To review what we have so far regarding Phillies projections for 2013:
- Here we worked out that the projections in the Bill James model would mean ~89 wins, based on certain assumptions about playing time
- Here we said that the ZiPS model projections would translate to ~81 wins
- Here we saw why the ZiPS projections indicate that the 95-win pace in the second half of 2012 is unlikely to be sustained in 2013 (partly because the 95 pace included about 6 wins attributable to luck, but mostly because the pitching will regress)
So given all of that, what would it take for the Phillies, as currently constructed, to have a strong year of, say, 95 wins, which would probably put them in contention for a division crown? In other words, what kind of performances would the current roster have to deliver in 2013 in order to generate a run differential large enough that it would translate to 95 wins with the pythagorean formula?
Let's work through one scenario where that would happen, and we can see how realistic that might be.
The traditional stats used for 2013 are shown in a table below, but here is how the 2013 wOBA compares for each player:
Rollins: .324 wOBA - similar to 2011 (.325) and 2012 (.322).
Young: .330 - midway between 2011 (.369) and 2012 (.297); close to 2010 (.336), but at three years older, and without the benefit of a good hitter's park.
Utley: .360 - not quite as good as 2010 (.370), but better than 2011 (.338) or 2012 (.342).
Howard: .350 - almost as good as 2011 (.355), even though he's two years older, and coming off an injury.
Ruiz: .350 - midway between 2010 (.368) and 2011 (.333), but far below 2012 (.398), so it assumes regression, but also that amphetamines did not help him significantly in 2010-11.
Mayberry: .340 - assumes his numbers improve as his exposure to RHPs is limited, and he mostly faces LHPs (.405 vs. lefties in 2011, .345 in 2012).
Finally, Brown, Revere, and Galvis all show significant improvement:
Brown: .337, or .266/.332/.460 (best so far was 2011, at .245/.333/.391, and .322 wOBA)
Revere: .315, or .295/.348/.363 (best so far was 2012, at .294/.333/.342, and .300 wOBA)
Galvis: .310, or .263/.300/.424 (2012 at .226/.254/.363, and .267 wOBA)
Playing time assumptions:
As in the previous reviews of projections, these are the assumptions for playing time:
Stats by player:
wRC by position:
In total, this would translate to 723 runs scored, or 39 more than last year.
- Cole Hamels and Cliff Lee both improve their ERA, from 3.05 and 3.16, respectively, to 2.90.
- Roy Halladay improves from 4.49 to 3.20, essentially showing that 2012 was just a blip.
- Kyle Kendrick continues improving to 3.80, halfway between his 1st half ERA (4.87) and 2nd half ERA (2.87) of 2012.
- Tyler Cloyd and John Lannan both at 4.30.
- Jonathan Papelbon and Jeremy Horst both regress somewhat, while Antonio Bastardo improves:
Looking further back, we could compare these ERA assumptions to recent years' ERA, but we wouldn't know how much luck/defense was involved in those past years. So instead, these graphs show FIP for 2010-2012, and ERA assumed for 2013:
With 723 runs scored and 600 runs allowed, the pythagorean expectation would be 95 wins. For comparison, I've also included the 2011 totals below. This scenario would allow the 2013 pitchers to give up 71 more runs than the historic staff of 2011, but also requires the offense to score 10 more runs than that team:
In short, very little can go wrong, and a heck of a lot of things would have to go right.
Finally, a word about luck. There are several types of luck or random variation. This scenario includes quite a bit of two types: 1) avoiding injuries, and 2) playing (or at least getting results) at relatively high levels compared to recent years.
There is another type of luck that is assumed to be neutral in this scenario, and that is the sequence or timing of events, also known as "clutch". In other words, taking all the same individual stats, but sequencing the hits, home runs, walks, etc. (or hits/HRs/walks allowed, etc.) to occur in more favorable situations, and therefore result in more wins.
For example, the above stats could be ratcheted back so that they translate to only, say, 89 wins, but with some timing luck/timely hitting, they could very well end up resulting in 95 wins (or 80 wins, if it's "bad" luck).