Calibration & track record
We answer with calibration: when the model gives an outcome a 60% chance, that kind of call should come true about 60% of the time. Here is how close it gets, and how it is measured.
Football prediction accuracy at TACTIX is measured as calibration, and across 6M+ graded predictions (all markets, player markets included) the model sits within ±0.2% of how often those outcomes actually happened, counting each prediction graded since the public record began. Winners and losers both count, in every market the model prices, and the figure is recomputed from the database on a schedule rather than typed in.
Each circle is one 10-point probability bucket: how likely the model said its outcomes were, against how often they actually happened. A perfectly calibrated model sits on the dashed line. Winners and losers are both in every bucket, and the table gives the number of predictions behind each point.
Source: TACTIX settled predictions (all markets) · as of 6 Nov 2026 · n = 6,144,644 settled predictions
| Model says | Happened | Settled (n) | 95% interval |
|---|---|---|---|
| 4% | 4% | 1,342,689 | 4.4–4.4% |
| 15% | 15% | 645,205 | 14.5–14.7% |
| 25% | 25% | 507,465 | 24.8–25% |
| 35% | 36% | 450,598 | 35.4–35.6% |
| 45% | 45% | 468,719 | 45.2–45.4% |
| 55% | 55% | 433,471 | 54.6–54.8% |
| 65% | 65% | 412,915 | 64.4–64.6% |
| 75% | 75% | 442,476 | 75–75.2% |
| 85% | 86% | 526,336 | 85.4–85.6% |
| 96% | 95% | 914,770 | 95.4–95.4% |
| Probability bucket | Average predicted | Happened | Predictions |
|---|---|---|---|
| 0–10% | 4.3% | 4.4% | 1,342,689 |
| 10–20% | 14.6% | 14.6% | 645,205 |
| 20–30% | 24.9% | 24.9% | 507,465 |
| 30–40% | 35.1% | 35.5% | 450,598 |
| 40–50% | 45.0% | 45.3% | 468,719 |
| 50–60% | 54.9% | 54.7% | 433,471 |
| 60–70% | 64.9% | 64.5% | 412,915 |
| 70–80% | 75.0% | 75.1% | 442,476 |
| 80–90% | 85.4% | 85.5% | 526,336 |
| 90–100% | 95.6% | 95.4% | 914,770 |
Each observation is one appearance by one player for one market line. Appearances are taken oldest first and counted as in the hit meters (last eight played matches, friendlies left out, appearances of 15+ minutes); a match where the statistic was not recorded for the player’s team is left out, and a match the player did not appear in is not counted at all. For every appearance with at least eight counted appearances before it, we note how many of those eight cleared the line (zero to eight) and whether this one did. Intervals are Wilson 95% intervals. A row with fewer than 200 observations shows its count only.
| Hits in the last eight | Observations | Hit the line next time | 95% interval |
|---|---|---|---|
| 0 of 8 | 526,876 | 32,499 (6.2%) | 6.1% to 6.2% |
| 1 of 8 | 296,825 | 41,689 (14.0%) | 13.9% to 14.2% |
| 2 of 8 | 186,775 | 41,717 (22.3%) | 22.2% to 22.5% |
| 3 of 8 | 120,865 | 36,949 (30.6%) | 30.3% to 30.8% |
| 4 of 8 | 77,844 | 29,956 (38.5%) | 38.1% to 38.8% |
| 5 of 8 | 46,721 | 21,573 (46.2%) | 45.7% to 46.6% |
| 6 of 8 | 24,656 | 13,145 (53.3%) | 52.7% to 53.9% |
| 7 of 8 | 10,853 | 6,729 (62.0%) | 61.1% to 62.9% |
| 8 of 8 | 3,093 | 2,194 (70.9%) | 69.3% to 72.5% |
| All observations | 1,294,508 | 226,451 (17.5%) | 17.4% to 17.6% |
| Hits in the last eight | Observations | Hit the line next time | 95% interval |
|---|---|---|---|
| 0 of 8 | 324,188 | 28,699 (8.9%) | 8.8% to 9.0% |
| 1 of 8 | 275,483 | 48,440 (17.6%) | 17.4% to 17.7% |
| 2 of 8 | 224,948 | 55,276 (24.6%) | 24.4% to 24.8% |
| 3 of 8 | 167,126 | 55,298 (33.1%) | 32.9% to 33.3% |
| 4 of 8 | 119,064 | 48,979 (41.1%) | 40.9% to 41.4% |
| 5 of 8 | 78,677 | 37,876 (48.1%) | 47.8% to 48.5% |
| 6 of 8 | 42,967 | 23,478 (54.6%) | 54.2% to 55.1% |
| 7 of 8 | 17,856 | 10,877 (60.9%) | 60.2% to 61.6% |
| 8 of 8 | 4,237 | 2,836 (66.9%) | 65.5% to 68.3% |
| All observations | 1,254,546 | 311,759 (24.9%) | 24.8% to 24.9% |
| Hits in the last eight | Observations | Hit the line next time | 95% interval |
|---|---|---|---|
| 0 of 8 | 737,159 | 35,897 (4.9%) | 4.8% to 4.9% |
| 1 of 8 | 322,951 | 33,244 (10.3%) | 10.2% to 10.4% |
| 2 of 8 | 140,718 | 22,814 (16.2%) | 16.0% to 16.4% |
| 3 of 8 | 60,022 | 13,577 (22.6%) | 22.3% to 23.0% |
| 4 of 8 | 24,570 | 6,922 (28.2%) | 27.6% to 28.7% |
| 5 of 8 | 8,655 | 2,880 (33.3%) | 32.3% to 34.3% |
| 6 of 8 | 2,317 | 874 (37.7%) | 35.8% to 39.7% |
| 7 of 8 | 486 | 237 (48.8%) | 44.4% to 53.2% |
| 8 of 8 | 85 | count only | – |
| All observations | 1,296,963 | 116,496 (9.0%) | 8.9% to 9.0% |
| Hits in the last eight | Observations | Hit the line next time | 95% interval |
|---|---|---|---|
| 0 of 8 | 805,754 | 39,444 (4.9%) | 4.9% to 4.9% |
| 1 of 8 | 343,318 | 27,859 (8.1%) | 8.0% to 8.2% |
| 2 of 8 | 111,104 | 12,323 (11.1%) | 10.9% to 11.3% |
| 3 of 8 | 29,031 | 4,102 (14.1%) | 13.7% to 14.5% |
| 4 of 8 | 6,409 | 1,117 (17.4%) | 16.5% to 18.4% |
| 5 of 8 | 1,140 | 256 (22.5%) | 20.1% to 25.0% |
| 6 of 8 | 175 | count only | – |
| 7 of 8 | 32 | count only | – |
| 8 of 8 | 0 | count only | – |
| All observations | 1,296,963 | 85,162 (6.6%) | 6.5% to 6.6% |
| Hits in the last eight | Observations | Hit the line next time | 95% interval |
|---|---|---|---|
| 0 of 8 | 515,645 | 39,165 (7.6%) | 7.5% to 7.7% |
| 1 of 8 | 364,269 | 49,412 (13.6%) | 13.5% to 13.7% |
| 2 of 8 | 216,435 | 42,064 (19.4%) | 19.3% to 19.6% |
| 3 of 8 | 115,010 | 29,364 (25.5%) | 25.3% to 25.8% |
| 4 of 8 | 54,176 | 16,818 (31.0%) | 30.7% to 31.4% |
| 5 of 8 | 22,245 | 8,161 (36.7%) | 36.1% to 37.3% |
| 6 of 8 | 7,140 | 2,980 (41.7%) | 40.6% to 42.9% |
| 7 of 8 | 1,759 | 897 (51.0%) | 48.7% to 53.3% |
| 8 of 8 | 284 | 165 (58.1%) | 52.3% to 63.7% |
| All observations | 1,296,963 | 189,026 (14.6%) | 14.5% to 14.6% |
| Hits in the last eight | Observations | Hit the line next time | 95% interval |
|---|---|---|---|
| 0 of 8 | 310,708 | 31,494 (10.1%) | 10.0% to 10.2% |
| 1 of 8 | 312,211 | 60,754 (19.5%) | 19.3% to 19.6% |
| 2 of 8 | 283,535 | 68,935 (24.3%) | 24.2% to 24.5% |
| 3 of 8 | 198,197 | 57,532 (29.0%) | 28.8% to 29.2% |
| 4 of 8 | 112,866 | 38,619 (34.2%) | 33.9% to 34.5% |
| 5 of 8 | 52,420 | 20,528 (39.2%) | 38.7% to 39.6% |
| 6 of 8 | 19,412 | 8,663 (44.6%) | 43.9% to 45.3% |
| 7 of 8 | 5,207 | 2,578 (49.5%) | 48.2% to 50.9% |
| 8 of 8 | 828 | 479 (57.9%) | 54.5% to 61.2% |
| All observations | 1,295,384 | 289,582 (22.4%) | 22.3% to 22.4% |
| Hits in the last eight | Observations | Hit the line next time | 95% interval |
|---|---|---|---|
| 0 of 8 | 50,846 | 9,541 (18.8%) | 18.4% to 19.1% |
| 1 of 8 | 103,614 | 28,117 (27.1%) | 26.9% to 27.4% |
| 2 of 8 | 153,059 | 55,247 (36.1%) | 35.9% to 36.3% |
| 3 of 8 | 198,804 | 87,673 (44.1%) | 43.9% to 44.3% |
| 4 of 8 | 224,458 | 114,769 (51.1%) | 50.9% to 51.3% |
| 5 of 8 | 219,963 | 126,216 (57.4%) | 57.2% to 57.6% |
| 6 of 8 | 180,234 | 115,353 (64.0%) | 63.8% to 64.2% |
| 7 of 8 | 116,970 | 82,203 (70.3%) | 70.0% to 70.5% |
| 8 of 8 | 47,403 | 36,517 (77.0%) | 76.7% to 77.4% |
| All observations | 1,295,351 | 655,636 (50.6%) | 50.5% to 50.7% |
| Hits in the last eight | Observations | Hit the line next time | 95% interval |
|---|---|---|---|
| 0 of 8 | 246,449 | 20,667 (8.4%) | 8.3% to 8.5% |
| 1 of 8 | 206,783 | 45,213 (21.9%) | 21.7% to 22.0% |
| 2 of 8 | 222,592 | 66,095 (29.7%) | 29.5% to 29.9% |
| 3 of 8 | 208,827 | 76,443 (36.6%) | 36.4% to 36.8% |
| 4 of 8 | 168,784 | 71,708 (42.5%) | 42.3% to 42.7% |
| 5 of 8 | 114,407 | 55,147 (48.2%) | 47.9% to 48.5% |
| 6 of 8 | 61,650 | 33,148 (53.8%) | 53.4% to 54.2% |
| 7 of 8 | 25,085 | 15,223 (60.7%) | 60.1% to 61.3% |
| 8 of 8 | 5,627 | 3,626 (64.4%) | 63.2% to 65.7% |
| All observations | 1,260,204 | 387,270 (30.7%) | 30.7% to 30.8% |
| Hits in the last eight | Observations | Hit the line next time | 95% interval |
|---|---|---|---|
| 0 of 8 | 447,345 | 47,246 (10.6%) | 10.5% to 10.7% |
| 1 of 8 | 443,859 | 61,316 (13.8%) | 13.7% to 13.9% |
| 2 of 8 | 259,338 | 43,286 (16.7%) | 16.6% to 16.8% |
| 3 of 8 | 107,169 | 20,313 (19.0%) | 18.7% to 19.2% |
| 4 of 8 | 31,508 | 6,616 (21.0%) | 20.6% to 21.5% |
| 5 of 8 | 6,677 | 1,518 (22.7%) | 21.8% to 23.8% |
| 6 of 8 | 964 | 237 (24.6%) | 22.0% to 27.4% |
| 7 of 8 | 97 | count only | – |
| 8 of 8 | 6 | count only | – |
| All observations | 1,296,963 | 180,563 (13.9%) | 13.9% to 14.0% |
| Hits in the last eight | Observations | Hit the line next time | 95% interval |
|---|---|---|---|
| 0 of 8 | 435,692 | 21,291 (4.9%) | 4.8% to 5.0% |
| 1 of 8 | 188,952 | 22,276 (11.8%) | 11.6% to 11.9% |
| 2 of 8 | 98,118 | 20,381 (20.8%) | 20.5% to 21.0% |
| 3 of 8 | 58,697 | 17,742 (30.2%) | 29.9% to 30.6% |
| 4 of 8 | 36,687 | 14,024 (38.2%) | 37.7% to 38.7% |
| 5 of 8 | 21,382 | 9,659 (45.2%) | 44.5% to 45.8% |
| 6 of 8 | 10,339 | 5,296 (51.2%) | 50.3% to 52.2% |
| 7 of 8 | 3,683 | 2,050 (55.7%) | 54.1% to 57.3% |
| 8 of 8 | 744 | 453 (60.9%) | 57.3% to 64.3% |
| All observations | 854,294 | 113,172 (13.3%) | 13.2% to 13.3% |
| Hits in the last eight | Observations | Hit the line next time | 95% interval |
|---|---|---|---|
| 0 of 8 | 568 | 132 (23.2%) | 20.0% to 26.9% |
| 1 of 8 | 2,020 | 962 (47.6%) | 45.5% to 49.8% |
| 2 of 8 | 6,815 | 3,478 (51.0%) | 49.9% to 52.2% |
| 3 of 8 | 14,546 | 7,598 (52.2%) | 51.4% to 53.1% |
| 4 of 8 | 20,977 | 11,485 (54.8%) | 54.1% to 55.4% |
| 5 of 8 | 21,279 | 12,180 (57.2%) | 56.6% to 57.9% |
| 6 of 8 | 14,899 | 8,800 (59.1%) | 58.3% to 59.9% |
| 7 of 8 | 6,627 | 4,078 (61.5%) | 60.4% to 62.7% |
| 8 of 8 | 1,447 | 927 (64.1%) | 61.6% to 66.5% |
| All observations | 89,178 | 49,640 (55.7%) | 55.3% to 56.0% |
Counts of past appearances. Not a forecast. As of 6 November 2026, from 12,531,317 observations. The cells as CSV · the same figures as JSON. 18+ | BeGambleAware.org
Every month we publish the same measurement for that month alone, good months and bad. In October 2026: 2,158,088 settled predictions, with stated and observed rates differing by 0.4 percentage points on average.
In October 2026 the bookmakers’ closing prices were more accurate than the model (log-loss difference +0.022, 95% interval +0.017 to +0.028 across 31 match days). The comparison uses the 11,158 of 38,471 predictions that had a closing price captured within 6 hours of kick-off.
Read the October 2026 scorecard · the latest scorecard, always
A single "accuracy %" mostly reflects how predictable a league or market is, and it is easy to flatter by picking easy markets. Calibration asks whether the stated probabilities are honest: when the model says 70%, does that outcome happen about seven times in ten? That is the property that matters when you use a probability to make a decision, so it is the number we publish, next to the count of predictions behind it.
Our calibration and track record update from settled results in public, losing predictions included. You can watch it on the live scoreboard. We never hide bad weeks and we never sell "guaranteed" tips — a prediction is a probability, not a certainty, and no model reliably beats the bookmakers' margin.
Every pick carries a model probability. We bucket them into three fixed-threshold tiers and report each one’s real win rate. The tiers are fixed probability thresholds, so a “Gold” pick means the same thing in every market and league.
Ranges in brackets are 95% intervals on the rated picks' hit rate, counting each match once: picks in the same match tend to land or miss together.
These tier rates are pooled across every market, so the headline average leans towards high-volume markets like over/under goals. Match result (1X2) — the hardest market to call — is shown on its own row in the table below; read the by-market figures, not the pooled average, as the honest measure of accuracy.
| Market | Gold | Silver | Bronze | Sample |
|---|---|---|---|---|
| Total goals (over / under) | 93% 9,086 of 9,800 picks from 6,261 matches (92–93%) | 89% 16,828 of 18,962 picks from 6,262 matches (88–89%) | 85% 22,012 of 25,901 picks from 6,262 matches (84–85%) | 54,663 |
| Double chance | — | 76% 328 of 432 picks from 342 matches (72–80%) | 75% 6,427 of 8,586 picks from 5,719 matches (74–76%) | 9,067 |
| Team to score | — | 82% 1,513 of 1,841 picks from 1,705 matches (80–84%) | 77% 6,691 of 8,698 picks from 5,656 matches (76–78%) | 10,622 |
| First-half goals | 89% 451 of 506 picks from 499 matches (86–92%) | 85% 4,567 of 5,379 picks from 5,200 matches (84–86%) | 80% 8,489 of 10,608 picks from 6,250 matches (79–81%) | 16,493 |
| Both teams to score | — | 56% 1,326 of 2,388 picks from 2,388 matches (54–58%) | 56% 9,445 of 16,965 picks from 16,965 matches (55–56%) | 19,530 |
TACTIX's forecasts are market-informed: the model's estimates, calibrated market by market, are blended with bookmakers' prices at the weight stated below. A dedicated three-way match-result model blends expected goals (xG) with a team Elo rating. On top of its base model, the current model adds per-market calibration (each market tuned to its own reliability), a dedicated three-way match-result model that combines expected goals with team Elo ratings, and, where it is switched on, a stacking layer over the base model's probabilities. Full detail is on our methodology page and the live performance is on the Model Scoreboard.
Market-informed forecasts. The weight in use: the match-result pick's probability and the both-teams-to-score and over/under 2.5 goals probabilities are blended with the bookmakers' implied probabilities at a fixed weight of 0.25 on the market.
Anywhere we discuss betting we carry 18+ messaging and signpost free, confidential help. Read our full responsible-gambling policy — including the National Gambling Helpline, BeGambleAware, GamCare and GAMSTOP.
This page explains how we measure accuracy. The forecasts themselves — win probabilities, xG and value across 240+ markets — live inside the product.