Get the best bet tips with Sports AI
Backtesting Sports AI football predictions on home-win markets from February 1 to April 9 showed 13.9% ROI across 2,787 bets with fixed €100 stakes — approximately €37,000 profit. Filtering to bets with a minimum 14% edge raised ROI to 27.62%. 1xBet provided the most betting opportunities with 1,024 qualifying bets, followed by William Hill with 527.
Sports AIs football predictions can help being a more successful sports bettor. We can offer you the most accurate and profitable 1X2 tips on the market. In this blog post we're going to take a look at the results that can be achieved with our football predictions. For that, we are analyzing the football markets from February 1st until April 9th.
In the end, it's all about the prices that are offered to you. If you approximately know the probability of a certain outcome of a sport event, you can also determine a fair price for that outcome. A classic example for that is a coin toss with fair odds of 2.00 (2.00 = 1/0.5 with 0.5 being the probability of the outcome). If you now get a price above these fair odds of 2.00, you have successfully found a thing called value bet. The value results from the fact hat odds above 2.00 are overpriced. Applied to the coin toss example it means that if you for instance get odds of 2.10 for a betting on heads, you will in the long run pretty sure make some decent profit.
Here's a little example of how you would take a betting decision. Let's take the match Tigres vs. Patriotas from the Copa Colombia played on 6th of April. Sports AIs algorithms predicted a probability of 40,48% Tigres winning the match. If you transform the probability to an odds format (1/0,4048) you get fair odds of 2,47. William Hill for example offered a price of 2,75 for a home win of the Tigres, which leads to an edge of approximately 11%. In such a case, it is advisable to bet on this outcome at that price of 2,75 offered by William Hill.
If you apply this strategy to the period under consideration, then following results would have been achieved. Notice, that in this example only bets on the home team winning in a football match were placed.
As you can see in the chart above, the results are very satisfying. With a fixed stake of 100€ per bet, 2.787 bets could have been placed and a profit of approximately 37.000€ could have been accumulated. In the end, with this strategy, a ROI of 13,9% could have been achieved.
The results above show the results with the following strategy: Bets were placed if an edge of at least 3% was found. The higher the edge needs to be in order to place a bet, the higher the ROI will probably be. And that's exactly what the results show us. You can see that there is a positive correlation between the minimum edge of a bet (called threshold on the right side) and the ROI. The downside though, is that the amount of matches meeting the criteria get lower the higher the threshold is set.
With a threshold of 14% we achieved a ROI of 27,62%!
The following bookmakers were included in the analysis: Bet365, William Hill, Marathon Bet, Unibet, Bet at home, GGBet, bwin, PariBet and 1xBet.
The chart below shows how many betting opportunities were found for each bookmaker. The results refer to the strategy where a minimum edge of 3% was used.
The results show that 1xBet is the best bookmaker to use with our strategy when it comes to the amount of betting opportunities. With 1024 bets placed at 1xBet, this bookie takes the lead at this statistic followed by William Hill with 527 bets. At the end of this statistic we will find Bet365 with only 26 betting opportunities.
At this point, there is no use in comparing the ROI per bookmaker since the amount of bets varies a lot between bookies. That's something that can be analyzed in the future.
Hopefully this blog post will help you to better understand the potential of Sports AIs bet tips and sports predictions. In future posts other markets and also other sports will be analyzed in order to give you a broader picture of the potential of Sports AIs predictions and bet tips.
In our backtest from February to April, Sports AI football home-win predictions achieved 13.9% ROI at a 3% minimum edge threshold across 2,787 bets. Raising the threshold to 14% improved ROI to 27.62% with fewer qualifying bets. These figures represent historical backtests — real-world results depend on bookmaker availability, odds timing, and market conditions.
In our analysis, 1xBet offered the most football betting opportunities with 1,024 qualifying bets at a 3% minimum edge, followed by William Hill with 527. Bet365 had only 26 qualifying bets, indicating tighter pricing. Bettors should maintain accounts with multiple bookmakers to maximize access to value opportunities as they arise.
Sports AI calculates win probability for each team using machine learning models trained on historical results, current form, expected goals (xG), home/away splits, and injury data. When the model's implied probability for an outcome exceeds the bookmaker's implied probability by the minimum edge threshold, the bet is flagged as a value opportunity worth placing.
The edge threshold is the minimum difference between the AI's estimated probability and the bookmaker's implied probability required before placing a bet. Higher thresholds filter out marginal bets, resulting in fewer trades but higher average ROI per bet. Our data shows a clear positive correlation: a 3% threshold produced 13.9% ROI, while a 14% threshold yielded 27.62% ROI with significantly fewer qualifying bets.