Showing 4 open source projects for "sports"

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  • 1
    Run Page

    Run Page

    Make your own running home page

    GitHub Actions manages automatic synchronization of runs and generation of new pages. Gatsby-generated static pages, fast. Support for Vercel (recommended) and GitHub Pages automated deployment. React Hooks. Mapbox for map display. Supports most sports apps such as nike strava. Automatically backup gpx data for easy backup and uploading to other software.
    Downloads: 0 This Week
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  • 2
    Expert Baseball Skipper

    Expert Baseball Skipper

    A software that helps you manage a baseball team (real or fantasy).

    Expert Baseball Skipper is a libre (as in free software) software used to manage a baseball team, whether it’s a real baseball team or fantasy. While still in its early stages, Expert Baseball Skipper is a modern take on LazyDogSoftware’s Baseball Memories (https://archive.org/details/tucows_247031_Baseball_Memories). Expert Baseball Skipper is actively being tested with the use of the most advanced baseball simulator on the web; https://www.franchiseball.com.
    Downloads: 0 This Week
    Last Update:
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  • 3
    Tartan Systems

    Tartan Systems

    Free Open Source Accounting and Club Systems

    ...The modules comprise the following: Asset's Register Book Clubs (Member and Book Register) Booking's Manager (Resorts and B&B's) Bowls Clubs (Lawn Bowls Tabs Draws and Competitions) Bowls Sectional Competitions (Lawn Bowls) Creditor's Ledger (Accounts Payable) Debtor's Ledger (Accounts Receivable) General Ledger (Nominal Ledger) Loans Ledger (Fixed and Variable Term Loans) Member's Ledger (Sports and Other Clubs) Rental's Ledger (Property and Collection) Salaries and Wages - ZA (Includes Staff Loans) Sales Invoicing (Includes Sales Orders, Quotations and Works Orders) Store's Ledger (Inventory)
    Downloads: 0 This Week
    Last Update:
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  • 4
    AlphaPy

    AlphaPy

    Python AutoML for Trading Systems and Sports Betting

    AlphaPy is a Python-based AutoML framework tailored for trading systems and sports betting applications. Built on popular libraries like scikit-learn and pandas, it enables data scientists and speculators to craft predictive models, ensemble strategies, and automated forecasting systems with minimal setup. Run machine learning models using scikit-learn, Keras, xgboost, LightGBM, and CatBoost. Generate blended or stacked ensembles.
    Downloads: 1 This Week
    Last Update:
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