If you are going for the emotional hedge, Sparty on the money line is the only way to go. Why take the points? Michigan wins by 7 and you are happy, but still lost your bet. The only true hedge is getting odds on your money if Sparty wins outright.
Mathlete - Just wondered why your Game Chart shows Michigan's initial win percentage at just uner 50%, when most trustworthy agents (i.e. the betting markets and your game prediction to name a couple) had Michigan as a small to medium favorite. I know Corso donned the leprechaun hat on GameDay, but I'm assuming that's not feeding into your metrics at all.
Your game prediction did mention that your metrics had Notre Dame ranked at 15 and Michigan at 17, so I'm assuming that's the reason, but does your game chart not factor in home-field advantage in it's initial win percentage estimate?
I use the RSS Radio app (free) and the podcast works fine on an iPhone 4S. No problems with any Mgopodcasts or WTKA.
OT comment on the podcast itself: Brian is amazingly calm and un-emo despite the insanely frustrating performance last Saturday. Maniacal laughing and exclaims of "AAARGH BIG TEEEEEEEEEN" are notably absent.
Just wondering: Have you ever looked to see if your Talent Rank metric has any predictive power as far as wins and losses? For example, can I take two teams, pull their respecitve Talent Rank values, and compute an expected point differential between the two on a neutral field, or better yet, an expected win probability based on talent difference?
It would be interesting to see if Talent Rank predicts wins and losses, and if so, whether Talent Rank has a linear relationship with win probability or not. Without knowing this, it is hard to get a sense for whether Alabama has an equal chance of beating Michigan as Michigan has of beating Minnesota. You make this comparison in your diary, but unless I assume a linear relationship between Talent Rank and win probability, I can't say how Michigan's chances of beating Minnesota compare to Alabama's chances of beating Michigan.
Either way, I think I speak for nerds everywhere when I say this is very interesting stuff.
Recent Comments
Seth - Loving the special teams UFRs! Hoping this will be a regular feature (among the MANY other regular features).
One minor quibble: Although they look identical on tape, I believe the #4 on kick return is actually Deveon Smith, not Cam Gordon.
Mathlete - Just wondered why your Game Chart shows Michigan's initial win percentage at just uner 50%, when most trustworthy agents (i.e. the betting markets and your game prediction to name a couple) had Michigan as a small to medium favorite. I know Corso donned the leprechaun hat on GameDay, but I'm assuming that's not feeding into your metrics at all.
Your game prediction did mention that your metrics had Notre Dame ranked at 15 and Michigan at 17, so I'm assuming that's the reason, but does your game chart not factor in home-field advantage in it's initial win percentage estimate?
Inquiring (nerdy) minds want to know.
I use the RSS Radio app (free) and the podcast works fine on an iPhone 4S. No problems with any Mgopodcasts or WTKA.
OT comment on the podcast itself: Brian is amazingly calm and un-emo despite the insanely frustrating performance last Saturday. Maniacal laughing and exclaims of "AAARGH BIG TEEEEEEEEEN" are notably absent.
Excellent work, as always, Mathlete.
Just wondering: Have you ever looked to see if your Talent Rank metric has any predictive power as far as wins and losses? For example, can I take two teams, pull their respecitve Talent Rank values, and compute an expected point differential between the two on a neutral field, or better yet, an expected win probability based on talent difference?
It would be interesting to see if Talent Rank predicts wins and losses, and if so, whether Talent Rank has a linear relationship with win probability or not. Without knowing this, it is hard to get a sense for whether Alabama has an equal chance of beating Michigan as Michigan has of beating Minnesota. You make this comparison in your diary, but unless I assume a linear relationship between Talent Rank and win probability, I can't say how Michigan's chances of beating Minnesota compare to Alabama's chances of beating Michigan.
Either way, I think I speak for nerds everywhere when I say this is very interesting stuff.
I have a UFR-type substance for the 2010 UConn game that charts rushers for every play. If you want it, let me know how I can get it to you.