Evaluating Prospects

The best way to evaluate baseball prospects at any level from high school to college to the international circuit to the minors is to send an army of good scouts to watch those players play.  Unfortunately, I don’t have that option.  Occasionally I do come across reliable scouting reports for certain Cub farm hands, but when I try to evaluate minor league players for Cubbies Crib, I have to rely almost entirely on statistics.

I’ve been asked a time or two what statistics I use to do this, and I have promised an article on the subject.  That article, if I wrote it as one, would be roughly the size of a small novel.  Instead, from time to time I’ll bring you some shorter pieces in which I highlight a particular metric I like to study and how it applies to the Cubs farm system.  These articles will be longer than you typically expect from Cubbies Crib, and there will be plenty of math along the way.

Today I’m going to try to compare hitters at different levels of the minors.  I’ll focus on first base, and on those players who might be called up to replace Carlos Pena should he be traded.

I will be comparing the offensive production of four first base prospects in the Cubs farm system: Iowa’s Bryan LaHair and Scott Moore, and Tennessee’s Rebel Ridling and Josh Vitters.

Since first base is a primary offensive position, and since I don’t want to write a book on just these four guys, I’m going to limit myself to OPS as a measure of their offensive production.  OPS is calculated by adding a players On Base Percentage and Slugging Percentage.

That gives us the numbers you see below.  All numbers come from Baseball Reference.

So, this clearly demonstrates that LeHair is the best offensive first baseman of the four, and that Rebel Ridling is second, right?  This also clearly shows that Josh Vitters might not be anywhere near as good as we think, since he comes in dead last, right?

Not so fast.

LeHair and Moore play in one league, and Ridling and Vitters play in another.  Each league in the minors has different characteristics.  Some league seem to favor pitching and some leagues seem to favor hitting.  Until we adjust these numbers for the league in which these guys are playing, we can’t draw any conclusions.

The average OPS in the Pacific Coast League (AAA) is 0.812.  The average OPS in the Southern League (AA) is 0.735.  Now I can take each player’s OPS and divide by their league average OPS.  A score of 1.000 means the player is right at the league average.  A score of less than 1.000 mean the player is below league average, and of greater than 1.000 means the player is above league average.  Note that I am not calculating OPS+ here.  That is a different, but very similar, calculation that I could (and probably should) do.  What I’m doing here is a quick shortcut that is a little easier to follow.  Just keep in mind that this is not OPS+, but just a league adjusted OPS.

Making that calculation gives us this result.

That changes things a bit.  Suddenly we see that Vitters is slightly above league average, so maybe he isn’t playing as badly as we first thought.  LeHair, on the other hand, looks even stronger.  If I were evaluating major league players, this is where I would stop.

But I cover the minor leagues, so I have one more adjustment to make.  This next part is probably going to be horribly controversial, but I haven’t thought up a better way to handle the topic.

In the minors, age matters.  Look at Ridling and Vitters.  Their number are similar, but Vitters is four years younger than Ridling.  When we are evaluating prospects, we have to consider the age of the players versus the average age of the league in which they play.  Vitters is young for Double A, and LaHair is old for Triple A.  Somehow we need to account for that.

Basically, what I am going to do is normalize their league adjusted OPS by an Age Factor.  I will calculate this Age Factor by dividing the average age for a player’s league by that player’s age.  A number great than 1.000 will indicate that the player is young for that particular league, and a number less than 1.000 will indicate that a player is old for that particular league.  By multiplying my Age Factor to the League Adjusted OPS, I will be scaling down the stats of players who are old for the league, and elevating the stats of players who are young for the league.  This is by no means a perfect system… or necessarily a good system… but it is an empirical system.  So let’s see what happens.

The average age for hitters in the Pacific Coast League is 27, and for the Southern League 24.5.  In the final table, you will see each player with their Age Factor calculated, and their Total Adjusted OPS

So when we take both the league and the player’s age into account, Vitters jumps from dead last to a solid second.  This drives home an important point, and one that is often overlooked even by national baseball writers.  When we consider the statistics of minor league players, particularly across leagues, you have to take to into account both the player’s age and especially the league in which that player is currently playing.  Working just off of raw statistics will give you consistently misleading results.

So do these numbers mean that LeHair is clearly better than Vitters or Ridling?  Nope.

Looking at these numbers, I take away the following:
– LaHair is having a great year, and he may not be as old for a minor league player as we first thought.  He deserves a chance to come up.
– Ridling is on pace to get a chance of his own one day.  His numbers are solid, if not spectacular.
– Vitters has some work to do yet.  An Age Factor of 1.167 indicates that he is fairly young for his league, but his Total Adjusted OPS is not quite as high as I would like to see it for a prospect of his calibre.  That said, it could be case of him getting off to a slow start.  If we repeat his calculations based on his June OPS of 0.826, we get a Total Adjusted OPS of 1.312, which is more in line with what I would expect.

Now for the disclaimers.  First of all, I should be comparing first baseman not against league averages, but against the league average for first baseman.  First base is a power position, so having a roughly league average OPS while playing first is nothing to brag about.  In other words, Moore’s numbers are probably weaker than they appear.

Second, using league average age is very problematic.  I think most evaluators would tell you that 24 is a little old for Double A, and by 27 you should probably be in the majors if you’re going to have a career as a major leaguer.  However, not all teams or evaluators agree on what league a prospect should be based on age.  Vitters is young for Double A by any metric, but probably not as young as he appears here.  On the other hand, my system is measuring a player against the people he is actually playing against.  Age adjustments have to be made, but using league average age to do it is by no means perfect.  Or necessarily good.  It is empirical, though, and that counts for quite a lot in my book.

Finally, I’m not sure how comfortable I am using these adjusted numbers to compare between all leagues.  For instance, in theory I should be able to compare LaHair to Reggie Golden, who is playing for Boise four levels further down in the minors.  I’m not convinced doing so would be accurate at all simply because of the differences in talent, ability, and polish between the two leagues.  I’m fairly comfortable looking across adjacent leagues (AAA to AA, AA to Hi A, and so on), and maybe even comparing across all the full season leagues… maybe… but I would hesitate to look more broadly than that.  However, the principles apply across all leagues.  We should always, at the very least, compare a player’s numbers back to the league average.  Each league really is different, and what is very good in one league could look rather bad if we do not keep the league context in mind.

Evaluating prospects with nothing but statistics is not the best way to go about it, but when that’s all you have to work with, you make the best of it.  This should give you an idea of how I go about it.  I will be bringing more of these features out in the future.