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Equivalent Fantasy Average: Looking for a stat corollary

How do some of the other stats correlate with fantasy production? I check.

Joe Camporeale-USA TODAY Sports

I know just enough math to get myself into trouble. Excelled all the way through high school, struggled a bit more in college, quit around the time things went from "find the right answer" to "prove the right answer."

That means that I can fathom up some interesting mathematical hypotheses, develop them to an extent, and eventually reach a point where I just throw my hands up and say "hope that's good enough." For those who have floated around these here parts the last couple years, that ties back to my Equivalent Fantasy Average, a fantasy sorting metric I came up with.

In short, EFA scales every fantasy contribution (home runs, RBI, runs stolen bases, batting average) to a number that looks like a batting average, based on the number of standard deviations away from the mean a player's stat was. A guy with 50 home runs will have a crazy high homer EFA, but if he's pulled down by a lack of steals, it balances out. At the end, averaging all five numbers yields a batting average-reminiscent number that encapsulates his total fantasy contribution. (For more on the hows and all, check ... well, any of the billionty-seven EFA pieces from the past, but how about this one.)

Thanks to Excel, it's pretty easy to calculate, and works out (to me) like a fantasy player rater that pares off any extraneous details that don't help directly in fantasy. I tweaked the method a few times over the last couple years and provided a handful of in-season updates, and that was that.

"Yes," I always thought, "but what of it?" See, the thing is that, unless you hired me to provide you with real-time EFA updates on a daily basis (if you want to do that, let's talk!), it's just a set of numbers that only look back that I toss out there at my leisure.

EFA was neat. I liked it. But I didn't know what to do with it. Short of getting an EFA column on FanGraphs, though, I wasn't sure what to do with it.

And then it occurred to me that FanGraphs does already have a whole host of columns. Maybe one of them aligned with my interests?

I built a table ranking every player with at least 300 plate appearances 1-268 by 15 different statistics:

  • EFA
  • Hits
  • Home runs
  • Runs
  • RBI
  • Batting average
  • On-base percentage
  • Slugging percentage
  • OPS
  • wOBA
  • wRAA
  • wRC
  • Batting Runs Above Average
  • RAR
  • wRC+

The idea was to plot each statistic against EFA and see what stat that we can monitor daily correlates best to EFA. Below, you'll see all 14 charts. They're unlabeled, because that doesn't really matter, but a couple should jump out at you:

All the Charts

Most of those charts look random, or at least close enough to random as makes no difference. Two of them, though, stand out with a high correlation. Put another way, the following chart lists the R-squared values for each stat when plotted against EFA, best to worst:

Stat R-Squared
Weighted Runs Created .868
Runs .840
Hits .731
Runs Batted In .653
Weighted Runs Above Average .555
Runs Above Replacement .547
On-Base Plus Slugging .531
Weight On-Base Average .517
Batting Runs Above Average .503
wRC+ .493
Slugging Percentage .477
Home Runs .432
On-Base Percentage .376
Batting Average .361

I'm going to start at the bottom. I'm not super surprised home runs don't really correlate with fantasy production, as it's such a specialized skill. But average, on-base, slugging? I really thought I'd see a positive trend with those, and instead there's not much of a connection at all.

Now, the top. That wRC is strongly correlated to fantasy success isn't much of a shock; it's an attempt at a catch-all offensive statistic, and good offensive players are going to be good fantasy players. The close second-place finisher, though, in runs scored, is really where the surprise comes in for me.

There's a certain logic to it. To score a lot of runs, a player has to be on base a lot, which likely means a high average. He probably has to be in a good offense, which means RBI opportunities often accompany run opportunities. He has to be in position to score runs, which likely means speed, which can mean steals. And, you know, every home run is a run. All in all, I get why runs scored and EFA correlate, sort of, but it still comes as a surprise to me.

There is a conversation to be had about correlation and causation here, of course. Just because runs and EFA line up pretty well doesn't mean one leads to the other. But I have been working on my preseason position rankings since I worked these numbers up, and I have sorted some of the positions by runs scored, and you know what? It looks good.

I'm not saying you sort all players by runs scored and be done with it. I'm not even saying you do that with wRC (though you could do a lot worse, honestly). I'm just saying ... I ain't updating EFA every day. Considering the work involved, I'm not sure I'll be working with it much at all this season. So if you want an approximation that seems to line up with the metric fairly well, runs scored seems to do it. Surprisingly so.