As someone who’s basically fanatical about his fantasy sports, I’m often asked by people if they could have my draft lists. They figure "he knows what he’s doing and he spends a ton of time doing it, so of course whatever he has is going to be better than what I can put together." While some of that is, of course, true (my back enjoys the self pat), the reality is this is an inexact science.
The explosion of the internet has left fantasy owners with tons of information. You’ve gone from site to site and downloaded draft lists. But more importantly, you’ve downloaded a spreadsheet full of projected stats. So now what? Do you just stare at it until something makes sense? While many do just that, this article will give you a brief introduction on how to turn those projections into player rankings. I’d be remiss if I didn’t give a quick shout-out to by my boy CA who introduced me to this way of thinking.
First, let us consider the home run. While opportunity, and by that I mean a higher at-bat total, is often a key factor into creating someone’s home run projection, the reality is you don’t care if a player hits 25 homers in 500 at-bats or if he does it in 350 at-bats as part of a platoon. A homer is a homer. So for valuation purposes, let’s just assume each home run is worth one point.
Second, what about runs and RBIs? These categories are a bit trickier. While it’s true that you don’t care about at-bats for these counting statistics. The fact is, without enough plate appearances, you’re just not going to get enough chances to knock in or score runs. So, while some will reduce the importance of these categories in their projections and in their valuations, I take a slightly different approach.
I like to assume that a run and an RBI are similar in value to the home run. In fact, a home run will also result in a run and an RBI so they are somewhat connected. The difference is, while a home run is purely the byproduct of the player, runs and RBIs have a dependency factor. Outside of the home run, you need help from your teammates in order to generate results. So, how do we square them up closely? First, based on historical data (and you can check your leagues historical standings if you don’t believe me) runs and RBIs occur at very similar paces
SMALL SAMPLE SIZE ALERT: In looking at a 20-team league I run; In last year’s standings there were 17,599 runs scored and 16,814 RBIs. That’s a difference of 785. Since the league is 20-teams, that’s 39.25 runs per team. Consider 14 starting offensive spots and that’s 2.8 runs per person more than RBIs. Convinced they are somewhat equal? What I then do is add runs and RBI together. In order to convert it back to something that makes it on par with homers, I choose to divide that number by some factor, say 3.8. So, a player projected to score 100 runs and drive in 100 gets a raw score of 52.63 (200 divided by 3.8). That’s roughly 26.31 points per category. So 100 runs and 100 RBIs are the equivalent of hitting 26.31 homers. Therefore, a player with a projection of 26-100-100 will now have a raw score of 78.63. We’re on our way.
In the next installment I will discuss how to factor stolen bases and batting average into the mix to complete your raw scoring.
