I developed an AI betting advisor for Premier League games with a custom prompt:
def forecast(gameInfo):
return {'secure': 'low', 'daring': 'high'}
Any similar experiments?
hey, i tried a similar ai approach but couldnt get it consistent. the analysis was quirky and odds shift roughy. not perfect but its a start if you dnt mind the risks.
Hey everyone, I’ve dabbled a bit into using AI for betting analysis too. I set up a little script that would play around with predictions on some game stats—not exactly Fortune Teller level, but it added an extra twist to my usual research. It was almost like having a chat with a friend who sometimes throws in a quirky suggestion; it wasn’t always spot on though! I found that mixing in some human intuition with the device’s output kept things lively. It’s really fun to see how these experiments can evolve over time, even if they’re just a casual experiment. Excited to see what everyone else comes up with. Happy tinkering! 
hey, i played around with an ai model for nba bets. it was pretty all over the place sometimes, but still fun. not as reliable as solid intuition but adds a cool twist. give it a whirl if you’re up for some unpredictability!
i have experimented with ai based betting analysis and found that mixing automated forecasts with real-time sport insights can produce both promising and erratic outcomes. In one project, i developed a model that predicted trends based on historical and current data. however, its predictions were sometimes inconsitent due to changing team dynamics and unforeseen events. blending the model’s suggestions with manual research often improved the reliability of the recommendations. from my experience, it is essential to continuously refine the algorithm and integrate diverse data inputs in order to achieve a more balanced and acurate wagering strategy.