NFL Prediction Model Development
Budget: $750 – $1,500 AUD
I'm seeking a skilled data scientist or machine learning engineer to create a predictive model using NFL game and player data.
Essential Requirements:
- Proficiency in Python, particularly with libraries such as Pandas, scikit-learn, and XGBoost.
- Expertise in building classification and regression models.
- Experience with structured sports datasets, especially NFL data.
- Ability to produce clear, organized outputs in CSV or JSON formats.
- Development of clean, modular, and well-documented code.
The model should:
- Generate predictions on game outcomes, player performances, and season statistics using historical NFL data.
- Include confidence levels with all outputs.
- Maintain accuracy and reliability, with ease of updates on a weekly basis.
If you have a background in sports data analysis or similar prediction models, that would be highly advantageous. Please provide:
- Examples of previous work
- Estimated timeline for completion
- Any questions you may have
Essential Requirements:
- Proficiency in Python, particularly with libraries such as Pandas, scikit-learn, and XGBoost.
- Expertise in building classification and regression models.
- Experience with structured sports datasets, especially NFL data.
- Ability to produce clear, organized outputs in CSV or JSON formats.
- Development of clean, modular, and well-documented code.
The model should:
- Generate predictions on game outcomes, player performances, and season statistics using historical NFL data.
- Include confidence levels with all outputs.
- Maintain accuracy and reliability, with ease of updates on a weekly basis.
If you have a background in sports data analysis or similar prediction models, that would be highly advantageous. Please provide:
- Examples of previous work
- Estimated timeline for completion
- Any questions you may have
Related categories:
Python
Machine Learning (ML)
Data Mining
Data Science
Data Analysis
Data Modeling
Predictive Analytics
Pandas