Jun 4, 2011; Atlanta, GA, USA; Georgia Tech Yellow Jackets designated hitter Daniel Palka (32) hits a home run against the Southern Miss Golden Eagles during the second inning in the Atlanta regional of the 2011 NCAA baseball tournament at Russ Chandler Stadium. Mandatory Credit: Dale Zanine-USA TODAY Sports
In March, on this site, I introduced “Tool WAA“, which was an attempt to use college baseball statistics to predict MLB success. With the MLB draft coming up and the college regular season over, I wanted to use the statistic to rank draft eligible players. So I only looked at ones that were Redshirt Sophomores or older (i.e., at least 3 years in college so they are eligible for the draft once going to a NCAA school), and only ones that had at least 100 plate appearances in 2013 (for most of the players, when it was possible, I used their career college numbers for the stats). I also only looked at players from what you might call the 5 major conferences, the ACC, SEC, Big 12, Big 10, and Pac 12. There are prospects in the non-Major conferences of course, including some really high rated ones like Michael Lorenzen or Kris Bryant, but I only tested the Tool WAA in a Major conference, and it isn’t fair to compare Big Sky statistics to SEC statistics because the strength of competition is different. If you recall in the initial article, things like OPS and K-BB did not test well, meaning they weren’t very predictive. HR % and Speed Score were the things that tested the best. So in this version of Tool WAA, I am only using those two statistics. I am also subtracting the simple Speed Score by 5 and the HR % by 2.6 %, just like I did in the initial post, which is why most players will have negatives. So we are measuring power and speed. It is a simple way to evaluate prospects statistically that I think can be a helpful way when used with scouting and not used in a way that is too binary. What I found when doing this is that there are very few college players that hit for both power and have speed. According to this measure, there were just 12 that had at least the average threshold of power and the average threshold of speed. There are 276 players on the list, too many to put in this post, so what I have done below is posted the top 20 in Tool WAA:
Name   College   Conference   Speed Score %   HR %   Simple Tool WAA
Daniel Palka   Georgia Tech   ACC   2.24   3.31           5.55
Max Rossiter   Arizona State   Pac 12   -3   -1.53          4.53
Aaron Cornell   Oklahoma State   Big 12   4.84   -1.55        3.29
Hunter Renfroe   Miss ST   SEC   -0.37   3.4                          3.03
Tyler Horan   Virginia Tech   ACC   -0.69   3.48                    2.79
Austin Wilson   Stanford   Pac 12   1.55   1.2                        2.75
Brett Williams   NC State   ACC   3.22   -0.56                       2.66
Pat Blair   Wake Forest   ACC   3.32   -0.76                           2.56
Matt Conway   Wake Forest   ACC   2.29   0.18           2.47
Cody Stubbs   North Carolina   ACC   1.4   1.03                  2.43
Matt Oberste   Oklahoma    Big 12   0.33   2.04                    2.37
Justin Ringo   Stanford   Pac 12   2   0.25                2.25
Michael O’Neill   Michigan   Big 10   2.58   -0.45               2.13
Andrew Rash   Virginia Tech   ACC   -1.125   3.21             2.08
Stephen Talbott   Purdue   Big 10   3.52   -1.52                     2
Josh Scheffert   Nebraska   Big 10   1.44   0.42                  1.86
Chris Marconcini   Duke   ACC   1.07   0.43                        1.5
Michael Camporeale   Washington   Pac 12   0.75   0.67   1.42
Thomas Brittle   Clemson   ACC   2.82   -1.42            1.4
Shane Kennedy   Clemson   ACC   2.12   -0.9                     1.22
If you want to view the whole list, you can by clicking here.