MLB Prospects Statistical Analysis-Minor League Odds-Off the Radar

In a previous post on this site, I used basic minor league data from all the 1st baseman to have played in the Majors since 2000 to see which were the most predictive to MLB success and created a very simple odds system (and used all the qualified 1st baseman as an example, and elsewhere, looked at the AA and AAA Mariner prospects using the odds system). Here, I am making a more complete list of players, looking at all the players that had at least 100 plate appearances in either AA or AAA. They must have less than 20 games of MLB experience. and must be 27 or younger (there were 475 players that qualified in all). Since the odds are purely offensive (the odds are the chances, percentage wise, that they would be successful, 107 wRC +, or average 1st baseman, as the baseline, if given the chance in the Majors), I wanted to get a complete look at the players, so I also used Speed Score and FRAA to measure their baserunning and defensive abilities. You can view and download the full spreadsheet by clicking on this link, but if you are feeling lazy, here is a screenshot of the top 20 players according to very simple formula that weighs 2012 FRAA, Speed Score, and odds equally:

Remember, the odds measure the odds that they would succeed (at a 107 wRC + pace) if placed in the Majors, and does not account for whether or not they will make the Majors (but that is why I use AA and AAA players, as they are a call a way from the Majors). A good number of these players may never play in the Majors, this just measures whether or not there is reason to believe that they would succeed if placed in the Majors (reading the original post linked to above explains this a little further). This also isn’t quite scientific. I’ve seen the vast majority of these players play, at least on video, and certainly don’t agree with the order of the players. Kalian Sams is not the Mariners’ best upper level prospect. However, this was not designed to be some kind of prospect ranking or to replace scouting in anyway. This is simply another way, a more data driven way, to look at prospects.

One thing I have noticed is that many teams take players in the late rounds, especially catchers, out of college (usually seniors), and move them through the system extremely quick even if they are struggling. Since minor league plate appearances play such a big role in the projections, this seems to create a slight bias, as those players, who aren’t actually good, are a little overrated. It is a glitch, but I don’t think it is a big deal. The rankings are biased against catchers, as catchers are usually slower and FRAA is not a very accurate statistic (if it is at all) when it comes to catchers. I kept them in there and didn’t adjust the catchers at all, but keep that in mind. Any suggestions, comments, or corrections are welcoming via commenting below, Twitter, or email (clinthulsey@my.unt.edu).