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Building a basic Poisson model for soccer (step-by-step)

Step-by-step guide to building a Poisson model for soccer with insights on arbitrage betting for guaranteed profits.

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Building a basic Poisson model for soccer (step-by-step)

Building a basic Poisson model for soccer involves estimating the average goals scored by each team and using the Poisson distribution to predict the probability of different scorelines.

The Poisson model is widely used in soccer analytics because goals are discrete events that occur independently over time, making Poisson distribution an appropriate tool for forecasting match outcomes.

While traditional models require assumptions and guesswork, arbitrage betting leverages discrepancies in bookmaker odds to secure guaranteed profits, eliminating the need for predicting exact outcomes.

Understanding the Poisson Distribution

The Poisson distribution models the probability of a given number of events happening in a fixed interval, assuming these events occur independently and at a constant average rate. In soccer, goals scored by a team during a match fit this assumption well, allowing us to predict the likelihood of various scorelines.

  • Models count of independent events (goals) within fixed time (match duration)
  • Requires average goals per team as input
  • Outputs probabilities for 0,1,2,... goals

💡Basic Poisson Formula

The probability of scoring k goals is given by P(k) = (λ^k * e^-λ) / k!, where λ is the average goals expected.

For example, if a team averages 1.5 goals per match, the chance they score exactly 2 goals is P(2) = (1.5^2 * e^-1.5) / 2! ≈ 0.251

Estimating Average Goals for Each Team

To build the model, calculate each team's average goals scored and conceded from historical data. These averages serve as λ parameters for the Poisson distribution, representing expected goals in the upcoming match.

  • Collect recent match data for both teams
  • Calculate average goals scored and conceded
  • Adjust for home and away performance if possible

Home and Away Adjustments

Teams often perform differently at home versus away, so using separate averages for home goals scored and away goals conceded improves model accuracy.

  • Home team λ = average home goals scored × opponent's average away goals conceded
  • Away team λ = average away goals scored × opponent's average home goals conceded

💡Calculating Team Lambda Values

If Team A scores 1.8 goals at home on average and Team B concedes 1.1 goals away on average, Team A's expected goals (λ) = 1.8 × 1.1 = 1.98.

Similarly, Team B's λ is calculated using its average away goals and Team A's average home goals conceded.

Calculating Probabilities for Different Scorelines

Using the λ values for each team, apply the Poisson formula to find the probability of each team scoring 0,1,2,... goals. Then combine these to estimate probabilities for full match scorelines by multiplying individual team probabilities.

  • Compute probabilities for goals from 0 up to a reasonable max (e.g., 5 goals)
  • Multiply home and away goal probabilities for each combined score
  • Sum probabilities for desired outcomes like home win, draw, or away win

💡Example Score Probability Calculation

If Team A’s λ=1.5 and Team B’s λ=1.0, calculate P(Team A scores 2) and P(Team B scores 1), then multiply to get probability of 2-1 scoreline.

P(2-1) = P(Team A=2) × P(Team B=1) = ((1.5^2 * e^-1.5)/2!) × ((1.0^1 * e^-1.0)/1!) ≈ 0.251 × 0.368 = 0.092

Limitations and Possible Improvements

While the basic Poisson model is a powerful starting point, it assumes independence and equal scoring rates throughout the match. Real matches have dynamics like red cards or tactical changes that affect goal probabilities. Advanced models like bivariate Poisson or incorporating team form improve predictions.

  • Ignores correlation between team scores
  • Assumes constant scoring rate
  • Does not account for situational factors like injuries

How Arbitrage Betting Bypasses Prediction Risks

Because even the best models can't predict all uncertainties, arbitrage betting offers a superior alternative by guaranteeing profits regardless of match outcome, eliminating the risk associated with imperfect forecasts.

  • No need to predict exact scores
  • Profit from discrepancies in bookmaker odds
  • Reduces reliance on complex model assumptions

Automating Poisson Model Calculations

Manually calculating probabilities and evaluating different scorelines can be time-consuming and prone to error. Tools like ArbitUp help automate these calculations and identify profitable arbitrage opportunities by comparing odds across bookmakers.

  • Speeds up probability computations
  • Integrates model outputs with betting odds
  • Highlights arbitrage opportunities to maximize profit

💡Using ArbitUp for Calculations

ArbitUp automates the Poisson calculations and cross-checks bookmaker odds to find arbitrage bets that guarantee returns regardless of outcomes.

This eliminates manual errors and simplifies complex multi-outcome analyses.

Practical Step-by-Step Summary

To build your Poisson model, start by gathering recent match goal data, calculate team averages, adjust for home/away factors, apply the Poisson formula to estimate score probabilities, and finally consider arbitrage betting to secure risk-free profits from identified odds discrepancies.

  • Collect and preprocess historical goal data
  • Calculate team-specific average goals (λ)
  • Use Poisson formula for goal probabilities
  • Combine team probabilities for full scorelines
  • Leverage arbitrage betting to reduce risks

💡Summary Example

Calculate Team A’s λ=1.8 and Team B’s λ=1.2, use Poisson to get score probabilities, and then find arbitrage opportunities among bookmakers that offer favorable odds on these outcomes.

This structured approach improves prediction quality and maximizes betting profitability.

Common Mistakes to Avoid

  • ⚠️Using outdated or insufficient data leading to inaccurate average goals
  • ⚠️Ignoring home and away performance differences when estimating λ values
  • ⚠️Assuming goal scoring events are completely independent without real-world adjustments
  • ⚠️Overcomplicating the model without understanding basic Poisson assumptions
  • ⚠️Failing to cross-check probabilities with actual bookmaker odds before betting
  • ⚠️Neglecting to consider arbitrage betting as a risk-free alternative
  • ⚠️Manually calculating complex probabilities which increases chance of errors

The Power of Arbitrage Betting

Arbitrage betting eliminates guesswork by exploiting differences in bookmaker odds to guarantee profits regardless of match outcomes.

  • Removes uncertainty inherent in predictive models
  • Provides consistent, risk-free returns when executed properly
  • Simplifies betting decisions without needing perfect forecasts

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IMPORTANT DISCLAIMER

This content is for entertainment and educational purposes only and does not constitute financial advice. Sports betting involves substantial risk. Only bet with money you can afford to lose. See our Terms of Service for complete legal disclaimers.

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