Some Words Regarding Baseball Projections

In yesterday’s Corey Kluber article, a commenter pointed out a Steamer quirk – only three starting pitchers are projected for a sub-3.00 ERA. Last season, 22 qualified pitchers finished the year under the 3.00 benchmark. If you set the threshold at 50 innings pitched, 39 starters were below a 3.00 ERA. Clearly Steamer is crazy. Right? I mean, we have to expect a lot more than three pitchers to demonstrate excellence.

Or maybe it’s not so crazy. Steamer provides a single projection based on a range of possible outcomes. Is it hard to believe that most pitchers aren’t likely to post a sub-3.00 ERA?

Let’s get this out of the way. I’m not a Steamer expert, I don’t know the inner workings of this particular system. My goal today isn’t to specifically address Steamer’s quirks, but to speak at a high level about all projections. Remember, you should trust the projections. But it’s useful to understand how they work in general.

You can think of a projection as a representative outcome for a player. There is some distribution of possible outcomes ranging from nothing to perfection. Perfect never happens, while nothing(or worse) happens all too frequently. Below is a hastily constructed illustration. Think of the X-Axis as WAR and the Y-Axis as frequency. Let’s say the graph is titled – 10,000 simulations of Player N for 2015.

Chart

This isn’t a perfect graph by any means, but it captures some of the basics. Who remembers the lesson on right-skewed distributions? The mode is the peak, the mean is somewhere to the right of that, and the median is even further right. Which is most useful to us: the most likely single outcome (mode), the average of all outcomes (mean), or the middle-most outcome (median)? You probably want some combination of the mean and mode. I assume each projection system tackles this question in a slightly different way.

So now we have a rough image of possible outcomes, and we know Steamer projects only three pitchers to beat a 3.00 ERA. Let’s turn to a simplistic example. Let’s say we have 30 pitchers who have an equal chance to finish anywhere between a 2.90 ERA and a 3.20 ERA. With that flat distribution of outcomes, we will project all of them to pitch to a 3.05 ERA. We still expect 10 of them to finish below the 3.00 threshold, but we have no means of projecting which ones. Reality is much more complicated.

Steamer probably expects more than three pitchers to finish with a sub-3.00 ERA. It just doesn’t know which ones. If you think about the risk factors involved with pitchers, it’s not surprising that few are projected to be excellent. They all have about a 30 percent chance to land on the disabled list. If they happen to play through injury, their performance can be a lot worse (see A.J. Burnett). They can find ill-luck, bad defense, or ballpark effects working against them. In many cases, one bad day can all but ensure an ERA north of 3.00.

Remember, the projections work. You should trust them. But it’s useful to understand how they work. Every year, some players will be better than expected and vice versa. The job of the projection system is to set an expectation, not to bet which players will be better or worse than that expectation. Actually, that’s your job as the fantasy owner. It’s up to you to decide which pitchers will outperform expectations. As we discussed yesterday, I think Kluber will be one of them.





You can follow me on twitter @BaseballATeam

42 Comments
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Matthew Tobin
9 years ago

You should use your knowledge to supplement projections. Start with the projections, if you think they are off, look for tangible changes. If you find something, you can adjust. But if you don’t, stick with the projections.

Ryan Brockmember
9 years ago
Reply to  Matthew Tobin

But, if you start doing that, you need to adjust ALL players. They all exist within a steamer universe where only a few pitchers have below a 3 ERA, so if you alter one of them to be better it is more valuable than in the real world where lots of pitchers have ERAs below 3. It gets complicated quickly.

Blue
9 years ago
Reply to  Ryan Brock

I don’t interpret the post as suggesting modifying the projection per se.

Blue
9 years ago
Reply to  Matthew Tobin

Exactly. The projections are fine as a baseline, but if your intention is target specific players blithely trusting them is foolish.