Football Quantitative/Betting Market Analyst

Responsibilities:

• Analyse Asian Handicap, Over/Under and related football markets.
• Monitor opening prices, current prices, closing prices and significant market movements.
• Calculate and interpret implied probability, fair probability, fair odds, expected value and market edge.
• Identify situations where Moonlizard's model probability differs materially from the market price.
• Analyse team strength, expected goals (xG), shots, expected threat, possession, player availability, injuries, suspensions, lineups, tactical changes, home/away performance and other relevant variables.
• Distinguish genuine information-driven market movement from noise.
• Study sharp-market behaviour and compare prices across bookmakers/exchanges where appropriate.
• Conduct historical analysis and backtesting of football trading strategies.
• Evaluate model performance using metrics such as ROI, yield, expected value, closing-line value, hit rate, drawdown, calibration and sample size.
• Investigate winning and losing trades to determine whether the original decision was statistically justified.
• Help determine which variables should enter Moonlizard's football probability models.
• Produce clear pre-match research reports for matches selected by the Moonlizard engine.
• Maintain strict trading discipline and follow Moonlizard's risk-management rules.

Requirements:

The ideal candidate should have strong knowledge of:

Football:

• Tactical football analysis
• Team and player statistics
• Expected Goals (xG)
• Lineups and player availability
• Match context and team strength

Betting Markets:

•  Asian Handicap
• Asian Totals / Over-Under
• Decimal odds
• Implied probability
• Market movement
• Closing lines
• Expected value
• Price vs probability

Quantitative Skills:

• Probability and statistics
• Data analysis
• Backtesting
• Model evaluation
• Excel/Google Sheets

Personal Qualities:

We value:

•  Analytical thinking
• Intellectual honesty
• Discipline
• Attention to detail
• Ability to challenge assumptions
• Strong risk awareness
• Confidentiality
• Clear communication
• Willingness to learn
• Ability to work with developers and quantitative researchers