Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Add new project IPL Score Predictor using Deep Learning #590

Closed
karthikyandrapu opened this issue Oct 26, 2024 · 4 comments · Fixed by #592
Closed

Add new project IPL Score Predictor using Deep Learning #590

karthikyandrapu opened this issue Oct 26, 2024 · 4 comments · Fixed by #592

Comments

@karthikyandrapu
Copy link
Contributor

IPL Score Predictor using Deep Learning

Is your feature request related to a problem? Please describe.
Currently, there is no effective way to predict the score of an IPL cricket match based on real-time factors like venue, batting team, bowling team, striker, and bowler. This feature would help cricket enthusiasts and analysts gain insights into match outcomes as the game progresses.

Describe the solution you'd like
Develop a deep learning-based IPL score predictor that uses real-time data inputs, including venue, teams, and player specifics, to generate a predicted score for an ongoing match. The predictor would analyze historical data to identify patterns and provide an estimated score.

Describe alternatives you've considered
Alternative solutions include:

  1. A statistical regression model that relies on simpler statistical methods rather than deep learning.
  2. A machine learning model like Random Forest or XGBoost that could offer faster predictions with potentially less accuracy than a deep learning model.

Approach to be followed (optional)

  1. Gather and preprocess historical IPL match data, including match venues, teams, players, and scores.
  2. Build a deep learning model with layers that can handle both categorical (e.g., team names) and numerical data.
  3. Train the model using historical match data to predict scores based on similar scenarios.
  4. Validate and test the model's accuracy using real-time match data.
  5. Deploy the model for public use via a command-line interface or web app.
@karthikyandrapu karthikyandrapu added the enhancement New feature or request label Oct 26, 2024
Copy link

Thanks for creating the issue in ML-Nexus!🎉
Before you start working on your PR, please make sure to:

  • ⭐ Star the repository if you haven't already.
  • Pull the latest changes to avoid any merge conflicts.
  • Attach before & after screenshots in your PR for clarity.
  • Include the issue number in your PR description for better tracking.
    Don't forget to follow @UppuluriKalyani – Project Admin – for more updates!
    Tag @Neilblaze,@SaiNivedh26 for assigning the issue to you.
    Happy open-source contributing!☺️

Copy link

Thanks for raising this issue! However, we believe a similar issue already exists. Kindly go through all the open issues and ask to be assigned to that issue.

@karthikyandrapu
Copy link
Contributor Author

@UppuluriKalyani , I couldn't find any similar projects.

Copy link

Hello @karthikyandrapu! Your issue #590 has been closed. Thank you for your contribution!

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Projects
None yet
Development

Successfully merging a pull request may close this issue.

2 participants