Now I am sure this is not rocket science to most of you and you have given this topic a thought before.  However, I am sure it never went beyond the stage of simply being a thought in your head.  I have taken the liberty of assigning some numbers to this hypothesis and unsurprisingly, the hypothesis proves true.

Outfielders

The first position I decided to take a look at was the outfield because there is an abundance of players whose numbers can be analyzed and when dealing with statistics, having a large sample size is always important.  For my top tier consistent players I chose Grady Sizemore, Carlos Beltran, Carlos Lee, and Vlad Guerrero.  These players have all shown an ability to produce consistent numbers every year and as a result they routinely find themselves among the top players drafted.  I know this is no longer the case with Vlad because he is getting old, but for a number of years he could be penciled into the first round without a second thought.  The lower tier players included Magglio Ordonez, Jermaine Dye, Vernon Wells, and Pat Burrell.

The Numbers

To start, I want to explain that I removed years where the player suffered a significant injury and missed significant playing time.  If a player lost 300 AB’s, his counting stats will obviously be affected and this would skew the data.  When looking at the numbers, I examined the percent change between years for each player, as well the raw data.  I then took into account the averages and the standard deviation of these categories.  For example: for my top tier outfielders I would take the average of the percent change in their stats and the standard deviation of the percent change in their stats.  Then I would take the average of their raw stats as well as the standard deviation of their raw stats.  I then did the same with the lower tier players.  Unsurprisingly, the top tier players came out on top when it came to consistency.

Averages

The averages were important because it showed that the top guys are the top guys because they play the most games and get the most AB’s.  My top tier players averaged 594 AB/year, while the lower tier players averaged only 562, also playing in four less games per year.  This is important because in fantasy baseball it is crucial to maximize the amount of time your players are actually playing.  You don’t want a guy in an active roster spot who sits out an inordinate amount of games with minor injuries.

Standard Deviation

Now on to the juicy stuff, which is standard deviation.  The top tier players had data that was much closer together, as shown by low standard deviation numbers.  This means that they would consistently produce the same numbers every year and not hit 25 HR one year, 40 the next, and 20 the year after.  When making your lineup, you were able to mark these guys down for their expected numbers without doubting yourself.

Games and AB’s

The lower tier players had a standard deviation in games played that was 34% higher when examining the percent change between years and 24% higher when examining the raw data.  These players are not as indispensable to their teams as the star players and their playing time and spot in the batting order can fluctuate from year to year.  This is important because you do not want to draft a guy who batted third last year only to find out he has been dropped to sixth in the batting order for the upcoming season. 

Runs and RBI

Due to many factors, one of which being the fluctuating in batting order spot, the lower tier players also struggled to produce consistent stats in these categories.  In terms of the percent change between years data, the standard deviation was 36% higher for runs and a whopping 80% for RBI.  With these guys, you had no idea what kind of numbers to expect.  A perfect example is Ordonez in the 2002 and 2003 campaigns.  In 2002, he had 116 runs and 135 RBI, which he then followed up in 2003 with 95 runs and 99 RBI while accumulating more AB’s.  His batting averages and OBP were consistent and he slugged only slightly higher. 

Batting Average

This stat also had a very high standard deviation.  In terms of percent change between years, the lower tier players had a 73% higher deviation, and 32% when examining raw data.  This is something you have probably all experienced before.  You draft Burrell in the mid-rounds with high expectations, and he rewards you with a .209 batting average like he did 2003.  Or Jermaine Dye, who followed up his brilliant .315, 44 HR 2006 season with a .254, 28 HR stinker.  With elite players like Vladdy, you do not see these types of fluctuations. 

First Base

I also ran the numbers at first base with Albert Pujols, Miguel Cabrera, Ryan Howard, Mark Teixeira (top tier), Justin Morneau, Garrett Atkins, and Aubrey Huff (lower tier).  The results were similar.  Huff has proven that he can hit like Teixeira as he did in 2003 when he hit .311 with 34 HR, 91 runs, and 107 RBI.  However, he also showed that he can hit like Billy Butler (.280, 15 HR, 68 runs, and 72 RBI in 2007).  Meanwhile, Teixeira always hits like Teixeira.

Conclusion

While guys like Huff, Ordonez, and Dye have proven that they can put up first round caliber numbers, they are never drafted there because they have never been able to prove that they can do it every year.  First round picks are like betting on the Patriots against the Bengals. Barring a serious injury, it is a sure thing and you know exactly what you are going to get.  Meanwhile, the lower tier players are like a game of roulette, a lot of luck is involved.

What do you think of my numbers?  Are the sample sizes too small for them to be taken seriously?  Do you think that first round picks are drafted simply because they hit 45 HR and 130 RBI the year before?

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