I love betting, its one of the very few guilty pleasures I allow myself. Of course, it doesn’t help that I have lost hundreds of dollars doing it but what the heck, no risk without reward right? And hey, it hasn’t always been losing, I have won quite a few times also.
Recently, however, I have been a little down on my luck. In fact, a ‘little down’ is buttressing it. This year I have never won a single bet. Out of the more than 30 bets I have put on football matches this year, not one has gone my way. This has put a stain on my otherwise pretty decent win rate, not mentioning up to a hundred bucks down the drain.
Like any self-respecting gambler, I decided to continue trying my luck. This time, however, I would try a different strategy. This is what sent me down a rabbit hole. One that has prickled my interest not just as a gambler but also as a tech writer.
Lemme introduce you to the world of sports betting analytics.
You see back in the day, before the advent of computing into mainstream culture, gamblers like myself used to rely on their ‘guts’ when placing a bet. And that worked just as well as you’d expect, many more losses than wins.
Turns out the human brain for all its creativity and inventiveness is not all that good at making predictions. We are susceptible to all sorts of biases and emotions which do not play well when trying to make an accurate prediction. I mean don’t get me wrong, emotions are what makes betting such an interesting activity. There is simply nothing like the thrill of the prospect of winning millions of dollars off a hundred-dollar bet.
But that’s all they are, emotions. And when it comes to making predictions, they are often an impediment. Fortunately for us, computers came to the fore and much as bettors wanted to continue relying on their ‘gut-feelings’, there is no competition with the power of computers.
What began as a disruptive movement in the sports betting industry is now standard practice. Betting now relies heavily on analytics. With modern tools, bookmakers and punters alike are utilizing analytics to get an edge in the market.
And at the heart of this movement is big data. In fact, by definition, there is no analytics without big data. After all, you do need numbers to crunch before you get on crunching.
The birth of analytics in sports betting for many can be traced to Billy Beane’s innovative use of a system called sabermetrics to recruit players for the Oaklands Athletics baseball team. As general manager of the team, Billy found himself with the almost impossible task of finding talented players with a limited budget. Instead of going the old way of trying to recruit star names, Billy relied on data to identify players whose values were way lower than their actual abilities.
As a result, he managed to assemble a pretty good team on a limited budget. One that went on to win the 2002 American League West title creating an amazing story that became the plot of the famous movie Moneyball.https://www.imdb.com/title/tt1210166/
Most importantly however Billy Beane ignited a movement that not only transformed baseball recruitment but revolutionized global sports.
In today’s game, in whatever sport, data is at the centre of everything; be it recruitment, game and player analysis and most importantly even betting.
So how does it work?
Well first, it is important to recognize the impact that technology has had on today’s betting. For one, most betting today is online. Most people don’t go through the hassle of buying a ticket in a betting house, rather they place bets on their devices from the comfort of their homes.
Bookmakers also rely on data to determine the value of the options they present to their customers. For example, in European and African markets data on teams and players’ form, injury records and previous head-to-head between two opposing teams is used to create odds for each team, say Arsenal (4.00) versus Liverpool (1.93). These odds are created due to each team’s form, player ratings and recent head-to-head results. From these odds, bookmakers place Liverpool as favourites to win.
Sounds easy, yes?
Well in a sense it is. That is if games panned like they do on paper. But sometimes (and this is a lot of times) nothing goes as planned. The weaker team puts up a fight and gets a result, mostly a draw, but even a win is possible.
And that game is rather easy to predict, there is a clear favourite. Which team do you choose if the odds are about the same? Say a game between midtable teams Southampton (2.40) versus Crystal Palace (2.60). No one is a clear favourite in this match-up.
This is where analytics comes in. Specific data like xG or xGA are today included in the data used in prediction.
The term xG in football is an abbreviation that stands for ‘expected goals’. It is a statistical measurement of the quality of goalscoring chances and the likelihood of them being scored.
xG is used by both bookmakers and punters alike to ensure they have not over/under-valued the odds for each possible result. It is today one of the most reliable used data points used to determine how a player or a team has played. A higher xG means the team or the player had more chances to score than the opposing team.
So, in our game, if say Southampton have had a higher xG in their previous games than Crystal Palace then a home win would be a good bet. A more cautious bet would be a double chance on a home win or a draw.
Whatever your choice, no matter the previous results and the presented odds, statistics like xG give punters an edge in the market. Combine these with sophisticated algorithms used by seasoned ‘professional’ punters and you have an industry that works much like the stock market.