How sports technology can change sports betting

Some of the most impactful and exciting innovations in sports tech are coming from applying machine learning (ML) and artificial intelligence (AI) technology to optical tracking systems, otherwise known as computer vision.

A basic definition of computer vision is training a computer to understand and automate tasks that the human visual system can do. Within sports, this includes training software to automatically detect and tag players’ movements and actions on the field or the court. This provides coaches with real-time tactical analysis, media production teams with a library of enhanced content and sports betting providers with a new way to gather official data on a game.

Traditional manual methods of sports data collection and analysis are labour intensive and open to human error. They require people sitting in the stadium watching the game, manually reporting what they’re seeing. This is then fed back to a team of analysts to number crunch and return to the broadcaster to overlay on their coverage.

Computer vision, AI and ML enables the automated collection and analysis of sports data, thereby creating operating efficiencies while bolstering the integrity of data. With the majority of sports leagues and competitions cancelled or postponed due to the global coronavirus pandemic, sports betting operators looked to sports and events at lower competition levels and in more remote locations.

Criminal elements took advantage of this newfound attention on obscure sports to corrupt local data scouts to create “ghost matches” (games that never actually take place but are faked with data to defraud bookmakers) as well as unsanctioned, rigged tournaments.

The speciality camera infrastructure for these optical tracking systems still come with significant sunk costs. However, as computer vision software continues to advance, it’s feasible that footage captured off a smartphone in a fixed location would be sufficient for an official data source.

If it’s cheaper to provide high quality broadcast coverage of more games, it also means there’s more games for fans to watch and place bets on. This is particularly important for lower division and niche sports looking to secure their share of legal, regulated gambling revenue.

For the fans

Another revolutionary impact of AI, ML and computer vision is enabling rights holders to offer deeply personalised content directly to their fans.

The AI algorithms learn what a fan likes, to essentially become an artificial producer, delivering customised content based on their preferences (advanced stats, focus on a particular player, unique or multi-lingual audio commentary, different camera angles).

AI and ML empowers fans that chose to bet on games to have an experience deeply customised to their preferences. By the same token, those that do not want to engage with gambling can have an experience free from odds or betting language (e.g. parental controls).

The potential of this technology is highlighted in the partnership between the NBA and Microsoft, announced earlier this year. As part of the deal, Microsoft will develop a new direct-to-consumer (D2C) platform on the Microsoft Azure cloud service that will use ML and AI to deliver “personalised game broadcasts as well as other content offerings that will allow the NBA’s global fanbase to customise and localise their experience”.

Betting was not specifically mentioned in the announcement, however fantasy sports was referenced as a key part of the fan experience, and the focus of this new partnership has obvious immediate applications to sports betting.

An example is a customised highlights or live-game experience based on how a fan’s individual prop-bet or parlay/multi-leg is placed: switching camera angles to focus on each relevant piece of action within games and a stat overlays adjusting based on how each part of the wager is performing in real-time.

Thomas Alomes is a global leader in sports technology ecosystem growth and development with a passion for connecting the best people with the best ideas. He is the host of Sports Tech Feed, The Global Sports Technology Podcast, and head of North America for the Sports Tech World Series (STWS), the largest global community of its kind in sports data, digital and technology. He also serves as chair of the Commercial Leadership Board of the International Sports Technology Association.