Football Match Outcome Prediction Model
Budget: $750 – $1,500 USD
I need a machine learning model using XGBoost to predict football match outcomes, focusing on all league matches. You will leverage multiple football APIs (SofaScore, API-Football, etc.) for comprehensive data.
Key Requirements:
- Predict 1X2, Over/Under, BTTS, and correct score and all other predictions outcomes
- Utilize extensive data: results, player stats, odds, weather, team lineups, injuries, standings etc.
Ideal Skills and Experience:
- Strong background in machine learning, particularly with XGBoost
- Experience with football data and prediction models
- Proficiency in handling and integrating data from multiple APIs
- Excellent programming skills (Python, R, etc.)
- Ability to validate and test model accuracy
Please provide relevant experience and approach.
Key Requirements:
- Predict 1X2, Over/Under, BTTS, and correct score and all other predictions outcomes
- Utilize extensive data: results, player stats, odds, weather, team lineups, injuries, standings etc.
Ideal Skills and Experience:
- Strong background in machine learning, particularly with XGBoost
- Experience with football data and prediction models
- Proficiency in handling and integrating data from multiple APIs
- Excellent programming skills (Python, R, etc.)
- Ability to validate and test model accuracy
Please provide relevant experience and approach.
Related categories:
Python
Software Architecture
Machine Learning (ML)
Data Mining
R Programming Language