Contact person: Business Client

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Location: Alberton, Australia

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"I need a web-based system that forecasts three key outcomes—moneyline (H2H), line/spread, and total points (over/under)—for the following sports: NRL, AFL, NBL, NBA, NHL, MLB, and NFL.

Core requirements
• Model training must rely on historical game data only; I already have access to public datasets and can provide sample CSVs if that helps.
• Weather, venue, date, and start-time should be treated as additional features to improve accuracy.
• The interface should let me:
– browse upcoming fixtures with the model’s probabilities and suggested picks
– record the bets I actually place (stake, odds, outcome)
– view running profit/loss and basic analytics such as win rate and ROI.

Technical notes
• Deploy as a responsive web application so I can use it from both desktop and mobile browsers.
• I’m comfortable with common stacks (Python + Flask/FastAPI, Node.js, etc.); choose whichever you find most efficient, provided the code is well-commented and easy to maintain.
• Please include instructions for retraining the model when new season data becomes available.

Deliverables
1. Clean, documented source code for the prediction engine and web front-end.
2. Script or notebook showing data preprocessing, feature engineering, model training, and evaluation metrics.
3. Deployment guide (Docker or similar) so I can spin the app up on my own server.

I’m aiming for a solid functional prototype that gets predictions up and running quickly, with room to iterate once real betting results start flowing through the tracker." (client-provided description)