In the modern game, football analysis goes far beyond final scores. Traditional league tables show who won and lost, but they don’t always reflect who should have won based on the quality of chances created and conceded. This is where Expected Points (xP) come in—a metric designed to provide a more accurate picture of team performance over time.
In this article, we break down what xP is, how it’s calculated, and why it matters.
What Is Expected Points (xP)?
Expected Points (xP) is a statistical model that estimates how many points a team deserved to earn in a match based on the quality of chances, rather than the final result. It is derived from Expected Goals (xG) data and simulates thousands of match outcomes based on the xG values of both teams.
Where xG tells us how likely a specific shot is to result in a goal, xP translates that data into an estimate of match points—0 for a loss, 1 for a draw, and 3 for a win.
How Is xP Calculated?
The basic steps for calculating xP are:
1. Determine xG for both teams – Use shot data to calculate how many goals each team should have scored.
2. Simulate the match – Using probabilistic models, simulate the match thousands of times to see how often each team wins, draws, or loses.
3. Assign points based on probabilities – Multiply the probability of each outcome by the points it awards:
- Win probability × 3
- Draw probability × 1
- Loss probability × 0
4. Sum the points – The result is the Expected Points for each team.
For example, if simulations suggest:
- 50% chance of winning (×3 = 1.5 points)
- 30% chance of drawing (×1 = 0.3 points)
- 20% chance of losing (×0 = 0 points)
Then xP = 1.5 + 0.3 + 0 = 1.8 points.
Why Use Expected Points?
Expected Points help answer a fundamental question: Are a team’s results sustainable or misleading? xP can reveal overachieving or underperforming teams by comparing actual points (from the table) to expected points (from performance data).
Key Uses of xP:
- Performance benchmarking: See if a team’s place in the table matches their underlying performance.
- Regression prediction: Forecast which teams might improve or decline in future matches.
- Coaching insights: Identify whether tactical changes are leading to better quality chances.
- Scouting and recruitment: Support decision-making by evaluating whether a team or player is contributing effectively to performance.
xP vs xG: What’s the Difference?
While xG is a shot-level metric, xP works at the match level. Here’s a quick comparison:
| Metric | Focus | Unit of Measure | Use |
|---|---|---|---|
| xG | Individual shots | Expected goals per shot/team | Quality of chances |
| xP | Entire matches | Expected points per game | Fair outcome predictor |
A team might have a high xG but still lose due to poor finishing or defensive errors. xP accounts for both attacking and defensive xG to simulate likely match results.
Example: A Practical Case
Let’s say Team A played Team B. The final score was 1-0 to Team A.
But the xG was:
Using simulations, the model might estimate:
- Team A wins: 25% of simulations
- Draw: 25%
- Team B wins: 50%
Expected Points:
- Team A: (0.25 × 3) + (0.25 × 1) = 1.0 xP
- Team B: (0.50 × 3) + (0.25 × 1) = 1.75 xP
Even though Team A won the game, Team B performed better according to the model. Over time, such insights help assess true team quality.
Limitations of xP
No metric is perfect. While xP offers a more nuanced view of team performance, it depends heavily on the accuracy of the underlying xG model. Other limitations include:
- Does not factor in red cards, injuries, or tactical context.
- Not predictive on a match-to-match basis—better over longer timeframes.
- May not capture defensive or pressing effectiveness well.
That said, xP remains a powerful tool when used in context.
Why xP Matters for Coaches, Analysts, and Fans
Whether you’re a coach tracking performance, a scout seeking undervalued talent, or a fan interested in deeper analysis, xP adds a valuable dimension to your understanding of the game. It helps move the conversation beyond scorelines to performance reality.
A team consistently outperforming their xP might be riding their luck—or executing a brilliant game plan. A team underperforming their xP might be due for a turnaround. Knowing the difference can give you a competitive edge.
Final Thoughts
Expected Points (xP) bridges the gap between performance and results. While traditional league tables show what happened, xP tells us what should have happened based on quality data. Used wisely, xP offers deeper insight into team form, sustainability, and potential—making it a must-know stat in modern football analysis.