Statman Reborn – Episode Four
Chatting to some fellow “anoraks” and racing statistics fans down the pub the other day (yes, they do exist even if we are a rare species), and we got on to the subject of beaten favourites.
A popular winner finding method employed by plenty of people I know, to the extent that the letters BF appear beside the name of any horse who topped the market on their last start and failed to win, and it got me thinking – are they a source of sure fire winners – or is it all an urban myth hyped up by the dreaded bookmakers to part us from our money?
Concept: It won’t take too long to see how punters would get on historically backing beaten favourites on their next outing but where is the fun in that?
We need to see if certain trainers are better at placing their horses to win next time after the money is down and has gone into the bookmaker’s satchels, whether certain tracks provide more (or less) profit, whether certain jockeys are the “go to” for beaten favourites looking to recoup losses and so on – the list of options is endless so I had better start making some decisions!
The Data: Data is recorded from 1st January 2004 to 19th October 2024 (when I stopped the Wi-Fi to start on this idea) – we could have used more data but if we want to look at current trainers and/or jockeys then there is no point.
I could (and thought about) remove the summer months so it was more applicable to “now”, but decided on a longer-term option so we will divide into three “sets” – Flat Turf, Flat All-Weather and National Hunt (all) – or we will be here forever and a day.
All races are included unless annotated differently, for both the United Kingdom and Ireland for clarification.
The Presentation: Have I mentioned that I like using tables - I think I have?
The truth is they work, they simplify things for all of us – and if I keep using similar tables with the odd amendment, you can get used to looking through them to pick out the information you need the most with ease.
Each section will remain clearly labelled, with an overview before breakdowns and a summary below each table giving my own views on how I would use the numbers, though after that it is all up to you.
Summary:
Nothing particularly unexpected with blindly backing beaten favourites a good way to start a new career selling The Big Issue.
If one thing surprised me, it was the poor strike rate of one in six or so– I would have guessed (wrongly) at a lot better than that. For any laying addicts out there, a profit of 1170.02 points was made but that’s from an awful lot of bets!
Now we need to dig deeper…so we will start by code and list any profitable trainers, but we will stick to the top 5 for ease of use with a minimum of 50 qualifiers to be included.
Summary:
Evidence if it was ever needed that there is gold if you start to dig for it. I accept the figures aren’t life-changing at first glance but hang on a minute – a return on investment of 43.00% to Betfair SP is not one to be sniffed at, and any idea that shows a profit to Industry Starting Price has a lot going for it.
Summary:
I struggle to remember finding a system of any kind that still made a profit to industry SP, but this bucks the trend. A Return On Investment of 42.49% to Betfair SP is impressive from minimal bets (averaging just over one a week), and worth making note of for future reference.
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