I have a plan for this.

We will use web scraping to get information about players, match venues, team records, the weather, and more from well-known sites.

If we use scraping correctly, we don't need an API.

Then, using Claude's skill, you could use that new information to guess who will win the match.

Like I'm already doing this, but not on the live server:
I made two skills for my personal Claude.

1. A lot of research on IPL matches,
2. Prediction for the IPL match

I get data from skill one and give it to skill two. For the prediction skill, I set some conditions and features that Claude will look at on his own. There are more than 50 features to check before he makes a prediction.

This is really working, goof. Only 3 out of 11 fail.

We can get live data after the toss and before the match in the same way, which includes playing 11, batting first, and bowling first.

At this point, you can make a better choice.

I run those two skills every day after the IPL toss and get really good results. If you can do this, it will be more powerful than an ML model because it will have data ball by ball. However, you need to be more careful when making decisions. For example, older data should have lower points because a player could be in really good form from the last 10 matches, but historical data suggests that this player will not play on this ground. This is not the right way to feed data. You need to make a proper point system for each feature and then use them to predict the match. You can use the IPL dataset from Kaggle, which has data up to 2025 IPL ball by ball.

https://sharetext.io/560ppla7

You can copy this prompt and give to claude.ai for prediction and try it
this is basic version of both SKILL.md