I recently heard someone mention SIERA baseball stat and how that was his favorite.  When asked why he liked that stat he responded. “Google it,”  It did sound familiar so today I googled it.  After reading some of these articles I’m left speechless.  This is complete and utter nonsense.

I have already disproved FIP as a predictor but haven’t posted that disproof here yet.  FIP and SIERA stats are predictive, or so they claim.  Because we know the past, and we know the past’s future because that’s also in the past, we have all the information needed to assess any of these predictive stats quantitatively.  Do they actually predict anything?

I showed that FIP does not predict anything.  It’s just some made up number purported to mean something.  This isn’t my opinion, it is fact.  I wrote code to run numbers using the past 50 seasons as a dataset.  But this post is about SIERA, not FIP.  I will not bother disproving SIERA because it does take work.  SIERA is even dumber than FIP so I already know with very good certainty that it doesn’t predict anything.

Anyhow, I don’t want to get into the nitty gritty other than a couple tidbits that can be put to test by this data model using current data.  The Yahoo article that came up using google was this:

Everything you always wanted to know about: SIERA

For example, last year, Zack Greinke led the major leagues with a 2.66 SIERA, because he struck out a ton of guys and didn’t walk many people, even though he had a 3.83 ERA. In my opinion, the discrepancy was a product of bad luck. Though luck may not explain why he got lit up in the playoffs.

This article was written December 2011 and talks about the 2011 season.  Here’s Greinke’s 2011 according to this data model:

2011 0.6 Zack_Greinke_MIL PITCH XXXXX

At WAA=0.6 he’s barely above average and way out of the top 200.  He ended 2011 in purgatory with a rank of XXXXX which means just OK.  Note the use of “In my opinion” in his explanation.  There is no room for opinion in math.  It is either true of false.  Any statement you make must have proof.  You must show your data which SIERA clearly does not in any articles explaining it.

Edit: Greinke got lit up in the playoffs that year because he was an average pitcher going up against the very best hitters in baseball.  This model shows that.  SIERA does not.

SIERA ranked Greinke best pitcher of 2011, ahead of this guy.

2011 9.3 Clayton_Kershaw_LAN PITCH +002+

According to this model Kershaw finished 2011 with a WAA=9.3 ranked #2 MLB player both batters and pitchers.  Granderson was #1 that year so Kershaw was the best pitcher of 2011.  Let’s hear what SIERA thinks of that:

The major-league ERA leader was Clayton Kershaw at 2.28. However, his SIERA was 2.81. That’s still terrific, good for fourth in the majors, but it may be a sign that he won’t have a 2.28 ERA again next year.

The problem with making predictions is that those of us who inhabit the future here in 2016 know what happened in 2012.  Let’s look 4 years into the future at Kershaw’s ERA.

2012 2.53 Clayton_Kershaw_LAN
2013 1.83 Clayton_Kershaw_LAN
2014 1.77 Clayton_Kershaw_LAN
2015 2.13 Clayton_Kershaw_LAN
2016 1.56 Clayton_Kershaw_LAN

Technically they were right about 2012.  His ERA did go up a little and then he’s been on fire for the next 4 years thereafter.  What did SIERA tell us?  Nothing.  Like FIP, SIERA is a made up number with Oracles like the author of this article explaining to us, the unwashed, what the future will bear.

No one can predict the future and if they can they’ll make some nice money in Vegas where gambling on this is completely legal.  Here’s a line from the beginning of the article:

How to calculate SIERA: You’re going to need a lot more than a calculator for this one, so it’s better to explain it conceptually.

This is why the guy I overheard couldn’t explain SIERA when asked because even this article can’t.