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Thread: Does FG Overcorrect Against Pitchers in Calculating FV

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    Does FG Overcorrect Against Pitchers in Calculating FV

    One of the findings that comes out of analyses of prospect values is that pitchers have tended to be overrated relative to hitting prospects. FG's article on future value shows this:

    https://blogs.fangraphs.com/scouting...couting-scale/

    FG's study itself is based on Baseball America's Top 100 list from 1996 forward.

    I was curious to see if BA had made any sort of adjustment by reducing the proportion of pitchers in their Top 100 lists. That would be one way to adjust for the fact pitchers have been overvalued relative to hitters. I looked at the proportion of pitchers on the BA Top 100 lists during the 1996-1998 period and compared that to the most recent 3 years (2017-2019). What that shows is there hasn't been an adjustment. In fact the proportion of pitchers has risen from 42% in the first 3 year period to 44% in the second 3 year period.

    FG itself adjusts for the higher bust rate for pitchers by separately calculating FV for pitchers for their given ranking. So a pitcher ranked with a 50 FV is worth less than a hitter with the same ranking.

    That's fine as it goes.

    But here is the issue. FG tends to have pitchers make up less 40% of its list (which has a Top 130). So it would appear to have made a second adjustment.

    Both adjustments are fine on their own as a way of reflecting the higher bust rate of pitchers. Adjust downward the proportion of pitchers on your list (whether top 100 or top 130). Or give pitchers a lower score relative to hitters with the same rating. But doing both makes it likely that they are over adjusting against pitching prospects.
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    Nope...

    https://blogs.fangraphs.com/an-updat...ect-valuation/

    A few years ago pitchers and hitters of the same FV level used to have significantly different dollar values. The adjustment was done to bring those dollar values closer together.

    Position scarcity isn't taken into account (the real logic behind the "pitchers get hurt all the time, so stock up on them" cliche), but pure contribution to wins is captured.

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    Quote Originally Posted by Enscheff View Post
    Nope...

    https://blogs.fangraphs.com/an-updat...ect-valuation/

    A few years ago pitchers and hitters of the same FV level used to have significantly different dollar values. The adjustment was done to bring those dollar values closer together.

    Position scarcity isn't taken into account (the real logic behind the "pitchers get hurt all the time, so stock up on them" cliche), but pure contribution to wins is captured.
    OK. I think I understand what they do when they merge all the buckets in one list. It makes sense.
    Last edited by nsacpi; 08-01-2019 at 01:01 PM.
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    Quote Originally Posted by nsacpi View Post
    OK. I think I understand what they do when they merge all the buckets in one list. It makes sense.
    It used to be off by much more before the adjustment was made:

    https://blogs.fangraphs.com/valuing-...100-prospects/

    I think it's pretty obvious why they have to wait for prospects to actually produce MLB WAR before a study like this can be completed.

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    I have a question. Is it just me, or do the bust rates for upper echelon prospects seem to be dipping pretty substantially over the past few years? That is purely my perception, but if it is the case then its probably due to improvements in analytically driven scouting and us having more statcast data on these guys. Even if this isn't currently happening, I'd imagine that it will be true in the future when we have more objective data to analyze these guys. So if this is true, do we need to make an adjustment to the surplus value formula for prospects that reflects this improvement in player evaluation? Or are the bust rates for prospects updated year to year within the formula?

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    It seems like the Braves have had excellent luck on top position prospects, while other teams haven't been so lucky. Brinson, Moncada took a while, and several others. Perhaps the Braves recent success is influencing the perception.

    However, it is possible teams are better now at evaluating these guys than they were 5 years ago. If that's the case, then a lot of this data is outdated since it takes so long for prospects to prove how valuable they ultimately became.

    Additionally, some teams like the Dodgers with position prospects and the Yankees with pitchers seem to very good at spinning mediocre prospects into MLB contributors. So, for example, a 45 pitcher with the Yankees is probably going to produce more than a 45 pitcher with the Mariners.

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    Quote Originally Posted by BeanieAntics View Post
    I have a question. Is it just me, or do the bust rates for upper echelon prospects seem to be dipping pretty substantially over the past few years? That is purely my perception, but if it is the case then its probably due to improvements in analytically driven scouting and us having more statcast data on these guys. Even if this isn't currently happening, I'd imagine that it will be true in the future when we have more objective data to analyze these guys. So if this is true, do we need to make an adjustment to the surplus value formula for prospects that reflects this improvement in player evaluation? Or are the bust rates for prospects updated year to year within the formula?
    Bust rates have declined over time. To the extent to which the surplus value formula lags that it is understating the value of current prospects. It should also be noted that the average major league player has been getting younger (much more so for hitters than pitchers). This also works to concentrate value in the pre-free agency years. To the extent the surplus value calculations are based on "dated" information, this also will cause the value calculations to understate the value of current prospects.

    Fifteen years ago the average age of hitters (weighted by # of at bats) was 29.3. This year it is 28.1. That's a pretty big change, and I'm sure valuation of prospects (which uses data that goes back 20 years or more) doesn't fully reflect something like that. It's likely the smarter teams use fewer years of data so that their valuation models respond more quickly to those kinds of shifts.
    Last edited by nsacpi; 08-01-2019 at 01:36 PM.
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