Cricket and FRAN

With the opening stage of the Cricket World Cup now complete, thanks to Odds Portal I have now have the approximate prices for 167 such matches since 2011 which show that backing the Favourite in these games is a profitable strategy with an overall ROI of around 2.7%.

With the number of sportsbooks offering prices somewhat limited in earlier years, though up from five to eleven these days, the data isn't perfect but the trend is apparent and while the number of knockout games is small, just 17 so far, if we include these games, the trend becomes even stronger.

Hopefully the screenshot above is self-explanatory. It shows the outcome of backing the Favourite for both the opening group and latter elimination stages and the ROIs, so for example, Favourites in the knockout stages have an ROI of almost 21%, and in all matches of 4.3%.

All Favourites are not equal however, and the next image shows the results by band:

Backing at very short odds isn't usually the best idea, and if the shortest priced 46 favourites are excluded, the ROI climbs to 6.2%.

India are about 1.37 to beat New Zealand in the first semi-final, which is very close to the price they were to win the same match up four years ago, and lost.

Not relevant for betting purposes, but it's a curiosity that New Zealand are the only country to win a knockout game as the underdog, having done this in 2011, 2015 (both v South Africa) and in 2019 versus India and they have good pedigree in World Cups reaching the last two finals.  

When New Zealand and India met in the opening stage of this World Cup, India won by 4 wickets, but New Zealand were always in the game and at one stage were 178-2 before ending at just 273. The numbers tell me to back India though, and it's about numbers, not teams.

Another rare comment on the blog, this time from my old friend schnakenpopanz who wrote:

Hi again, As I have often mentioned, I follow your blog with great admiration. What is your opinion on rating systems? On the one hand, ELO is often used to rate teams better. I use Ken Massey's site a lot. https://masseyratings.com/ Especially for college sports, it allows for very good ratings. Thank you very much and good luck.

While I love looking at ratings, the challenge I have is using them to beat the market. A little history, but back in 1987 (36 years ago!) I bought a book called The Punter's Revenge - Computers in the world of gambling - by Tony Drapkin and Richard Forsyth (I still have it in fact) and one chapter which had a big influence on me was 8.4 "Rating the strength of football teams".  

The method was named FRAN (Football Rating Assessment Number) and was based on Elo (not ELO!) with Home teams "risking" 7% of their rating and Away teams 5%. I was quite fascinated by the idea, and spent many hours in the late 1980s / early 1990s maintaining ratings, looking for value, and with some success. 

I remember one midweek round of matches when I had a number of multiple bets on Away wins in Divisions Three and Four, (in those days you couldn't bet on single matches), and all five landed for what, at the time, was a rather nice payout. I remember it because waiting for the final results to be confirmed made me late to meet a friend at the pub, and she was less than impressed with my excuse. 

I think I've mentioned before that I'd look at the prices in the Racing Post on my commute into London, stop at a phone on my walk to the office and call in my bets which was great until my bookmaker accounts all got closed down in fairly quick succession, which was probably more than a coincidence, and made me realise that my time could probably be spent more profitably elsewhere. Similar to my reaction when told I'd have to pay Premium Charges, part of me was satisfied that the ban meant my success was being confirmed. 

But I never forgot the idea, and many years later I resumed maintaining ratings on teams which is how I stumbled across the typical profile for matches with a higher than expected probability of ending up as a Draw, which became known as the XX Draws system back in 2012 or 2013. 

Like everything else, the betting landscape has evolved a lot since the late 1980s. Betfair made it possible for me to make money consistently again from betting, but other, far more sophisticated organisations, were developing their own models to identify value, and a relatively basic model based on an Excel spreadsheet was never going to find an edge.

I think ratings compiled by others are a good starting point, but because they are widely available, you need to identify a weakness (one example might be the rating for home field advantage) and tweak the overall rating to improve it, but of course everyone else is trying to do the same thing. 

Fortunately the sports markets aren't efficient, and in some cases remain inefficient for much longer than should be expected, and if you identify new trends early, and adapt your model accordingly, there is some hay to be made, at least for a while.

"The trend has vanished, killed by its own discovery." -Benoit B. Mandlebrot