Clustering Your Way To Line Betting Success : Building a Predictive Model

In the previous blog I used a clustering algorithm - Partitioning Around Medoids (PAM) as it happens - to group games that were similar in terms of pre-game TAB Bookmaker odds, the teams' MARS Ratings, and whether or not the game was an Interstate clash. There it turned out that, even though I'd clustered using only pre-game data, the resulting clusters were highly differentiated with respect to the line betting success rates of the Home teams in each cluster.
Read More

Clustering Your Way To Line Betting Success

For today's blog I'll be creating a game clustering that uses as input only the information that we might reasonably know pre-game - for example, the pre-game team MARS Ratings, Bookmaker prices (or some metric derived from them), and information about the game venue.
Read More