Automation set to sweep the sports trading floor?
Algorithms have automated trading in many areas of the financial world. Could sports betting soon follow suit? Scott Longley investigates.
The degree to which the world of financial trading is now dominated by automated trading is perhaps best illustrated by an article published on the tech news portal O’Reilly in January, which suggested it is now feasible for an amateur trader to attempt to beat the market by building their own trading algorithm utilising less than 100 lines of Python code.
As the FT said when flagging up this article to its readers, this might not be quite advisable; but it illustrates the extent to which financial trading is now a fully technology-driven process, with automated trading of financial instruments taking place with little or no human intervention.
Almost any kind of financial instrument — stocks, currencies, commodities, credit or volatility products — can be traded in such a fashion.
Not only that, in certain market segments, algorithms are responsible for the large majority of the trading volume.
Given the transformation of the complex world of financial trading, can the sports betting world be far behind?
Probably not, suggests David Loveday, now a consultant but formerly chief executive at OpenBet, and someone who knows about the current and future challenges of providing sports betting backend technology.
Odds compilers may become a thing of the past
“Is the sports betting market going to follow the financial markets down the fully automated route? Yes, I think inevitably,” he says. “The technology that underpins most of the bigger operators’ sportsbook backends is very much at the legacy end of tech.”
With the technology involved now so advanced – and with the example of what is happening in the financial world to act as a beacon – Loveday argues that it is now possible to build a better, more responsive system that would also be more reliable.
“The tech advances that are out there in finance might soon enough rock the foundations of the current sports betting market giants,” he says.
Indeed, for some providers in the area the future is already upon us. “The days of manual trading are on their way out,” says Paolo Personeni, managing director at Betradar’s Managed Trading Services (MTS) business.
“The foundations of any sportsbook can now be fully automated thanks to the algorithms, the quants analysis and models and the technology. The idea of having large teams of people compiling odds is likely to very soon be somewhat archaic.”
The MTS offering – which has 90 customers globally now working with it – takes a step forward from just offering a slimmed-down and automated trading operation. It offers a combination of algorithms and high-quality trading, and also promises to take the volatility out of sports betting.
“Commercially we are now able to bear 100% of the risk,” says Personeni. “We have worked on this for the past year, working with the big data and it means we can model and price in a completely new way.”
The work Betradar has done with the big data available is key to the MTS development. “We are challenging the legacy trading room status quo,” he says.
Similarly working on the next generation of sports betting technology is Gaming Innovation Group’s iGaming Cloud unit, which has put together an iBetting Cloud offering that has already launched with German-facing sportsbook Wetten.com.
Christopher Langeland, managing director at iGaming Cloud, says that the increased automation of sports betting will be an evolutionary process.
“There is absolutely no question that automation can deliver huge gains in efficiency, accuracy and coverage,” he says. “If it’s designed and built well, fully-automated systems can be fantastic tools.”
Evolution, not revolution
He does caution, however, that innovation in technology is never a straight line graph, forging ever upwards towards some future ideal. “There’s always a rush to say ‘this will be a game-changer’ but, in fact, real revolutions are very rare. Increased automation of sports betting will be an evolutionary process.”
It is definitely a process that is already under way. Services such as Sportradar’s MTS and the iBetting Cloud offering are part of a noticeable wave of innovation in this area, which includes start-ups in the space such as ioSport and Stratagem, the latter of which is looking to provide a sports trading offering which can predict sports outcomes.
Andreas Koukorinis, founder at Stratagem, says his business has made a big investment in artificial intelligence and machine learning to put together the makings of a platform and putting together a common language to deal match up sporting events with betting lines.
“These are all established ideas in finance,” says Koukorinis. “I don’t know why it hasn’t been so prevalent in sports betting. Maybe the data wasn’t easily available. But I do know that getting the data to talk to each other is really hard.”
The data may be available now but as Langeland points out, the complex nature of sports events remains an obstacle. “Like large quoted companies, sports events are massively complex and multifaceted structures where the whims and decisions of fallible humans can influence the end results, as can external contextual factors,” he says.
Algorithms, he says, aren’t enough on their own just yet. “For the foreseeable future a mix of increasing automation with a bit of skilful human steering is going to be the best way to go.”
He adds that “clever automation can help smaller operators emulate the effects of brute manpower”, leaving companies the challenge of concentrating on the areas where they have to truly compete with the larger operators, in particular marketing.
Still, the developments to date wouldn’t have been possible even just a few years ago when the access to first, the necessary tech, and second, the data, was limited.
“The actual technology is now a commodity,” says Personeni at Betradar. “But none of this would be possible without the access to the data.”
As with other areas of technology, we are certainly moving down the road towards automation and importantly for the operators the hoped-for cost savings that will be associated with it. We aren’t there quite yet; the “holy grail”, as Koukorinis puts it, is a few years away.
But the steps on the road are being marked out. The only questions now are about speed of travel, not direction.