Expected Goals (xG) Calculator & Converter

In modern football betting, Expected Goals (xG) is the gold standard metric. It tells you how many goals a team should have scored based on the quality of chances created, stripping away the noise of luck and variance.

However, knowing that “Liverpool had 2.45 xG” is useless if you cannot translate that number into betting value. That is where our xG Calculator comes in. It acts as a bridge between data and profit, converting raw xG numbers into Implied Probabilities and Fair Odds using the Poisson Distribution model.

Expected Goals (xG) Calculator

Convert xG Stats to Fair Odds & Probabilities
Dominant Home
Tight Match
Strong Away
Goal Fest
Home Win
--%
@--
Draw
--%
@--
Away Win
--%
@--
Most Likely Scores (Heatmap)
Grid shows scores from 0-0 (top-left) to 5-5 (bottom-right). Color intensity = Probability.

How to Use the xG Odds Calculator

This tool is designed to help you price up a match like a professional bookmaker. Follow these steps to find value:

  1. Find the xG Data: Get the projected xG for the upcoming match. You can find this on sites like FBref, Understat, or by using an average of the team’s last 5 matches.
  2. Input the Numbers: Enter the Home xG and Away xG into the calculator.
  3. Analyze the “Fair Odds”: The tool will display the true odds for the Home Win, Draw, and Away Win.
    • Example: If the calculator says the Fair Odds for a Home Win are 1.80, but the bookmaker is offering 2.10, you have found a “Value Bet” (a positive Expected Value wager).
  4. Check the Heatmap: Look at the “Correct Score Matrix” to see the most likely scorelines. This is crucial for precise betting.

Related Tools: If the xG data suggests a tight game with a high chance of a draw, consider using our Draw No Bet Calculator to reduce risk. If the data predicts a goal-fest, verify the value with our Over/Under Calculator.

Real-World Examples: xG in Action

How does converting xG to probability help you beat the bookie? Let’s look at two common scenarios.

Example 1: The “False Favorite”

Manchester United are playing Crystal Palace. The bookies price United at 1.50 (66% implied chance) purely on reputation.

  • The Data: Recent performance shows United averaging 1.20 xG and Palace averaging 1.10 xG.
  • The Calculation: You input these numbers. The calculator reveals the true probability of a United win is only 42% (Fair Odds 2.38).
  • The Verdict: The bookmaker’s price of 1.50 is terrible value. The calculator saves you from making a losing bet. You might instead look at the Double Chance Calculator to back Palace.

Example 2: The Correct Score Hunt

You want to place a high-odds bet on the Correct Score market for a match between Arsenal and Brighton.

  • The Data: Arsenal xG: 2.15 | Brighton xG: 0.85.
  • The Heatmap: The calculator’s heatmap highlights 2-0 and 2-1 as the most intensely green (highest probability) cells.
  • The Strategy: Instead of guessing, you split your stake between these two specific scorelines based on the math.

Frequently Asked Questions (FAQ)

What mathematical model does this calculator use?

This calculator uses the Double Poisson Distribution. It calculates the probability of every possible scoreline (from 0-0 to 9-9) based on the input xG, and then sums these probabilities to derive the percentage chance for a Home Win, Draw, or Away Win.

Where can I find reliable xG data?

Excellent free sources include FBref (StatsBomb data), Understat, and Infogol. For the best results, try to use “Expected Goals For” (xG) and “Expected Goals Against” (xGA) to create a weighted average for the two teams playing.

Why are the calculator odds different from the bookmaker’s odds?

Bookmaker odds include a “margin” (or juice)—usually 5-8%—which ensures they make a profit. Our calculator shows the Fair Odds (100% market) with zero margin. If our Fair Odds are significantly lower than the Bookmaker’s odds, you have found value.

Can I use this for other sports besides football?

This specific calculator is tuned for Football (Soccer) because goal scoring is a rare event that fits the Poisson distribution perfectly. For high-scoring sports like Basketball or Rugby, different statistical models are required.

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