In part I of my n-part series on the Quality Start, I outlined why this stat should A) be understood to have no real baseball value and b) be understood as a fairly ideal fantasy stat. To sum, the QS is an ideal replacement for ‘wins’ in assessing fantasy pitcher contribution in any format, because it relies more on the skill of the pitcher than on the circumstances beyond his control, because it is easy to understand, and because it is projectable.

As a minority fantasy stat, the QS still does not appear in most easily attainable projection systems when you are doing your own player evaluation. But given a few bits of easily attainable information, it is much easier to predict with some accuracy how many quality starts a pitcher can be expected to have.

A simple cursory web search revealed a few different equations for predicting QS, and I tested two of these against 2012 data. Mr. Cheat Sheet and Cup of Fantasy Joe both outline pretty good forumlas, and you should read those links for insight into how the formulas work and what they suggest you learn from them. Comparing the formulas from each site against all SPs who had 10+ QS, I found the following:

Cup of Fantasy Joe and Mr. Cheat Sheet Quality Start formulas compared against actual 2012 data for pitchers with 10+ QS

Cup of Fantasy Joe and Mr. Cheat Sheet Quality Start formulas compared against actual 2012 data for pitchers with 10+ QS

From this data it’s fairly clear both CoFJ and Mr Cheat Sheet are close enough in projecting QS numbers against actual data that I would leave it to preference in choosing which formula to work with. I found Mr Cheat Sheet’s formula a little easier to wrap my math-inhibited mind around. It could be that against a larger pool of data, the discrepancies become clearer.

 

If you really like tables, here is a list of a few top, middle, and bottom pitchers with their 2012 actual QS, compared against what COFJ and MCS’s forumulas project using the same 2012 data:

A sample of top, middle, and bottom-tier pitcher Quality Starts compared with various formulas to project the same

A sample of top, middle, and bottom-tier pitcher Quality Starts compared with various formulas to project the same

 

Looking at this chart the discrepancies between the projection formulas appear a bit more extreme, and it becomes clear that in reality a pitcher will over- or under-perform his projection based on a variety of factors. Both COFJ and MCS weigh games started, total innings pitched, and ERA in determining QS, and while it is clear these numbers can get very close to accurate results, it is also clear that the margin of error is probably about +/- 3.5 QS or so. Again, I’m math inhibited so this is an eyeballed guess.

One thing that I feel this table DOES reveal is the degree to which a Win is less representative of a pitcher’s true talent than the QS. Again, fantasy stats are much poorer at evaluating true talent than advanced stats, but if we all agree that Ross Detwiler is worth a bit more than a 2012 Tommy Hanson or Ivan Nova, QS better reflects that.

 

You can view the full spreadsheet of 2012 quality start comparisons here.

Some speculative conclusions

A few quick, dirty conclusions based on this info:

  1. Even if you do uses Wins, the QS formula can give you a measure of talent for a pitcher to help ground a Wins projection more into reality than a simple guess.
  2. You could avoid projecting QS or any game-performance projection by focusing instead on IP and ERA. A 1, 2, or 3 starter who avoids injury and gets deep into games is a good bet to put up strong QS numbers.
  3. As with any ranking, the results of the formula you use can only be as good as the projection system you rely on. Projection systems are generally more reliable than individual gut-feel, but the general rule of thumb is that more meaningful data leads to better projections. Trust the numbers you get for an established pitcher with several years of service time more than the numbers for young guys.
  4. Especially in head-to-head leagues, QS is a useful SP evaluating stat. In roto leagues, a more ideal stat may be some WAR-based evaluation that is more context neutral. But in leagues where you have to win week to week, QS is less likely than Wins to punish good starters who pitch for crappy teams or reward mediocre starters on offensive powerhouse teams.
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