In the science community, a meta-analysis is what we do when we don’t want to do any work ourselves and instead want to take the work of a bunch of other people, tease the data a little, draw some conclusions that nobody had noticed before, and then pawn it off as our own.

Presenting the 2010 Tampa Bay Rays Top Prospects Meta-Analysis.

Notes on how the rankings were constructed are found at the bottom of this post. Notes on the final rankings can be found after the table…

A few notes on the final rankings

  • Last year, there were only two players (David Price, Wade Davis) in the top 5 of every list. This year, the top three are unanimous, although there is disagreement about the exact order. Nobody else is in the top 5 of each list (Matt Moore is top 5 in 5 of 6 lists).
  • Alexander Colome, Alex Torres, Kyle Lobstein, Matt Sweeney and Wilking Rodriguez are new to the list this season.
  • David Price (#1 in ‘09), Jeff Niemann (10) and Fernando Perez (13) are no longer eligible. Mitch Talbot (13) is no longer in the organization. John Jaso (11) and Jake Jefferies (14) fell off the list.
  • Tim Beckham had the biggest drop from last season (#2 in ‘09) and Desmond Jennings had the highest jump (6).
  • Of the players that appeared on every list, Matt Sweeney had the biggest disparity between high (5) and low (24) rank.
  • Four of the players have triple-A experience. Of the other rest, 7 have never been above single-A or short-season ball.

A few notes on how the Meta-Analysis was constructed

  • We included rankings from Baseball America, Baseball Prospectus, Minor League Ball, Biscuits Crumbs (Stacy Long), ESPN (Keith Law) and our own Trade Value Index.
  • Our Trade Value Index ranks players a bit differently. In addition to projecting how good a player will be, we also consider value to the organization. For more information see the most recent TVI post.
  • The final list includes all players that appeared in the top 10 of at least one list.
  • Some players did not appear on every list. For players not on a list, we gave that player a ranking of 2 spots lower than the lowest ranked player in the list for the purpose of calculating the final average.
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