Hi everyone,
I’m looking for an experienced AI/ML developer or sports betting quantitative analyst to build a custom sports betting prediction model.
What I’m looking for
I want to develop an AI-driven system that can analyze historical and current sports data and generate probability-based predictions and betting recommendations.
The model should ideally be able to:
Analyze large amounts of historical match data
Calculate win/draw/loss probabilities
Analyze player/team performance and statistics
Consider injuries, lineups, form, home/away performance, etc.
Compare model probabilities against available bookmaker odds
Identify potential +EV (positive expected value) bets
Track closing-line movement and odds history
Provide confidence/probability percentages
Track predictions and actual results
Continuously evaluate and improve model performance
Have proper backtesting to determine whether the strategy actually works
Sports
I’m open to different sports, but I’m particularly interested in:
⚽ Football
🏀 Basketball
🥊 Boxing
🎾 Tennis
🏈 American Football
I’m also interested in hearing your recommendation about which sport would be the best starting point from a modeling perspective.
Technical requirements
I would prefer someone experienced with:
Python
Machine Learning / Deep Learning
Pandas / NumPy
Scikit-learn
XGBoost / LightGBM
Statistical modeling
APIs and sports data
Odds data
Database design
Backtesting
EV/value betting concepts
I’m not looking for a simple tipster or prediction script. I want a properly designed quantitative model with measurable historical performance.
Important
I want the model to be tested using out-of-sample data / walk-forward backtesting and realistic historical odds, including consideration of bookmaker margin and closing prices.
I’m open to discussing the architecture, data sources, model types, and methodology with someone who has relevant experience.
Budget: Negotiable depending on experience and scope.
If you’re interested, please DM me with:
Your experience with sports betting models
Examples of similar projects you have built
Sports you have modeled
Your preferred technology/data stack
Estimated development time
Your expected budget
Whether you can provide a demo or previous results
Serious developers/data scientists only. I’m looking for someone interested in building a long-term, scalable project, not a quick prediction script.
I’m looking for an experienced AI/ML developer or sports betting quantitative analyst to build a custom sports betting prediction model.
What I’m looking for
I want to develop an AI-driven system that can analyze historical and current sports data and generate probability-based predictions and betting recommendations.
The model should ideally be able to:
Analyze large amounts of historical match data
Calculate win/draw/loss probabilities
Analyze player/team performance and statistics
Consider injuries, lineups, form, home/away performance, etc.
Compare model probabilities against available bookmaker odds
Identify potential +EV (positive expected value) bets
Track closing-line movement and odds history
Provide confidence/probability percentages
Track predictions and actual results
Continuously evaluate and improve model performance
Have proper backtesting to determine whether the strategy actually works
Sports
I’m open to different sports, but I’m particularly interested in:
⚽ Football
🏀 Basketball
🥊 Boxing
🎾 Tennis
🏈 American Football
I’m also interested in hearing your recommendation about which sport would be the best starting point from a modeling perspective.
Technical requirements
I would prefer someone experienced with:
Python
Machine Learning / Deep Learning
Pandas / NumPy
Scikit-learn
XGBoost / LightGBM
Statistical modeling
APIs and sports data
Odds data
Database design
Backtesting
EV/value betting concepts
I’m not looking for a simple tipster or prediction script. I want a properly designed quantitative model with measurable historical performance.
Important
I want the model to be tested using out-of-sample data / walk-forward backtesting and realistic historical odds, including consideration of bookmaker margin and closing prices.
I’m open to discussing the architecture, data sources, model types, and methodology with someone who has relevant experience.
Budget: Negotiable depending on experience and scope.
If you’re interested, please DM me with:
Your experience with sports betting models
Examples of similar projects you have built
Sports you have modeled
Your preferred technology/data stack
Estimated development time
Your expected budget
Whether you can provide a demo or previous results
Serious developers/data scientists only. I’m looking for someone interested in building a long-term, scalable project, not a quick prediction script.