Hidden statistics are the bread-and-butter of any good analysis, but most DIPS models rarely go beyond the obvious to find a player’s true value. FIP can take you most of the way by looking at the three true outcomes (home runs, walks and strikeouts) and xFIP adjusts FIP to what it would be with a league-average HR/FB rate. But neither of those systems considers how well pitchers control more volatile statistics — the ones that take up the other 70% of plate appearances. Now, with the new SIERA here at FanGraphs, we’re finally gathering the kernels that’ll help all of us figure out the small things that make good pitchers, well, so good.

A year after its release, SIERA has undergone some important changes, which we’re highlighting this week. I think you’ll like what you see. FanGraphs’ new-and-improved ERA estimation system now uses different proprietary data, takes more interactions and quadratic terms into account when reaching its conclusions, treats starters and relievers differently and adjusts for run environment. In other words, the new SIERA does an even better job analyzing pitching skills.

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Predicting baseball statistics is a tough job, especially when it comes to pitchers.

For every Roy Halladay pitch machine, there are 10 James Shieldses – guys whose ERAs change a run or two every year. Basically, it’s a crapshoot when it comes to figuring out the next ace – or the former ace-in-waiting who’ll lose his job by the all-star break. Don’t believe me? Consider this: In the past 11 years, four hitters have led the major leagues in WAR; eight pitchers have led the majors in ERA.

So while the league-leading run producers might be predictable, league-leading run preventers change almost every year. But hope isn’t completely lost when it comes to figuring out the next pitching superstar – or dud. Some pitching stats are very predictable, and focusing on those few numbers might lead us to a better system to evaluate talent.

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