Made Rs. 8000 using Machine Learning models in 1 day...
Here's how I modelled my data:
- Got statistics of the entire Pak and Ind squads with their last 5 performances.
- Got statistics of Last 3 games at Nassau County Stadium.
- Got betting odds for all of these matches.
Used a very simple XGBoost model to get the implied odds for betting odds and compared it to the actual odds. Model did well on Test and Validation set using K-Fold Cross Validation.
Compared the predicted odds and actual betting odds, figured there is some positive E(V) here. So made two bets of 10k each. Made 8k in 1 match.
Unemotional after winning and unemotional even after loss.
Talking product sense with Ridhi
9 min AI interview5 questions
I asked ChatGPT what this means:
Firstly, this individual gathered a lot of data, including statistics about the players in the Pakistan and India cricket teams, their recent performances, data specific to the Nassau County Stadium for the last three games, and also the odds that bookmakers were offering for these matches.
They then used a machine learning technique called XGBoost to analyze this data. XGBoost essentially helps predict outcomes based on given data. In this case, it was used to predict the implied odds for the matches based on the statistics gathered.
To make sure their predictions were reliable, they tested their model on separate sets of data (Test and Validation sets) using a technique called K-Fold Cross Validation. This helps ensure that the model performs consistently well across different datasets and doesn't just work well by chance.
After comparing their model's predictions with the actual betting odds, they found that there was a positive expected value (E[V]). This means that, on average, their model was predicting odds that were better than what the bookmakers were offering.
Feeling confident in their model, they made two bets of 10k each. In one match, they made a profit of 8k.
What's impressive here is that this approach seems to have paid off, indicating that with the right analysis and data, it's possible to make informed betting decisions. Additionally, the individual remained unemotional both when they won and when they lost, which is crucial in maintaining a rational approach to betting.
Just stay focused on the process, I trade the markets using the same logic. Using Machine Learning it is fairly trivial to use uncorrelated exogenous variables which makes it crazier than ever.
Make a YouTube video and share link
sheesh man, does this really work for majority?
impressive!
Is this a reproducible result?
This doesn't work. You just got lucky. People in my Team create models for every cricket/football world cup. It doesn't work mostly
This is very impressive.