About OriginalXG
Data-driven football predictions with full transparency.
What We Do
OriginalXG generates football match predictions using Expected Goals (xG) data and statistical probability modelling. We cover the top 5 European leagues: Premier League, La Liga, Bundesliga, Serie A, and Ligue 1.
Unlike tipster sites that rely on gut feeling, recent form, or head-to-head records, our predictions are built entirely on shot quality data. xG measures the quality of chances a team creates and concedes — not just the scoreline — which makes it a far more reliable predictor of future performance.
How the Model Works
- Data collection: We track per-shot xG data for every match across all 5 leagues, calculating rolling home and away averages for each team.
- Expected goals calculation: For each upcoming match, we combine the home team's attacking xG with the away team's defensive xG (and vice versa) to estimate expected goals for each side.
- Probability modelling: These expected goals feed into a statistical model that calculates the probability of every possible scoreline — from 0-0 to 5-5.
- Outcome probabilities: We sum scoreline probabilities to get overall home win, draw, and away win percentages.
- Value detection: We compare our model's probabilities to bookmaker odds. When our model significantly disagrees with the market, we flag it as a value opportunity.
Our Data Sources
- xG data: Understat.com — per-shot Expected Goals data for every match since 2014
- Odds data: The Odds API — real-time odds from 15+ UK bookmakers
- Lineup data: Football-Data.org — confirmed team lineups for final predictions
Prediction Schedule
Each gameweek, we publish predictions in stages — getting more accurate as kickoff approaches:
| Version | When | What's included |
|---|---|---|
| Early Predictions | Monday | xG-based predictions published for all upcoming matches across 5 leagues. Our top picks are highlighted — the ones where our model is most confident. |
| Updated Predictions | Friday | Adjusted for injuries, suspensions, and midweek European fixtures. Odds comparison added to highlight value opportunities. |
| Final Predictions | Pre-kickoff (Saturday) | Updated once confirmed lineups are announced. This is the version we track for accuracy. |
| Results Review | Monday | Full gameweek review: how we did, what surprised us, updated accuracy stats. Delivered to subscribers via email. |
Accuracy & Transparency
Every prediction is logged and compared against actual results. Our accuracy dashboard updates automatically after every gameweek — no cherry-picking, no hiding bad weeks.
We also compare our accuracy against Chris Sutton's BBC Sport predictions and the bookmaker favourite. We believe in proving our track record, not just claiming it.
As a concrete illustration: backtested across 11 seasons (2014/15–2024/25) and 18,316 matches with real bookmaker odds, our Recommended Picks (66-72% model confidence) delivered a 74% win rate and +8% ROI, profitable in 10 out of 11 seasons. Full breakdown on the Results page.
What We're Not
- We are not a tipping service. We don't tell you what to bet on.
- We are not affiliated with any bookmaker. We don't earn commission from gambling.
- We show you what the data says and let you draw your own conclusions.
⚠️ OriginalXG is a statistical analysis site. Any references to bookmaker odds or value bets are mathematical observations, not gambling recommendations. If you or someone you know has a gambling problem, please visit BeGambleAware.org.
FAQ
Why xG instead of just looking at results?
Results include a lot of noise — lucky deflections, missed penalties, goalkeeper heroics. xG strips out the randomness and measures the underlying quality of chances. A team that creates 2.5 xG per game but only scores 1.5 goals is due for a correction upward. xG helps us see that before the results catch up.
How accurate is the model?
No model predicts football perfectly — the sport is beautifully unpredictable. Our target is >45% accuracy on match outcomes (random guessing would get you ~33%) and >12% on exact scores (random is ~3%). Check our live accuracy stats to see how we're doing.
What does "value bet" mean?
A value bet is where our model assigns a higher probability to an outcome than the bookmaker's odds imply. For example, if our model says Home Win has a 50% chance but the bookmaker's odds imply only 40%, that's a +10% edge. It doesn't mean it will happen — it means the odds are more generous than our data suggests they should be.
Do you cover cup matches?
Currently we focus on league matches only, where we have the richest xG data for consistent modelling. Cup matches with teams from different divisions are harder to model reliably.