tag:blogger.com,1999:blog-38600807.post2314066064649093538..comments2007-09-26T16:05:02.150-04:00Brian Burkenoreply@blogger.comBlogger6125tag:blogger.com,1999:blog-38600807.post-85340039436951748092007-09-26T16:05:00.000-04:002007-09-26T16:05:00.000-04:00

Tarr-I was considering adding an addtional dummy variable for Denver, but there's only been one kicker home-based there during the data period. So it would capture Elam's individual performance within the stadium variable.And it gets even more complicated than just individual stadiums. You'd really have to model the wind, temp, etc. for each kick. Just saying "Giants Stadium" averages out the

Brian Burkehttp://www.blogger.com/profile/12371470711365236987noreply@blogger.comtag:blogger.com,1999:blog-38600807.post-63880548105267906652007-09-26T15:35:00.000-04:002007-09-26T15:35:00.000-04:00

Perhaps the indoor/warm weather factors would be more significant if you considered where each kick took place, as oppose to just applying one factor to a kicker based on his home field. Ideal would be to model every stadium seperately, although that's a ton of work and the data might be too sparse.I believe FO has three kicking locations: Denver, Florida, and everywhere else. Maybe indoor as

Tarrhttp://www.blogger.com/profile/14368810359650066790noreply@blogger.comtag:blogger.com,1999:blog-38600807.post-15571966452486487062007-09-26T09:52:00.000-04:002007-09-26T09:52:00.000-04:00

Jon-The difference between -0.016 and -0.024 is miniscule over the course of one season. It would only be about 0.08 of a field goal (about 0.24 points over 16 games). You could consider them both average. Additionally, they had nearly identical average attempt distances, so it would be easy to compare their accuracy rates directly.

Brian Burkehttp://www.blogger.com/profile/12371470711365236987noreply@blogger.comtag:blogger.com,1999:blog-38600807.post-70842141810004881482007-09-26T09:33:00.000-04:002007-09-26T09:33:00.000-04:00

pf-I've heard that about Heinz Field too. It would be interesting to compare Steelers kickers performance home vs. away using this method.

Brian Burkehttp://www.blogger.com/profile/12371470711365236987noreply@blogger.comtag:blogger.com,1999:blog-38600807.post-64807203813831806392007-09-26T05:59:00.000-04:002007-09-26T05:59:00.000-04:00

So, in the revised numbers, #28 Tynes (-.016) is better than #32 Feely (-.024), even if just marginally. Maybe Jerry Reese does know what he's doing. Maybe.

Jon M.noreply@blogger.comtag:blogger.com,1999:blog-38600807.post-66838164687033341962007-09-24T22:29:00.000-04:002007-09-24T22:29:00.000-04:00

Nice work. One thing I noticed is that the Steeler's Jeff Reed is pretty low. Heinz field is notoriously tough for kickers, and I don't think Reed is any worse than opposing kickers there. I'm not sure if you have the data to account for it.Another thing that might be cool is if an analogous analysis for kickoff ability. The charts could be combined by converting to an estimated point value.

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