[au_gambler]

A couple of suggestions to improve on this method.

The authors' regression left an intercept or 'adjustment term' of 3.4% - 5.7%. For a perfect bookmaker, this intercept term would be equal to the overround. The number calculated unfortunately averages that overround between different bookmakers and at different times (overrounds often decrease over time). It might be more effective to adjust for the actual overround of each market sampled, i.e. divide each price by the sum of the inverse of the prospects.

They appear to use a flat betting strategy, and the threshold to bet or not was selected based on profitibility. I was simplifying in another comment when I said profitibility should be the goal. In reality it's utility you should be optimizing for. Nobody wants a ultimately profitable system that reads like an EKG, they want a high sharpe ratio. The paper's results are actually very good here, but the trend could be lifted and stabilized further by betting proportionally to expectation, or by explicitly optimizing for such.

[brucen]

Raises an interesting point regarding a staking strategy. Given the bookmakers are going to cut you off, it potentially could be better to just go as hard as you can & live with the risk.

Alternatively, an interesting tweak would be to see what the best historical edge has been, and wait for the best opportunities to surface & only bet on those. Effectively you limit yourself by saying "I can only place N bets per bookmaker, what should my strategy be?"

[flashman]

This comment is an example of the adage that successful sports betters could probably be making money in lots of other ways :)

[shakedown1]

Interesting. Are you refering to kelly criterion?

[au_gambler]

There needs to be some degree of risk aversion given the uncertainties in estimating your edge. I am thinking more along the lines of a CRRA utility function - something a little less aggressive than kelly.

[qwtel]

in your opinion, is there any practical benefit over just using half kelly?