Soccer predictions: actual data vs predicted data
Slate 20260711 · 2 match(es)
How to read this report. Each match shows the model's headline prediction, the stage-by-stage lambda (goal-rate) build, both teams' standing/form inputs, and every starter's projected line next to their real season baseline. A moderate / large deviation badge flags a projection that strays far from the player's season form — a quick way to spot when the inputs look right but a projection does not. When the real result is known an actual-vs-predicted banner appears.
All matches overview
| Match | Score | Winner | H / D / A | O2.5 | BTTS | Conf | λ H/A | Actual | Result |
|---|
| Norway vs England FIFA World Cup | 0-1 | England | 13.7% / 20.7% / 65.6% | 51.8% | 46.4% | 0.79 | 0.81 / 2.08 | - | pending |
| Argentina vs Switzerland FIFA World Cup | 1-0 | Argentina | 41.9% / 29.1% / 29.0% | 37.6% | 44.0% | 0.71 | 1.29 / 1.02 | - | pending |
Match detail
Norway vs England
FIFA World Cup · 20260711 · 4-3-3 vs 4-2-3-1
Predicted 0-1Winner: EnglandConfidence 0.79λ home/away 0.81 / 2.08Most-likely P 12.6%
Actual vs predicted: result not available yet (upcoming fixture).
Lambda decomposition (how the goal rates were built)
| Stage | Norway λ | England λ |
|---|
| Pre-calibration | 0.813 | 2.080 |
| Final λ | 0.813 | 2.080 |
competition calibration scale 1.0competition observed total goals 0.0quality gap applied Truemismatch score pressure applied Falsecompetitive underdog floor applied Falsestage discount 1.0
Scoreline distribution & markets
| Top 5 scorelines | P |
|---|
| 0-1 | 12.6% |
| 0-2 | 12.5% |
| 1-1 | 9.8% |
| 1-2 | 9.7% |
| 0-3 | 8.2% |
| Home win | 13.7% |
| Draw | 20.7% |
| Away win | 65.6% |
| Over 2.5 | 51.8% |
| BTTS yes | 46.4% |
Pregame fair line — favorite England (65.6%), fair total 2.89, fair spread -1.27
Projected players vs season baseline
Proj = projected for this match · Season = this season's per-game average from match data · deviation badge compares projected xG to the player's season xG/game.
Norway — projected line vs season baseline (4-3-3)
| Player | Pos | Min | Proj G | Proj xG | Season xG/g | | Proj Sh | Season Sh/g | Proj Rtg | Season Rtg | Rec |
|---|
| Antonio Nusa | F | 62 | 0 | 0.00 | 0.03 | 98% | 2 | 0.6 | 83.5 | 44.3 | 12 |
| Erling Haaland | F | 95 | 0 | 0.39 | 0.46 | ok | 2 | 2.1 | 98.7 | 40.1 | 15 |
| Alexander Sørloth | F | 45 | 0 | 0.00 | 0.06 | 96% | 2 | 0.5 | 90.7 | 41.4 | 19 |
| Patrick Berg | M | 68 | 0 | 0.00 | 0.02 | 100% | 0 | 0.4 | 83.9 | 53.5 | 8 |
| Sander Berge | M | 88 | 0 | 0.00 | 0.01 | 100% | 1 | 0.2 | 86.4 | 31.8 | 13 |
| Martin Ødegaard | M | 77 | 0 | 0.04 | 0.12 | 67% | 2 | 0.8 | 94.6 | 39.2 | 16 |
| David Møller Wolfe | D | 80 | 0 | 0.00 | - | n/a | 0 | 0.0 | 79.6 | 46.8 | 10 |
| Torbjørn Heggem | D | 66 | 0 | 0.22 | 0.03 | 652% | 0 | 0.1 | 79.9 | 46.0 | 13 |
| Kristoffer Ajer | D | 92 | 0 | 0.12 | 0.02 | 680% | 0 | 0.1 | 82.2 | 31.5 | 13 |
| Julian Ryerson | M | 92 | 0 | 0.00 | 0.02 | 100% | 1 | 0.2 | 86.2 | 34.6 | 14 |
| Ørjan Nyland | G | 88 | 0 | 0.00 | - | n/a | | 0.0 | 82.7 | 35.2 | 10 |
| Team totals | 0 | 0.81 | | 10 | | 86.2 | |
England — projected line vs season baseline (4-2-3-1)
| Player | Pos | Min | Proj G | Proj xG | Season xG/g | | Proj Sh | Season Sh/g | Proj Rtg | Season Rtg | Rec |
|---|
| Bukayo Saka | F | 41 | 0 | 0.00 | 0.16 | 99% | 2 | 1.2 | 95.6 | 45.5 | 19 |
| Declan Rice | M | 95 | 0 | 0.00 | 0.02 | 100% | 2 | 0.7 | 95.0 | 52.2 | 20 |
| Elliot Anderson | M | 94 | 0 | 0.04 | 0.04 | ok | 1 | 1.0 | 88.2 | 57.3 | 18 |
| Nico O'Reilly | D | 89 | 0 | 0.27 | 0.12 | 131% | 1 | 0.7 | 80.2 | 37.8 | 15 |
| John Stones | D | 42 | 0 | 0.00 | 0.00 | 100% | 0 | 0.1 | 88.6 | 23.5 | 14 |
| Ezri Konsa | D | 95 | 0 | 0.36 | 0.07 | 399% | 1 | 0.3 | 89.7 | 52.6 | 20 |
| Djed Spence | D | 43 | 0 | 0.29 | 0.05 | 549% | 0 | 0.2 | 85.3 | 61.8 | 13 |
| Jordan Pickford | G | 92 | 0 | 0.00 | - | n/a | | 0.0 | 90.6 | 42.9 | 14 |
| Jude Bellingham | M | 79 | 0 | 0.40 | 0.18 | 128% | 2 | 1.1 | 98.4 | 57.3 | 16 |
| Anthony Gordon | F | 49 | 0 | 0.00 | 0.04 | 91% | 2 | 0.3 | 90.3 | 22.7 | 21 |
| Harry Kane | F | 94 | 1 | 0.67 | 0.46 | 48% | 2 | 2.6 | 97.4 | 63.5 | 17 |
| Team totals | 1 | 2.08 | | 13 | | 90.8 | |
Antagonist / tactical summary
Midfield is evenly contested — Martin Ødegaard vs Jude Bellingham will be the pivotal duel. Total antagonist xG — Home: 0.82, Away: 1.17. Home danger zone: Striker vs Two Centre Backs — 1v2 Aerial/Physical Battle. Away danger zone: Striker vs Two Centre Backs — 1v2 Aerial/Physical Battle.
Midfield — possession 48.2% / 51.8%, dominance ratio 0.44, key duel: Martin Ødegaard vs Jude Bellingham
Alexander Sørloth xG 0.00Antonio Nusa xG 0.00Erling Haaland xG 0.68Declan Rice xG 0.44Bukayo Saka xG 0.00Anthony Gordon xG 0.00
Summary
Antagonist matchup analysis for Norway vs England. Most likely scoreline: 0-1. Lambdas derived from 5 home and 5 away individual player duels.
Tactical parity between 4-3-3 and 4-2-3-1. Match outcome driven primarily by individual player quality. Midfield is evenly contested — Martin Ødegaard vs Jude Bellingham will be the pivotal duel. Total antagonist xG — Home: 0.82, Away: 1.17. Home danger zone: Striker vs Two Centre Backs — 1v2 Aerial/Physical Battle. Away danger zone: Striker vs Two Centre Backs — 1v2 Aerial/Physical Battle.
Argentina vs Switzerland
FIFA World Cup · 20260711 · 4-3-1-2 vs 4-2-3-1
Predicted 1-0Winner: ArgentinaConfidence 0.71λ home/away 1.29 / 1.02Most-likely P 13.5%
Actual vs predicted: result not available yet (upcoming fixture).
Lambda decomposition (how the goal rates were built)
| Stage | Argentina λ | Switzerland λ |
|---|
| Pre-competitive-floor | 1.291 | 0.786 |
| Pre-calibration | 1.291 | 0.786 |
| Final λ | 1.291 | 1.020 |
competition calibration scale 1.0competition observed total goals 0.0quality gap applied Truemismatch score pressure applied Falsecompetitive underdog floor applied Truestage discount 1.0
Scoreline distribution & markets
| Top 5 scorelines | P |
|---|
| 1-0 | 13.5% |
| 1-1 | 13.4% |
| 0-0 | 11.2% |
| 0-1 | 10.7% |
| 2-0 | 8.4% |
| Home win | 41.9% |
| Draw | 29.1% |
| Away win | 29.0% |
| Over 2.5 | 37.6% |
| BTTS yes | 44.0% |
Pregame fair line — favorite Argentina (41.9%), fair total 2.31, fair spread 0.27
Projected players vs season baseline
Proj = projected for this match · Season = this season's per-game average from match data · deviation badge compares projected xG to the player's season xG/game.
Argentina — projected line vs season baseline (4-3-1-2)
| Player | Pos | Min | Proj G | Proj xG | Season xG/g | | Proj Sh | Season Sh/g | Proj Rtg | Season Rtg | Rec |
|---|
| Emiliano Martínez | G | 91 | 0 | 0.00 | - | n/a | | 0.0 | 91.7 | 48.4 | 20 |
| Lautaro Martínez | F | 55 | 0 | 0.12 | 0.37 | 69% | 2 | 1.3 | 95.3 | 55.1 | 10 |
| Lionel Messi | F | 78 | 1 | 0.25 | 0.49 | 49% | 2 | 2.8 | 94.4 | 51.8 | 12 |
| Alexis Mac Allister | M | 92 | 0 | 0.06 | 0.13 | 55% | 2 | 1.2 | 94.4 | 42.6 | 17 |
| Enzo Fernández | M | 87 | 0 | 0.09 | 0.09 | ok | 1 | 0.9 | 91.6 | 39.2 | 15 |
| Leandro Paredes | M | 70 | 0 | 0.02 | 0.02 | 58% | 1 | 0.6 | 85.1 | 37.9 | 14 |
| Rodrigo De Paul | M | 84 | 0 | 0.00 | 0.10 | 100% | 1 | 0.5 | 91.0 | 38.3 | 11 |
| Nicolás Tagliafico | D | 75 | 0 | 0.02 | 0.00 | 404% | 0 | 0.2 | 84.4 | 29.7 | 13 |
| Lisandro Martínez | D | 95 | 0 | 0.02 | 0.01 | 183% | 1 | 0.2 | 88.7 | 38.2 | 13 |
| Cristian Romero | D | 93 | 0 | 0.13 | 0.03 | 322% | 0 | 0.2 | 89.6 | 32.4 | 13 |
| Gonzalo Montiel | D | 49 | 0 | 0.55 | 0.07 | 730% | 0 | 0.1 | 84.6 | 22.1 | 12 |
| Team totals | 1 | 1.29 | | 11 | | 90.1 | |
Switzerland — projected line vs season baseline (4-2-3-1)
| Player | Pos | Min | Proj G | Proj xG | Season xG/g | | Proj Sh | Season Sh/g | Proj Rtg | Season Rtg | Rec |
|---|
| Rubén Vargas | M | 53 | 0 | 0.13 | 0.07 | 82% | 2 | 0.7 | 81.9 | 31.8 | 18 |
| Fabian Rieder | M | 59 | 0 | 0.00 | 0.05 | 100% | 0 | 0.2 | 80.7 | 27.3 | 15 |
| Dan Ndoye | M | 86 | 0 | 0.00 | 0.03 | 100% | 2 | 0.6 | 86.3 | 18.2 | 23 |
| Granit Xhaka | M | 88 | 0 | 0.00 | 0.05 | 100% | 2 | 0.3 | 92.3 | 29.7 | 18 |
| Remo Freuler | M | 81 | 0 | 0.00 | 0.03 | 100% | 0 | 0.3 | 87.7 | 37.9 | 18 |
| Ricardo Rodríguez | D | 85 | 0 | 0.01 | 0.00 | 1088% | 0 | 0.1 | 80.7 | 33.8 | 18 |
| Nico Elvedi | D | 90 | 0 | 0.15 | 0.03 | 425% | 1 | 0.2 | 84.1 | 26.9 | 16 |
| Manuel Akanji | D | 92 | 0 | 0.28 | 0.02 | 1373% | 0 | 0.1 | 89.5 | 21.1 | 14 |
| Denis Zakaria | M | 95 | 0 | 0.05 | 0.04 | ok | 1 | 0.3 | 89.0 | 16.6 | 16 |
| Gregor Kobel | G | 95 | 0 | 0.00 | - | n/a | | 0.0 | 93.6 | 36.6 | 16 |
| Breel Embolo | F | 73 | 0 | 0.34 | 0.27 | ok | 2 | 1.0 | 84.0 | 32.7 | 15 |
| Team totals | 0 | 1.02 | | 11 | | 86.3 | |
Antagonist / tactical summary
Midfield is evenly contested — Enzo Fernández vs Dan Ndoye will be the pivotal duel. Total antagonist xG — Home: 0.63, Away: 0.92. Home danger zone: Attacking Mid vs Double Pivot — Tight Space Battle. Away danger zone: Striker vs Two Centre Backs — 1v2 Aerial/Physical Battle.
Midfield — possession 50.9% / 49.1%, dominance ratio 0.53, key duel: Enzo Fernández vs Dan Ndoye
Lautaro Martínez xG 0.17Lionel Messi xG 0.36Alexis Mac Allister xG 0.10Rubén Vargas xG 0.12Dan Ndoye xG 0.21Granit Xhaka xG 0.25
Summary
Antagonist matchup analysis for Argentina vs Switzerland. Most likely scoreline: 1-0. Lambdas derived from 3 home and 4 away individual player duels.
Tactical parity between 4-3-1-2 and 4-2-3-1. Match outcome driven primarily by individual player quality. Midfield is evenly contested — Enzo Fernández vs Dan Ndoye will be the pivotal duel. Total antagonist xG — Home: 0.63, Away: 0.92. Home danger zone: Attacking Mid vs Double Pivot — Tight Space Battle. Away danger zone: Striker vs Two Centre Backs — 1v2 Aerial/Physical Battle.
Generated 2026-09-04 22:27:55 UTC · Soccer prediction reporting