Meta
-
Recent Posts
- Steven Krivit continues to trash Andrea Rossi and his LENR technology. — [LINK]
- Interview with Adam Lashinsky — [VIDEO]
- Why some people are more innovative — [VIDEO]
- Forbes editor deciphers Steve Jobs’s Apple. — [VIDEO]
- Jason Ruspini rebuts Eric Zitzewitz on the regulation of political prediction markets. — [COMMENT]
- Eric Zitzewitz petitions the CFTC in favor of real-money prediction markets about politics. — [TEXT]
- Global warming is a big scam. — [LINK]
- A Swarm of Nano Quadrotors — [VIDEO]
- The Tragedy of the Commons — [VIDEO]
- Guy Kawasaki on Steve Jobs — [VIDEO]
- Inside Apple — [VIDEO]
- Mitt Romney’s taxes — [LINKS]
- A critique of Apple’s multimedia iBooks. — [LINK]
- Does Apple lack “generosity”? — [LINKS]
- Apple Education Push — [LINKS]
- Water Crystals — [DOCUMENT]
- Apple’s e-book software will allow publishers to make textbooks more interactive. — [LINKS + VIDEO]
- Alain Soral is France’s most dangerous intellectual… (dangerous for the French plutocrats, that is). — [VIDEO]
- Computers thru time — [CHART]
- NASA has finally understood the theorical basis of LENR (low-energy nuclear reactions). — [VIDEO]
Super Bowl XLIII – 2009
This entry was posted in Analysis (Accuracy & Precision), Exchanges & Markets, Market Expiry, Market Prices & Probabilities and tagged American football, BetFair, prediction markets, Super Bowl, Super Bowl 2009, Super Bowl XLIII. Bookmark the permalink.
4 Responses to Super Bowl XLIII – 2009
Leave a Reply
You must be logged in to post a comment.
Is this a knockout comp? The graph looks too mathematical to be anything else.
Barry, explain more your question.
I took that chart from BetFairPredicts.com, because BetFair.com don’t allow us to take expired charts.
If the teams are knocked out of the competition (or mathematically have no chance) then thats going to improve the probability of the other remaining teams. I.e. 8 equal teams would have a 12.5%, 4 get knocked out and the remaining 4 would jump to 25%, 2 more and its 50/50%.
The probability of the Steelers in the latter part of the graph jump from 20% to 40% to 70%(80%) nearly doubling. Important information in the graph, the ranges of 19-21% and 39-41% etc, is smoothed out and would be where “the masses” affect the price.
The final 2 teams jump up in the last week, but if the graph was somewhat normalised to take out the knockout effect, it might be easier to see if the Cardinals improved their % (24 to 30) while Steelers (80 to 70) went down.
Thanks for the elaboration, Barry. Let’s see whether someone comments on that.