How to Calculate the Probability of a Football Match Outcome — Step by Step
Why Calculate Probabilities Yourself
Most bettors decide on intuition, media opinion, or by following the crowd. The professional approach starts with a single question: "What is the true probability of this event?" Only with that answer can you tell whether the bookmaker is offering a value bet — a positive-expectation wager.
This guide walks you through the whole process, from gathering data to a finished recommendation. It's the exact algorithm the BETSKOP system runs every day across Europe's top leagues.
Step 1: Gather Data — the Foundation
You need specific figures per team: average goals scored (overall and home/away separately), average goals conceded (overall and home/away), form over the last 5-10 matches, head-to-head history, and the injury and suspension status of key players.
Data sources: a professional sports API (such as API-Football), Transfermarkt, WhoScored, FBref. BETSKOP gathers everything automatically via API each day, removing human error. To do it by hand, FBref alone is enough — all the stats you need are there for free.
Critically: use the current season only, and separate home and away figures. A team that scores 2.5 at home may score only 0.8 away — a huge gap. More on home advantage and its effect on the maths.
Step 2: League Average — Your Baseline
Average goals per match in the league is your baseline. For each team you compute "attacking strength" and "defensive weakness" relative to it. In the Premier League the average is about 2.7 goals per match (≈1.35 per team). In La Liga — 2.5 (1.25). In the Bundesliga — 3.0 (1.50). In Serie A — 2.5 (1.25). In Ligue 1 — 2.5 (1.25). In the Russian Premier League — 2.3 (1.15).
Step 3: Compute Lambda — Expected Goals
A detailed breakdown of expected goals is in our Poisson model article. Briefly: home xG = average home goals × (away goals conceded by the opponent / league average); away xG follows the same pattern.
Example: Liverpool vs Everton. Liverpool scores 2.1 at home; Everton concedes 1.8 away. Premier League average: 1.35. Liverpool xG = 2.1 × (1.8 / 1.35) = 2.80. Everton scores 0.7 away; Liverpool concedes 0.8 at home. Everton xG = 0.7 × (0.8 / 1.35) = 0.41.
Already the picture is clear: expected total = 2.80 + 0.41 = 3.21 goals. Liverpool at 2.80 should dominate; Everton at 0.41 is unlikely to score.
Step 4: Build the Probability Matrix
For each possible goal count we compute the exact probability. We calculate P(0) through P(5) for both teams, multiply, and get the full matrix.
For Liverpool: P(0)=6.1%, P(1)=17.0%, P(2)=23.8%, P(3)=22.2%. For Everton: P(0)=66.4%, P(1)=27.2%, P(2)=5.6%. The most likely scores: 2-0 (15.8%), 3-0 (14.7%).
Step 5: Sum for Each Market
Liverpool win — the sum of all cells where home goals are greater: about 82%. Draw — the diagonal: 11%. Everton win: 7%. Under 2.5 — cells totalling 0-2 goals: about 36%. Over 2.5: 64%. BTTS Yes: 28%. BTTS No: 72%.
Step 6: Compare With Odds — Find the Edge
The book offers 1.25 on a Liverpool win (implied 80%). Our calculation: 82%. Edge = (0.82 × 1.25) - 1 = +2.5%. Below our 5% threshold — skip.
The book offers 2.60 on Under 2.5 (implied 38.5%). Our calculation: 36%. Edge = (0.36 × 2.60) - 1 = -6.4%. Negative — no bet. The book offers 2.80 on BTTS No (implied 35.7%). Our calculation: 72%. Edge = (0.72 × 2.80) - 1 = +101.6%. A huge edge — re-check the calculation… then stake the optimal amount via the Kelly Criterion.
Step 7: Automation — Why Do It by Hand
BETSKOP runs this whole process automatically each day for every match in the top leagues. Of 10-30 daily fixtures, usually 1-5 clear the 5% edge threshold and are published as recommendations. Follow the Telegram channel for ready signals with the full calculation. All results are open for verification.