Game probabilities for the division round are available at the New York Times. This week I take a look at the role of luck in the composition of the playoff field.
...the luckiest may be the Indianapolis Colts. Not only did they survive a 28-point second-half deficit in the wild-card round, but they were also the team that most overperformed statistical expectations in the regular season.
Based on the core efficiencies of passing, running, turnovers and penalties, plus the Colts’ strength of schedule, my efficiency model expected them to have between seven and eight wins. But they finished with 11, which was 3.2 more than expected.
All but 2 of the 12 playoff teams were above average in terms of beating their statistical expectations, and all but one of the surviving eight beat expectations. Although you may at first think this pattern points to an obvious flaw in the efficiency model, it turns out this is exactly what the field of statistics predicts...
The saints had 11 wins, not 10.
How might Niner odds change if one made adjustments that accounted for Crabtree being out most of the season?
shouldn't the team with the highest efficiency be the toughest opponent, not the one with the most "bad luck"?
Started using a network based baysien analysis. Totally new to this stuff - I know it has some great limitations but I think combined with some of the work most analysts (using frequinists bassed measures) are already using it could be great addition. Novel way to look at it (if people already havent) So utilizing a network based simulation I think the Denver/San Diego game may actually be closer (direct versus indirect comparisons). My results are here
http://springsandsprockets.blogspot.ca/2014/01/from-data-to-super-bowl-playoff-chances.html .
Would love some feedback.