued right now by this series. Nny has done this sort of work at Marlin Maniac (linked in both our names) and it really helps with valuing prospects in the way they should be valued.

    I think Victor Wang has done work on how to discount WAR in future years, and that may be a place to start. I’m not sure if his adjustments in prospect valuation analysis are estimates or more rigorous calculations however.

    Comment by Michael — March 9, 2010 @ 2:04 pm

  14. I’ve been hearing that the MLE’s done by Brian Cartwright for his Oliver projection system work in a similar way. We can break down a player into certain category types, find how players of that age/level progress through the minors and translate at big league levels, and estimate an approximate number for that characteristic. It still probably involves some fudging with scouting analysis, but it’s definitely in the cards.

    Can’t wait to see more, Bryan.

    Comment by Michael — March 9, 2010 @ 2:06 pm

  15. Michael or anyone else: Send me a link if you have it to Victor’s work in this area.

    I believe in collaboration all the way, and really what I want to do is come up with a system that organizes all the great work done before me into a way that changes people’s approach to prospects.

    Comment by Bryan Smith — March 9, 2010 @ 2:10 pm

  16. Yeah, that’s definitely more towards the field of what I am interested in. I think that that would be for better use than what MLEs are (Which are “This is how he would have done if he was in the majors last year”).

    Also, I don’t think I’ve read anything on this but I’m sure you’ve thought about it, injury would play a huge role in WAR those first 6-7 years. I imagine that’d make position prospects a lot more valuable. There’s obviously Will Carroll’s work with BP that could help figuring that out.

    Comment by Nny — March 9, 2010 @ 2:22 pm

  17. The reason I’ve yet to talk about pitchers is because of the injury thing, and it intimidates the hell out of me. But I think if we use a valid field of comparables, injury will be accounted for with the success/failure stories. We might have to do some adjusting here and there, but the comps should do most of the work.

    Comment by Bryan Smith — March 9, 2010 @ 2:34 pm

  18. I like the concept of calling Brown a 1.1/3.8 prospect, with 1.1 being a rough estimate of the weighted mean and 3.8 being the reasonable projection as a regular.

    To be clear, if you looked at Chase Utley after his age 24 season in 2003, I am guessing that he would have been something like 2.0/4.0, and that in essence the rosy peak is really a 75th percentile rather than a 90th percentile estimate. Have I got this right?

    Comment by Mike Green — March 9, 2010 @ 5:19 pm

  19. Mike: Without specifically going into Utley’s case, I think you have it right. I don’t know what percentiles I would say these are, but I think 50th/75th is certainly close enough.

    Comment by Bryan Smith — March 9, 2010 @ 5:36 pm

  20. I’d be careful throwing discount rate into prospect analysis. The concept of players as assets (worth more in the future but less now) is something that really only applies when looking at trades.

    If I remember correctly Victor Wang’s work already included bust potential. Under his conclusions, you could calculate who won or lost a trade by using this methodology (numbers made up for example):

    “The Cubs trade a 1/2 season of Ted Lilly for the No. 35 prospect, with the Cubs paying Lilly’s salary. We expect Lilly to be worth an additional 1.5 wins which for Tampa Bay would improve their playoff odds by 20%. The No. 35 prospect has historically produced 2.5 WAR over the first six years of his career (this number includes all the #35s who didn’t make it so bust potential is built in). Chicago wins the trade because increasing your playoff odds 20% is worth $5 million while 2.5 WAR over 6 years is worth $7 million, but hey flags fly forever, right?”

    I guess I just want to point out if we’re viewing players as assets (and applying discounted rates, etc.) you need to take into account a guys 25th percentile (and below) projection of 0 WAR because he never makes it to the majors.

    Comment by Trev — March 14, 2010 @ 1:59 pm

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