There is a large, and ever growing market in the area of on-line gambling, with worldwide revenues of upwards of $50 billion USD. However, the market may be considered new, but it still quite traditional, in the sense there are providers (the online bookmakers, casinos, etc.) and clients who place bets with providers. No more different from walking into a bookies shop, scrawling a horse’s name on a betting slip, and giving the cashier some money. And like traditional betting markets, between 95% and 98% of clients end up making a loss in the long term.
Do you see how ‘traditional’ on-line bookmaking can be… like its old-school cousin maybe only 2% of clients ever seeing a profit? It gets worse, as the vast majority of clients see a very minimal return, with maybe 99% of this 2% of clients barely breaking even. Sure, there’s probably a very, very, teeny-tiny number of punters who make significant gains, but lets face it, that won’t be you. The numbers are just too much against you with the way in which the majority of people gamble. Two principal factors serve to limit the vast majority of punter’s revenue possibilities – a lack of analytic capabilities, and a bias towards short term gain.
Taking the latter factor first, colloquially, the long-term strategy is backed up by a story from a friend working in one of the major on-line bookmakers in the UK. One of their on-line clients was consistently making a large profit every quarter, and my friend was asked to analyze their betting behaviour. It turned out this individual was “merely” placing very large sums on almost sure-fire bets. Although the modest return for the large outlay was risky, this individual turned over sufficient revenue to compete with an executive-level salary. In short, this punter was playing the long-game, and it was paying off.
But back to analytics – how do most people place bets in the first place? Sure, some will study the odds, get the occasional tip and try for various savvy doubling-up or doubling-down strategies. However, the dull mass of betting clients will try to guess a lucky horse, have a bias towards a particular trainer, or refuse to bet against their favourite football team. All these inputs only serve to skew a cold analytical evaluation of the odds. While inside information and expert bias may work for well-informed players in the field, jockeys, reserve team coaches, etc., they are unavailable to the average punter in the street.
There is a niche is seems, to provide some guidance to a large swathe of impulsive, happy-go-lucky gamblers who trust instinct over data. I’m “betting” that at least some of them would take a data-driven approach if is was sufficiently accessible, available and workable. So, with that as a taster for the problem area, I’ll leave you to ponder what form such a client-serving analytics capability may take, and what you could do with a fair data-driven assessment of the odds for a match, horse-race or other sporting event. The betting companies build predictive models, so why shouldn’t you?