Football betting in Kenya has been revolutionised over the last few years by the influx and availability of new apps, together with improved access to matches. Betting companies are now using technologies like machine learning alongside AI to better acquire information about customers and offer tailor-made experiences and additional features.
A 2024 GSMA report revealed that mobile connections increased throughout the population by a massive 118.7%. Smartphone usage is becoming more prevalent and internet penetration has reached 40%, meaning online access to betting facilities is widespread.
A large number of Kenya's betting app users are disenfranchised and unemployed young people who depend on social media to receive news about the world. The majority of these youngsters are likely to place high-risk bets on lightly regulated sportsbook sites in the hope of winning life-changing amounts of money. Today, we will take a look at the operators' use of real-time prediction, its influence on the market, and the future.
The role of real-time predictions
There are a few ways in which real-time predictions have impacted
betting behaviour in the Kenyan market. First, we will discuss the functional
aspects and then address the implications of this shift within the sector.
Betting during a game is now easier than ever, and bookkeepers can adjust live odds to accommodate changing game trends and keep punters engaged throughout. This live version of betting provides instant experiences that allow punters to adjust their decisions as the game progresses, thus helping to prevent losses or to capitalise on the changing odds.
AI and machine learning apps are very common in today’s betting platforms. They vary from Opta’s supercomputer to Flashscore and LiveScore, alongside many others. These models enable punters to learn the underlying stats behind predictions and assist them in making more accurate predictions. Other predictive models like Eagle Predict take it a step further and calculate the statistics that would be extremely difficult to analyse manually. The user is then shown a more complete picture of what could affect the game. Given how much money people lose on complex parlay bets, these tools provide a way to minimise the placing of ill-informed bets while still allowing gamblers to enjoy themselves in a safe manner.
Some gamblers have come up with ways to build their models using machine
learning and AI to inspect their bets over time, coordinating their habits and
tastes to become more accurate. This approach can be great for minimising risk
and potential losses. Another aspect is to consider that more specialized
markets have emerged, and real-time predictions have provided markets such as
player-specific bets and minute-by-minute betting. This allows the bettor to
explore opportunities and use novel strategies and interests.
More people are participating – in the early days of gambling in Kenya, punters would keep their records in a common form of hand-recorded, written paper or an Excel sheet. The entry cost was quite high, which meant fewer people took the risk to venture into gambling. It was also difficult to gamble, as apps, smartphones and the internet were not as prevalent as they are now. With live data and access to records, more people are spending money on bets already pre-set for them or advocated for by sportsbooks, just because it is simply so easy to do so.
The darker side of real-time data usage
· Gambling and betting are now more accessible and perhaps less risky for some clever gamblers, but certain risks are worth knowing about. These come in the form of practices instituted by thesportsbook. Even with regulations, some gaps could still be exploited.
- Constant real-time data access can encourage risky bets. Real-time data can make the bettor overconfident and prone to riskier actions. These actions could be in the form of loss chasing or placing careless bets simply because they come with an offer. A classic example of this is parlay bets, which are really difficult to win but pay a lot if your bet comes through. The near miss effects that such bets cause may stimulate gamblers to bet harder at their own expense.
- Companies use push notifications manipulatively. While users can go into settings and disable notifications, most won't because some of the messages will be useful and you'll want to see them as soon as they pop up. However, notifications for trending bets, odds changes and promotions create a sense of urgency, along with the FOMO (fear of missing out). They instil the habit of checking the app every now and then, which can lead to impulsive betting or addiction. The alerts are like intermittent reinforcement that is present in other forms of gambling, further anchoring bettors in a vicious cycle.
- Risky in-game and prop bets are easier to make. With real-time data, in-game and prop bets have become much easier to make. These forms of betting allow one to place bets on specific events in a game. Corner kicks, player performance and cards issued are some of the examples of such risky in-game bets. All these lend flavour to the game but also enhance the rate and immediacy of bets provided, which can increase losses.
- Targeted marketing encouraging betting is more precise and personalised. Some of the largest and most visible advertising campaigns in Kenya are run by gambling companies. The same is true even in games, where real-time data is used to design promotions that sound realistic or very attainable. The ads reach young adults and sports enthusiasts while normalising gambling in sports culture. The exposure through repetition makes people numb to the potential harm and slowly encourages more users into betting.
How can real-time
data be used to help problem gamblers?
It is no secret that bookmakers have a great deal of information about their customers. They have been criticised for using that information and their high contribution to nationalrevenue to ban winners and take advantage of those who they can recognise as having gambling problems. With the right change in policy and consciousness to push more open legislation, this data could be used for responsible activities such as:
Use of real-time data for intervention. Norsk Tipping is a relatively new intervention system that uses personalised messages to encourage moderation or provide support material. The system has posted some high success rates and such a system can pick up on problems early and help guide bettors away from those ‘riskier’ behaviours. The data can be used to push and create individualised policies that protect bettors even more forcefully with self-exclusion programs, and identify those at risk to help them at an early stage.
Predictive analytics. Experiments
have shown that machine learning can effectively identify problem gamblers
using behavioural data. This can then be applied to prevent disordered gambling
behaviour.
