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Group L · Matchday 7 · 2026-06-17

Ghana vs Panama

Toronto, Canada · neutral venue

Most likely scoreline

0–0 13.7%

40.2%

GHA win

28.6%

Draw

31.2%

PAN win

Top scorelines

0–0 13.7%
1–0 13.2%
0–1 11.4%
1–1 11.0%

Total goals

0 to 10 goals · most likely → tallest

The agent’s call

3-agent ensemble · deepseek-chat

GHA win

36.7%

Draw

29.7%

PAN win

33.7%

The model's prior (40% home win) is slightly optimistic given Ghana's poor recent form (LLLLD) against Panama's solid run (DWLWD). However, Ghana's key players are at a higher club level, which offsets the form gap. The head-to-head is blank, conditions are neutral, and no injuries or relevant news shift the balance. I adjust the model downward for Ghana and upward for Panama, making the outcome nearly even: 35% home, 30% draw, 35% away. Both teams have modest expected goals (Ghana 1.20, Panama 1.00) and the model's top scorelines are low-scoring (0-0, 1-0, 0-1, 1-1). Given the form and quality, a 1-1 draw is the most likely single scoreline, with 0-0 and 1-0/0-1 also common. The distribution remains tight, with 2-1 and 1-2 less likely but possible.

What the agent weighed

Recent form

Ghana's last 5 matches: LLLLD (0 wins, 1 draw, 4 losses). Panama's last 5: DWLWD (2 wins, 2 draws, 1 loss). → favours Panama
Head-to-head

No previous meetings between Ghana and Panama. → no bearing
Availability

No injuries or suspensions reported for either side. → no bearing
Key players

Ghana's key players (Ayew, Partey, I. Williams, Nuamah, Fatawu) play at higher club levels (Leicester, Athletic Club) than Panama's (Waterman, Fajardo, Díaz, Davis, Murillo) who mostly play in South America or Ligue 1 (Marseille). → favours Ghana
Recent news

News articles about Ghana's roster preview and Asamoah Gyan's comments are generic; one article about Ezzalzouli injury is irrelevant (he is Moroccan). Panama news articles are about Neymar and England, not relevant. → no bearing
Conditions

BMO Field: 19.4°C, overcast, 54% humidity, 13 km/h wind, no precipitation. Mild conditions, no extreme heat or altitude. Roof is not controlled, but weather is neutral. → no bearing
Model vs market

Model gives Ghana 40% win, draw 29%, Panama 31% win. No market lines supplied, so model is the only prior. → favours Ghana slightly

What the agent checked on the web

Searched tavily for GHA · PAN — 6 sources kept

Agent scorelines

0–0 18%
1–0 16%
1–1 16%
0–1 15%
2–1 10%
0–2 9%

generated 2026-06-11

Last 5 — GHA

-0.36 pts/match vs model expectation · opp. avg #27

KOR #37 -0.8
AUT #22 -0.7
GER #7 -0.3
MEX #21 -0.7
WAL #46 +0.1

GF / GA last 10: 11 / 14

Last 5 — PAN

+0.19 pts/match vs model expectation · opp. avg #69

RSA #64 -0.1
RSA #64 +1.9
BRA #3 -0.1
DOM #149 +0.5
BIH #63 -0.5

GF / GA last 10: 18 / 16

Head-to-head (last 5)

No prior meetings in the dataset.

▸ Full score grid (7×7)

P(home goals × away goals), %

13.7

11.4

5.7

2.2

0.7

0.2

0.1

13.2

11.0

5.5

2.2

0.7

0.2

0.1

7.7

6.4

3.2

1.3

0.4

0.1

0.0

3.5

2.9

1.5

0.6

0.2

0.1

0.0

1.4

1.1

0.6

0.2

0.1

0.0

0.5

0.4

0.2

0.1

0.0

0.2

0.1

0.0

Rows = GHA goals; columns = PAN goals. Above-diagonal cells are home wins; diagonal = draws; below = away wins. Truncated at 6 — the joint mass past that is < 1 %.

Expected goals (Poisson rate, λ)

1.2

GHA

1.0

PAN

Independent-Poisson rates. W/D/L and the score grid integrate the full 13×13 joint under these two parameters.

News context — injuries, suspensions, projected XI — is not part of the model, which sees only past results.