Pitcher Busts
Ryan Anderson (injuries, high school pitcher)
Bobby Bradley (injuries, high school pitcher)
Jovanny Cedeno (injuries, free agent Dominican Republic)
Ben Christensen (injuries, college pitcher)
Chris George (sucked, high school pitcher)
Adam Johnson (sucked, college pitcher)
Nick Neugebauer (injuries, high school pitcher)
Bud Smith (injuries, junior college pitcher)
Hitter Busts
Joe Borchard (tools bust, college)
Dee Brown (bust, high school)
Drew Henson (tools bust, high school)
Abraham Nunez (Age-Gate, Dominican Republic )
Jose Ortiz (Dominican Republic, played well in Japan)
Thoughts:
A) Be very skeptical about football playersB) Injuries kill pitchers
C) Talent can come from anywhere. The two best players on this list, Pujols and Oswalt, both came from the junior college ranks and were low-round picks (13th for Pujols, 23rd for Oswalt
D) Some tools guys pan out, others don't. Some sluggers pan out, others don't. Obvious, but true.
E) Even now it is too early to fully evaluate this list. We don't know what will happen with Cust, Hamilton, and Betemit in particular.
I like to look back at old prospects lists and see how accurate or how far off different systems are when predicting major league success, and then break it down like Sickels has done and determine what major factors are behind each bust or break-out player. Like Sickels, I think the #1 threat to all pitchers is injury, while the #1 threat to hitters is the toolsy or slugger type prospect hype that is hard to live up to. As I've spent time going over these types of lists I've also come up with my own explanations for player performance or lack thereof that I think are also important to note.
1. Inappropriate projections based off of body type and not based off of performance.
Whenever I read a scouting report that starts out with something like, "Reminds me of a young ____," then I'm automatically skeptical. Any scout that bases his (or her) opinion of a prospect off of what a player looks like is a scout that is too caught up in appearances and biases and isn't seeing what's really important about a player. I know it sounds like I'm making this too basic, but if a hitter looks, talks, acts, runs, swings, smells and tastes like Ken Griffey Jr., but his mechanics only allow a bat speed that is 65% of Ken Griffey Jr.'s bat speed, then all that exterior stuff is just a deceptive facade. In reality, a hitter or pitcher is simply a sum of mechanical parts being operated by a nervous system rooted in a base of mentally recorded experiences. There are so many minor motions that go into a swing or a throwing motion that it's really only fair to base a scouting report off of appearances only if it is paired with motion detecting equipment that can give a fair and accurate read on the end result. Radar guns are helpful in some regards, but there is some very amazing computer based motion detection equipment out there that I don't think is used adequately when judging hitters, and consequently a lot of guys are touted as the next big thing when really they show very few similarities to established players.
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Besides simple mechanics, I think a lot of players are judged based off of "tools" and projected development without proper analysis of already apparent strengths and weaknesses. Just as an example, in 2001 Corey Patterson was ranked the #1 prospect in baseball, with Albert Pujols ranked as the #18 prospect, and while some would argue that Patterson was a bust and Pujols was a surprise break-out, I would argue that the opposite is true.
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To the far-left we have our offensive metrics, followed by the
R-Squared, as well as the
Standard Deviation. For the uninitiated, R-Squared is another term for "coefficient of
determination"--a measurement of correlation.
The higher the R-Squared total, the greater the correlation, and thus, the more consistent the metric. Depending on how it's being used, an R-Squared of below 0.5000 is typically considered too low to justify any sort of predictive value. Standard deviation, meanwhile, is simply a measure of variance--the higher the number, the more volatile the metric.
In simpler terms, the numbers that are most accurate in predicting year-to-year consistency are K%, BB%, HR% and ISO. Going back to our Pujols and Patterson comparison, we see that the differences in K% and BB% are actually very significant, especially when you consider the weight that K% has in predicting year-to-year consistency. I don't want to spend too much time breaking down the numbers and boring everyone with weighted statistical data, but I wa nt to make it clear that by judging a player's past performance, you can get a pretty accurate picture of what their chances at success at the big league level are, and projected development should be replaced with realized development. With that in mind, I think Patterson has developed about like his stats suggest he would, meaning that he was a victim of hype rather than a simple bust, and Pujols has lived up to his stats as well.
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