A month ago, I used the CAIRO system's individual player projections to come up with a projected team win total of 78.2 wins. Now, thanks to the largesse of Dan Szymborski of Baseball Think Factory, we have the ZiPS projections to use for this purpose. Annual evaluations of various projection systems find ZiPS to be at or very near the top of the heap. So this data should at least give us a reasonable expectation of where the 2012 should be....approximately.

Before I get into the methodology and the numbers, I want to make a quick point about projection systems. They are not magic. They are not divinely revealed truth. They are not intended to be definitive statements on how various players will perform in the coming season. They use sound methodology (involving, in the very least, weighted averages of recent seasons, translations from minor league data, appropriate regression, and the application of aging curves) to project how the available data suggests the player will perform. Every projection is actually the median projection from a range of possibilities. A player projected to hit .300 will probably have a good chance to hit anywhere from .285 to .315. The likely range for a player with a lot of MLB data is considerably smaller than for a rookie whose projection is based largely on a translation of minor league stats. Rookies and sophomores are particularly difficult to project. Johnny Giavotella, for instance, could be quite good, or genuinely bad next year.

Systems like ZiPS attempt to come up with an objective projection, but a wide variety of things could happen. Some Royals will outperform their projections and some will underperform. If more Royals do better than their projections, they'll win more games than is suggested below, and if more perform worse than projected, they'll win fewer games. The following is merely an illustration of how this projection system suggests the Royals will perform next year. Do with that information what you will.

Methodology

The CAIRO projections provided a WAR value for each player, so I totaled team WAR to project the team's win total (in the comments, kcdc1 and I used other methodologies as well to come up with projected win totals ranging from 73 to 78). The ZiPS projections (at least in this rollout) do not include WAR, so I calculated each player's Runs Scored and Runs Allowed. For hitters, I calculated Base Runs. For pitchers, I used two methodologies, Runs Allowed based on ERA and Runs Allowed based on FIP.

To account for defense, I utilized ZiPS defensive projections. As they give no run values, I had to apply an approximate value to correspond to each label. I assigned the following run values per 100 PA's.

Excellent 1.75

Very good 1

Average .25

Fair -.5

Poor -1.25

The above is based on the assumption that a player whose fielding is average for his position is providing a modest positive run saving value. Using the above formula, Salvador Perez, over 560 PA's provides a positive run savings of 5.6 runs.

For playing time estimates, I used the same PA and IP as in the CAIRO exercise with the following changes, due to player acquisitions over the last month. Yuniesky Betancourt was given 175 PA, Chris Getz was pushed down to 50 PA and Joaquin Arias got the boot. For pitchers, Jose Mijares was given 50 ip, Tim Collins, Blake Wood and Kelvin Herrera all were bumped down to 40 ip. For all players, their RS and RA were based on adjusted projections in accordance with my playing time estimates, rather than ZiPS playing time projections.

After I came up with the Runs Scored and Runs Allowed, I used Pythag (with an exponent of 1.884 based on last year's run environment (h/t to kcdc1)) to come up with a team win total.

Results

Runs Scored (plus defensive runs saved) - 750.9

Runs allowed (based on ERA) - 781.3

Runs allowed (based on FIP) - 755.1

Win Total (based on ERA) - 78.0

Win Total (based on FIP) - 80.6

Scott endorses the above numbers. Katie takes no responsibility for them.