Applications of Win Probabilities (June 13, 2003)
Phil Birnbaum checks in with some excellent work based on empirical data. Jump to page 7 to read his study. (PDF file is 240 Kb)
(I say it much, but I still don't say it enough, but thank you Retrosheet!)
--posted by TangoTiger at 01:35 PM EDT
Posted 10:57 p.m.,
June 14, 2003
(#1) -
Michael
So to calculate general leverage this may work, but studying IBB situations or telling if the closer should be used I think one needs to look at the team makeup more closely. One needs to consider both what the quality of your non-closer good bullen arms are and the quality of the team hitting. If you are facing some of the worst of a bad lineup, say Detroit, of hitters than a 1 run lead may be safer than facing the 2-4 hitters of a powerful lineup, say Toronto, with a 2 run lead.
Posted 9:51 a.m.,
June 15, 2003
(#2) -
tangotiger
It's always important to use the right tools for the right job. Phil's data is completely empirical, and therefore, the situation you face yourself in should be similar to what the empirical shows.
If you have additional variables like "pitcher is 20% abve average", the hitter at bat is 30% above average, but the batter on deck is 10% below average, and the hitter after him is 5% above average, you have to create your model to reflect what it is you want. Empirically, you won't find the sample size to match that. Which is why you need a Markov chain that handles all this (or you run a sim).
The empirical data or a basic Markov may help you and guide you to an answer, but if the variables not being considered are very relevant, your conclusion will be suspect.