Monthly review
October 2026
1 October 2026 – 31 October 2026 · 1,796 words
Over October 2026 we had published a prediction before kick-off for 768 fixtures, across 24 match days and 27 competitions. We called 386 of them correctly, 50.3%.
Does our confidence mean anything
Taking every call in the period and sorting it by how confident we were: we said under 40% on 104 fixtures, averaging 38.4%, and were right 36.5% of the time; we said 40 to 50% on 277 fixtures, averaging 44.8%, and were right 43.3% of the time; we said 50 to 60% on 194 fixtures, averaging 54.5%, and were right 52.1% of the time; we said 60 to 70% on 112 fixtures, averaging 64.6%, and were right 59.8% of the time; we said 70% and above on 81 fixtures, averaging 77.1%, and were right 74.1% of the time. At the other end, 40 to 50% came out within 1.5 points of what we claimed, on 277 fixtures — there, the figure on the card means what it says.
The outcome we almost never call
Of 768 fixtures, 187 ended level — 24.3% of them. We called a draw in none of them. Not rarely: never, and that is worth explaining rather than apologising for. The three probabilities on each card come from simulating the two sides' scoring rates independently and counting how often each outcome appears. That method has a built-in ceiling on the draw: across this period the highest draw probability we published was 32.6%, and the nearest a draw ever came to leading its fixture was 9.1 points short. For the draw to top a card, two teams would have to be so exactly matched that neither win is likelier than the tie — which is rarer than a tie itself. So the headline call cannot name the outcome that happens a quarter of the time, and roughly a quarter of our misses are lost before kick-off. Independence is also the part we would change first. Real football scores are not independent at the low end: 0-0 and 1-1 happen more often than two separate rates predict, which is why the standard correction in the literature exists and why our draw numbers are likely a little low across the board. Until that is fixed, the probability we print for the draw is the figure worth reading on a tight fixture — not the call above it.
The fixtures we called close
On 104 fixtures no outcome reached 40% — the model divided them close to three ways and had, by its own account, little to say. 37 of those ended level, 35.6%, against 24.3% across the period as a whole. That difference matters more than it looks. It means the probabilities do rise when a draw is coming, even though the call printed above them never names one. The information is in the forecast; it is the headline that throws it away. If you read one number on a fixture we have split three ways, read the draw percentage rather than the team we listed first. We were right on 36.5% of them, which is roughly what guessing between two of three outcomes would give you, and we would rather publish a fixture like that flagged as undecidable than manufacture a lean.
Home, away, and which we get right
We backed the home side 578 times and the visiting side 190, so 75% of our calls went to the home team. They landed 50.0% of the time. The away calls landed 51.1%.
When we disagreed with the bookmakers
On 256 fixtures we had both our own number and a bookmaker price for the outcome we called. We were at least 10 points above the market on 45 of them — a real disagreement, several times larger than the margin built into the odds — and those calls came in 44.4% of the time. On the 100 fixtures where our number sat within 5 points of the price, we were right 52.0%. The two are close enough that the honest summary is that our disagreements with the market are neither vindicated nor punished over this period.
Against the bookmakers' favourite
The benchmark worth measuring against is not chance, it is the shortest price — anyone can read the odds for nothing. On the 256 fixtures where we had all three prices, backing the bookmakers' favourite every time would have been right 151 times, 59.0%. We were right 141 times, 55.1%. We named the same outcome as the market on 217 of them, 85%. So over this period the model came out 3.9 points BELOW simply following the favourite. That is the least comfortable number on this page and it is the one we would want a reader to see first. It does not make the probabilities worthless — a calibrated number tells you something a binary pick never does, and the market has no obligation to explain itself — but anyone here for the pick alone should know that the free version of it is currently doing better.
The goals we expected
Underneath the win probabilities sit two expected-goals figures, and they are the part of the model that is easiest to check and hardest to fudge. Across 768 fixtures we expected 1.60 goals for the home side and 1.18 for the away side, a total of 2.78. What actually happened was 1.61 and 1.36, a total of 2.98. The away figure is the one that drifts: we were under by 0.18 of a goal per match. It is small in absolute terms and it is systematic, which is the more interesting property — a bias that holds across hundreds of fixtures is correctable in a way that a wide spread is not. Rounding each expectation to a whole number reproduced the exact scoreline 87 times, 11.3%. We mention that as a curiosity rather than a claim: nobody should be predicting exact scorelines, and a model that appeared good at it would be a model that had been overfitted.
The high-scoring flag, tested
One model on each card does nothing but estimate how likely the home side is to score four goals or more. Over 768 fixtures that happened 73 times, 9.5%. The flag was raised on 122 of them, 16% of what we published. Where it was raised, the home side reached four goals 18.0% of the time; where it was not, 7.9%. So it is separating the two, by a factor of about 2.3. That is what the flag is asked to do, and worth stating plainly given it is also the part of the output we have most recently had to correct.
The calls we backed hardest
81 calls were published at 70% or above. 60 of them came in, 74.1%, against an average stated confidence of 77.1%. The most expensive of them was Bayern Munich to beat Viking FK at 85.3%, which finished 3–3 — a draw, which is the outcome we structurally cannot call.
The call we would point to
The call we are most pleased with is not the most confident one, it is the one furthest from the price. Rio Ave to beat C.D. Nacional in Primeira Liga: we published 71.7% where the odds implied about 45.5%, a gap of 26.2 points, and it finished 3–2. 20 calls in this period were that far above the market and came in. We list one rather than all of them because a page of the ones that worked, with the ones that did not left out, is how a track record gets quietly turned into advertising — the figure for how that whole group did is in the section above, and it is not flattering.
Where we were most wrong
Viking FK against Bayern Munich, in UEFA Champions League, finished 3–3. We had published Bayern Munich to beat Viking FK at 85.3%, the largest confidence we placed on anything that did not happen in this period. It is worth noting what our five worst misses have in common: 4 of them ended level. The model's most confident errors are not upsets, they are draws. It stays on the record. A site that reports only its hits is not reporting a record, it is reporting a selection.
The best and worst week
Split the period by week and the spread is wide: our best week was the week of 12 October, 136 of 248 (54.8%); the worst was the week of 19 October, 92 of 214 (43.0%). Across 4 comparable weeks the range is 43.0% to 54.8%.
Week by week
In order, the weeks ran: week of 28 September, 45 of 89 (50.6%); week of 5 October, 113 of 217 (52.1%); week of 12 October, 136 of 248 (54.8%); week of 19 October, 92 of 214 (43.0%). The spread between the best and worst week is 11.8 points, with no direction to it. That is what a stable model looks like at this volume: the weekly figure moves around, the monthly one much less.
Against last month
Against the month before: 817 settled fixtures then at 45.9%, 768 now at 50.3%, a move of +4.4 points. More useful than the headline: in the 50 to 70% range, where most of our calls sit, we were 5.1 points below our stated confidence last month and 3.3 points below it this one.
Where we published, and how it went
We published across 27 competitions. The five busiest were League Two (56), League One (52), Championship (49), Int: UEFA Nations League (44), Liga Profesional Argentina (41). Among the 22 with at least 20 settled fixtures, we read UEFA Champions League best — 66.7% across 30 matches — and Serie B worst, at 28.6% across 28. We would not yet call that a real difference between leagues. At these sample sizes the gap between the best and worst competition is about what you would get by splitting one league in half at random, and the leagues we cover least are exactly the ones where the rating model has the least history to work from. It is worth watching across several months; it is not worth acting on after one.
How to read all this
One month of 768 fixtures settles very little on its own. A percentage point either way on a sample this size is noise, and we would rather say so than dress it up. What these reviews are for is the shape that emerges when several of them sit side by side: whether a stated 65% keeps landing near 65%, whether the gap between our number and the market's keeps costing us, whether a competition we read badly this month is still being read badly in three. Those are answerable, and they are answerable in public, which is the only reason to publish the bad figures alongside the good ones.
Every figure here comes from predictions published before the match day — never from a re-run after the results were known. Results come from public fixture feeds. Every period we have reviewed → How the model is measured →