;)
Friday, June 3, 2011 at 12:42PM What features of a contest, I wondered this week, led to it having a larger or smaller overround than an average game? In which games might the bookie be able to grab another quarter or half a percent, and in which might he be forced to round down the overround?
Saturday, May 28, 2011 at 5:30PM In recent blogs where I've been posting about a win production function the goal has been to fit a team's season-long winning percentage as a function of its scoring statistics for that same season. What if, instead, our goal was to predict a team's winning percentage at the start of a season, using only scoring statistics from previous seasons?
Friday, May 27, 2011 at 2:38PM A couple of blogs back I described some win production functions, which relate a team's winning percentage in the home-and-away season to characteristics of its scoring during that season, in particular to its rate of scoring shot production and its conversion of those scoring shots relative to its opponents'.
Wednesday, May 25, 2011 at 9:35PM Over on the Simulations blog I've been investigating how the returns to Kelly-staking and Level-staking respond to different levels of variability and bias in the bookmaker's team probability assessments, and to different levels of overround in that bookmaker's market prices. In this blog I'll investigate, using a purely mathematical approach, how a punter's expected return varies as the overround varies, depending on the size of the bias in the bookmaker's probability assessment and in the true probability of the team being wagered on.
Tuesday, May 24, 2011 at 9:33PM In the previous blog I came up with win production functions for the AFL - ways of estimating a team's winning percentage on the basis of the difference between the scoring shots it produces and those it allows its opponents to create, and the difference between the rate at which it converts those scoring shots and the rate at which its opponents convert them.
