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This guide introduces shift-left testing and its benefits. Learn to increase your SDLC velocity and minimize bugs at release by shifting testing left.
In April 2021, football giant Florentino Perez infamously defended the proposed creation of a European Super League (ESL). Through planned streaming deals with Amazon and Facebook, greater spectacle and shorter match times, the ESL appeared an attempt to keep football relevant in the age of video games and online content. “Young people are no longer interested in football,” claimed Perez, because “they have other platforms on which to distract themselves.” He was likely referring to Twitch and YouTube, where Generation Z now spend more time watching other people play video games than many major sporting events.
Make no mistake, esports tournaments are nowhere near close to drawing in the same viewership as the FIFA World Cup, but that’s only because esports are just starting out. Speaking on the future of esports in a press article, the founder of G2 Esports explained: «Everybody knows about football. Some play it. Some don’t. Some watch it. Some don’t. But definitely, everybody knows it exists. We’ll get to that point with esports at some point in time.» And esports is already catching up at lightning speed. Data released by Statista valued the global esports market at around 1.08 billion US dollars in 2021 — an almost 50% increase from the previous year. In what seems like overnight, esports growth has doubled, opening up the path for the rise of esports betting.
That said, attributing the rise of esports betting simply to the rise in esports is too simplistic. The rise of esports betting is the direct result of the superior customer experience inherent in betting on esports compared to traditional sports.
The key differentiator driving the rise of esports betting is data. In producing a high volume of low-latency data, esports lend themselves more obviously to betting, which relies on data to inform odds and determine outcomes. In that they are run off a machine, esports can offer a far superior customer betting experience than traditional sports because data related to the game is distributed instantly and updated by the millisecond. Free from the restraints of manual data collection proper to traditional sports betting, and with huge amounts of accurate data to play with, bookmakers can provide customers with new and enhanced betting experiences.
Here are five opportunities that the rise of esports betting presents for bookmakers and betters alike, as well as their respective challenges.
Crucial for grasping the significance of the rise of esports betting is the knowledge that information is key to making money in the gambling industry. If you’re a bookmaker, you ideally need to know the outcome of an in-play bet the split second it happens. Any delay between an event taking place and the betting market receiving this information could result in financial losses if it means that gamblers ascertain the outcome of a bet before you do. In a practice known as courtsiding, spectators watching a sporting event in person can witness an event take place in real time and retrospectively bet on it before the bookmaker has a chance to process the outcome, thereby cheating the system.
Entirely eliminating this delay from traditional sports betting is impossible due to the manual nature of the data collection. Tennis is the classic example; no matter how quickly an umpire presses the button to update the score after a point has been scored, it will always take them a number of seconds (and that’s if they’re not corrupt). In an industry where the business model relies on nobody else having access to information before you do, the rise of esports betting is a game changer. In esports betting, relaying information relating to outcomes is instantaneous. Through automated data extraction and distribution technology, gambling operators can receive official rights-held data instantaneously and straight from source.
Besides receiving data in real time, the digital nature of esports allows gambling operators instant access to all game-related data. This has driven the rise of esports betting because bookmakers can now offer a broad spectrum of in-play bets with little effort. In traditional sports, in-play betting can only reach a certain level of complexity before it becomes too difficult for bookmakers to manually track and report outcomes. Moreover, given the relative simplicity of traditional sports to esports, there are few things that can happen in a sporting event that it makes sense to offer bets on, like the team to win the next corner or throw in, in the case of football.
Because esports run on machines and produce vast amounts of data, they can benefit from machine learning, which presents two advantages. First, the more tournaments that take place, the more accurately bookmakers will be able to price pre-game odds in the future. Second, built-in algorithms can update in-play odds by the millisecond as events unfold; in CS: GO, for example, a game-win probability could be calculated by combining the current score, map difficulty, equipment value, money carried, and player skill. Many characteristics that such an algorithm could take into account, like player health, aren’t trackable or even quantifiable in traditional sports. This enables esports bookmakers to build a highly accurate picture of likely outcomes.
While machine learning is a driver of the rise of esports betting, the complexity of esports compared to sports like tennis makes them tricky to model. In other words, to be able to create these algorithms in the first place, you need to work out which in-game events are actually impacting certain outcomes. Given that esports haven’t been around for so long, League of Legends, Dota 2 and CS: GO are currently the only fully-modelled titles. For newer titles, there is currently a real opportunity for punters with in-depth understanding of the game to win money before the gambling operators have a chance to strengthen the models. There will be a period of adjustment for bookmakers, but it will pay off in the long term.
As with any sport, the more you understand the game, the higher your chances of placing a successful bet. In Formula One, an example of a highly strategic traditional sport, fans may take weather, track layout and driver starting position into account when assessing the likelihood of a certain outcome. Because F1 cars are machines, gamblers are also privy to information such as tyre wear and fuel consumption; this sets F1 apart from more traditional sports like basketball, where gamblers can’t tell how worn out or low on energy a player is. Esports are similar to F1 in the sense that the gambler has lots of valuable information to play with that only a machine can provide them with, like player health, respawn rate and tactical deployment. The more information a gambler has, the more tactical their betting strategy can be.
The challenge for bookmakers is to find ways of contextualising in-game events within the broader game strategy. If a League of Legends player slays a dragon, for example, does that tell you the player is having a good day in the same way that a goal in the first five minutes of a match might suggest a footballer is in good form? The diversity of esports titles and their respective complexity makes winning difficult for non-expert gamblers, who are up against a niche, clued-up esports audience. Breaking down different esports titles to sell them in a way that is digestible for a broader clientele will be crucial for bookmakers if they are to capitalise on the rise of esports betting and maximise potential revenue.
The availability of large amounts of game-related data opens up the possibility for new data-driven customer betting experiences. The most obvious of these are visualisations, such as informational widgets that help gamblers to keep track of the game down to the smallest detail. Map schematics can display the real-time movement of players on a virtual map; live log widgets can record events as they unfold, such as ‘player one killed player 2 at 10:12:15;’ and team scoreboards can document the characters’ status, such as health, kill count and inventory. The most significant visualisations for betting, however, are prediction trackers, which use machine-learning models to predict certain outcomes in real time, and comparison graphs, which provide at-a-glance comparisons between teams.
In parallel to the rise of esports betting, some esports production companies like Electronic Sports League (ESL) and Blast have provided fans with a new way to stake money in esports: tokenized digital content. Non-fungible tokens (NFTs), blockchain-based digital collectibles, could not lend themselves better to the esports model. If NFTs were introduced into games themselves as prize winnings, this could also open up another betting category for bookmakers.
Major bookmakers like Bet365, William Hill and Pinnacle Sportsbook already offer bets on multiple esports titles, including CS: GO, Delta 2, League of Legends and PUBG. While League of Legends is currently the only one to bring in the same revenue margins as traditional sports, GRID continually sees demand for both new titles and new datasets to support models. Esports may just be starting out in Europe, but they are already considered a sport in their own right in Asia, where professional players receive lucrative scholarships and sponsorships. If esports currently make up around 5% of sportsbook revenues in the UK right now, we predict that the revenue share between esports and traditional sports will be closer to 50/50 in ten years time. Watch this space.
Applause empowers leading online sportsbook and casino operators to deliver exceptional digital experiences your customers love. Whether your company needs to ensure online gambling works around borders, validate a new betting feature or identify transaction issues with specific payment methods, you will benefit from real-world testing. Learn more how Applause can help you grow your online sportsbook and casino business.
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