The number of league points a team would be expected to earn based on their xG and xGA across a series of matches.
Expected Points (xPTS) calculates how many points a team would have been expected to accumulate based on the quality of chances they created and conceded — rather than actual results. For each match, the xG and xGA figures are fed into a Poisson model to generate a probability of home win, draw, and away win. Each probability is then multiplied by the corresponding points (3, 1, 0) to produce the expected points for that fixture.
A team with xPTS substantially above their actual points total has been unlucky — their underlying performance deserved more. A team with xPTS well below their actual points has been fortunate — they have been over-performing their underlying quality. Over a full season, actual points tend to converge toward xPTS.
Short-term form tables can be misleading due to variance in finishing and goalkeeping. xPTS-based form tables strip out this noise, showing which teams are performing well in terms of chance creation and prevention regardless of whether the ball is going in or not. A team on a bad run of results but with strong xPTS figures is a prime candidate for mean reversion.
This is particularly useful at the start of a season when sample sizes are small. By gameweek 6, actual points are heavily influenced by luck, but xPTS already reflects the true quality gap between teams reasonably well.
Bookmakers set match odds partly based on league position and recent results. Teams who are undervalued by bookmakers because of a poor actual points tally (despite strong xPTS) can offer value — the market is pricing a team as weaker than their underlying data suggests. Combining xPTS analysis with current odds is a core element of systematic value betting in football.
xPTS also helps identify "overachieving" teams — those whose actual points far exceed their xPTS total. These sides often show regression as the season progresses, making them poor betting propositions despite a strong league position.
xG (Expected Goals)
A metric that scores every shot by its probability of resulting in a goal, based on factors like shot location, angle, and assist type.
xGA (Expected Goals Against)
The expected goals conceded by a team — a measure of defensive quality based on the quality of chances allowed, not just goals shipped.
Poisson Distribution
The statistical model used to predict football match scorelines by treating goal-scoring as a random process based on each team's expected goals rate.
Value Betting
Betting at odds that are higher than the true probability of the outcome — finding bets where the bookmaker has underestimated the chances of an event.
Expected Value (EV)
The average outcome of a bet over a large number of repetitions — positive EV means the bet profits long-term; negative EV means it loses.
Football KPIs: The Key Performance Indicators That Actually Matter
Football KPIs (Key Performance Indicators) are the small set of metrics that consistently predict match outcomes. We list the 12 that matter, what each measures, and which are noise.
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FootyStats Premium is a paid football data subscription. We compare it to free alternatives (FBref, Sofascore, Fotmob) and to paid competitors (StatsBomb, Opta), and explain who should pay.
The Football Language Model: 2,000+ Metrics That Describe the Modern Game
Modern football is described by 2,000+ tracked metrics — from xG to PPDA to OBV. We explain the structure of football's metric vocabulary, how it grew, and how to navigate it.
Expected Points (xP): From xG to Points Per Match
Expected Points (xP) translates per-shot xG into a probabilistic points-per-match figure: how many points a team would have earned, on average, with the chances they created and conceded.
For informational and educational purposes only. Disclaimer
