Brentford v Nottingham Forest
Brentford host Nottingham Forest in matchweek 9.
Sat, Oct 31, 11:00 AM ET · Matchweek 9 · Premier League
Club research: Brentford · Nottingham Forest
Tested blind on past seasons. These are the model's own probability distributions, published so you can see what it says — not picks, not advice, and not compared against any price.
Tested blind on nine past Premier League seasons (2013-14 to 2021-22, 3,420 matches) it was never fit on, where it beat the previous model and a plain rating system. Its total-goals numbers follow the league's recent scoring rate, so they are the same for every match — in that test they were more accurate than the previous model's team-by-team totals. Its live record this season is still being graded. 40 Premier League matches have been graded under this model — far too few to support any accuracy claim. No live win rate or accuracy figure is quoted until its season record is large enough to mean something. 36 matches were graded under the model this one replaced; that record is kept separately and is not evidence for this model.
Model-only for now: no market snapshot recent enough to compare covers this fixture yet, so there is no market comparison here — only the model's own numbers. An older captured price may still appear on a suggested card, which accepts older captures and shows the price it used. Prices join this forecast closer to kickoff, and this snapshot refreshes until then.
Brentford host Nottingham Forest in matchweek 9.
The draw is a real outcome and is never folded away.
Two of three outcomes
Each is a sum of the three probabilities above, so it cannot disagree with them.
These ten account for 75.2% of the distribution — the remaining 24.8% is spread across every other scoreline.
| Score (Brentford–Nottingham Forest) | Probability | |
|---|---|---|
| 1–1 | 11.3% | |
| 1–0 | 10.5% | |
| 2–1 | 9.7% | |
| 2–0 | 9% | |
| 0–1 | 6.6% | |
| 1–2 | 6.1% | |
| 0–0 | 6.1% | |
| 3–1 | 5.5% | |
| 2–2 | 5.2% | |
| 3–0 | 5.1% |
Expected 2.79. The middle half of the distribution falls between 2 and 4 goals.
Probability of each total (goals)
Over / under ladder
| Line | Over | Under |
|---|---|---|
| 0.5 | 93.9% | 6.1% |
| 1.5 | 76.8% | 23.2% |
| 2.5 | 52.9% | 47.1% |
| 3.5 | 30.7% | 69.3% |
| 4.5 | 15.2% | 84.8% |
Half lines only — a match cannot land exactly on one, so over and under sum to 100% with no push.
The marginal of the same grid — not a separate fit, so these add back to the total above.
Every figure is an exact sum over the same score grid.
Winning margin (Brentford goals − Nottingham Forest goals)
Positive means Brentford win by that many, 0 is the draw, negative means Nottingham Forest. Margins beyond ±4 carry the remaining mass and are not drawn.
The lineup is not posted yet, so each figure is the chance that player scores IF he starts — not a claim that he will. This is a different model from the score matrix above, with its own out-of-sample test.
| Player | Club | Appearances | To score | A shot on target |
|---|---|---|---|---|
| Igor Thiago | Brentford | 38 | 36.4% | 64.4% |
| Chris Wood | Nottingham Forest | 75 | 35.4% | 59.3% |
| Callum Wilson | Brentford | 43 | 35.3% | 61.2% |
| Arnaud Kalimuendo | Nottingham Forest | none | 26.1% | 55.1% |
| Gustavo Nunes | Brentford | none | 26.1% | 55.1% |
| Kaye Furo | Brentford | none | 26.1% | 55.1% |
| Liam Delap | Nottingham Forest | 44 | 24.8% | 54.9% |
| Callum Hudson-Odoi | Nottingham Forest | 66 | 22.3% | 49.4% |
| Igor Jesus | Nottingham Forest | 28 | 21.7% | 49.2% |
| Dan Ndoye | Nottingham Forest | 14 | 20.7% | 40.9% |
| Jaidon Anthony | Brentford | 45 | 20.5% | 47.1% |
| Kevin Schade | Brentford | 68 | 20.5% | 50% |
Showing the 12 likeliest of 53. No injury or suspension feed exists here, so a player who is unavailable can still appear in this list. Shots on target is a separate model from the scorer figure beside it, fitted and tested on its own — the two are not derived from one another and can disagree.
Per-club attack and defence rates are fitted to Premier League results only, then combined into an exact Poisson score matrix for this fixture. Every probability on this page is a closed-form sum over that one grid — there is no sampling here, so there is no run count to quote and the figures are identical for every visitor, every time.
The fit takes an explicit cutoff at the run clock, so it cannot see a result from a match it is forecasting. Team-level only: no lineup, injury or team-news input exists in this model, by design.
Paper-only and educational. Not betting advice. All Premier League fixtures