Sports betting is among the key factors driving engagement and revenue in the sports industry. Watching a sports match or tournament as a mere spectator and as a bettor delivers a different experience to fans. Betting makes the games more exciting to watch and there’s a possibility of getting a return depending on your predictions. However, winning sports bets isn’t always a straightforward process.

Winning sports bets requires in-depth analysis of historical and current data to increase your probability of making an accurate bet. That means data can significantly increase your chances of winning, but you’ll need the technology to analyze large data sets with accuracy. Here’s a look at the technology behind sports betting analytics.

Artificial intelligence

Artificial intelligence (AI) isn’t something new in the sports industry. In the sports betting market, the technology has proven essential in analyzing huge sets of historical data within seconds to identify patterns and predict match results. However, the technology isn’t limited to predicting wins or losses, as it extends to multiple bets like player performance and live betting options.

But can AI predict sports betting outcomes with 100% accuracy?

Unfortunately, while artificial intelligence is great at calculating the mathematical probability of different outcomes, it doesn’t guarantee you a win. For instance, when betting on an EPL game featuring Arsenal vs Bournemouth at Unibet, an AI-powered system can predict the probability of Arsenal winning at 70%, Bournemouth winning at 24%, and a tie at 6%. However, that doesn’t mean that Arsenal can’t lose or tie against Bournemouth.

Cloud computing and IoT

Cloud computing supports real-time data processing in matches/ tournaments, giving bettors instant feedback on the player’s performance metrics. That supports dynamic decision-making when betting to give you an edge over the oddsmakers. For instance, you can adjust your in-play betting strategy based on live data related to player fatigue levels and defense tactics.

Internet of Things (IoT), on the other hand, can help to automate the sports betting market. The technology enhances in-play betting by providing real-time odds and data from games while helping operators improve their security by monitoring and detecting suspicious betting activity. Additionally, IoT increases player engagement and helps bettors turn sports data into actionable insights to improve their chances of making accurate predictions.

Machine learning

Machine learning is practically a subcategory of AI. The technology adapts and learns from the available data, improving over time. As such, ML algorithms can analyze historical information about a player, match, or tournament, identifying trends that you might miss using the naked human eye.

When betting on sports, machine learning can be used on anything from the team’s performance throughout the season to injuries, player transfer, and much more. The technology aims to find valuable bets where the sportsbooks’ odds don’t reflect the true probability of the event. However, even sportsbooks use complex machine-learning algorithms to know the probability of different outcomes when setting odds.

Text and sentiment analysis

Also known as emotional artificial intelligence, sentiment analysis refers to leveraging natural language processing systems, text mining, and computational linguistics to attract subjective information from users. In sports betting analytics, text and sentiment analysis help experts predict match results more accurately by analyzing user-generated information like social media posts, blog comments, and more.