# England vs Ghana > World Cup · Kickoff Tue 23 Jun 2026, 20:00 UTC · [Canonical HTML](https://betsprinter.com/fixtures/36988) **Status:** Finished **Final score:** England 0–0 Ghana ## Model verdict - **England win:** 44% - **Draw:** 27% - **Ghana win:** 29% - **Source:** model ## Pre-match deep dive ### Tight game expected as model favours low-scoring outcome ## The stage This is a World Cup group fixture with kickoff scheduled for Tue 23 Jun 2026 at 20:00 UTC[^fact-1]. The specific venue is not part of the supplied facts; focus remains on how the available data shapes expectations. ## Form & momentum England arrive on recent form that reads WWW over the last three matches, averaging 3.00 points per game and scoring 2.67 goals while conceding 0.67 per match[^fact-4]. Ghana’s visible sample is smaller but perfect in its latest outing: W in the last match, worth 3.00 points, with 1.00 goals scored and 0.00 conceded in that game[^fact-5]. The quantitative gap between the nations is reflected in an Elo differential of +105 in England’s favour after home advantage is applied[^fact-3]. That Elo edge and England’s richer recent attacking output suggest the home side carries the more convincing underlying profile into the fixture[^fact-3][^fact-4]. Model probabilities put England as the most likely outcome at 44%, a draw at 27% and an away win for Ghana at 29% — the model reports high confidence, with a 15 percentage-point gap to the runner-up outcome[^fact-2]. That distribution underlines a clear leaning without treating this as a foregone conclusion; the model’s mark for a draw and Ghana win together still make up 56% when combined[^fact-2]. ## Personnel Two form players stand out in the supplied facts. England’s most in-form attacking outlet in the provided sample is Harry Kane: 2 goals and 0 assists in the last appearance, with an average match rating of 8.67[^fact-7]. Ghana’s in-form focal point in the supplied sample is Caleb Yirenkyi: 1 goal and 0 assists in his last appearance, average rating 7.74[^fact-8]. These figures suggest both sides have match-winners arriving with momentum in the attacking third, though the sample sizes here are limited to the recent appearances included in the facts[^fact-7][^fact-8]. The supplied facts do not list squad absences or suspensions, so no definitive assessment of enforced changes can be made from the material provided[^fact-9]. ## Where the model sees value The clearest market-model divergence in the supplied analysis is on total goals. The model favours Under 2.5 goals at 54% while the market at Pinnacle is pricing the line at 2.30 (implying a market probability materially lower than the model’s), yielding an edge of 10.9 percentage points and labelled with high confidence by the modelers[^fact-6]. That is the primary priced discrepancy highlighted across the markets compared: three markets were analysed against the model in the supplied facts[^fact-9]. Context from form helps make sense of that under lean. England’s recent matches show a high goals-scored rate (2.67 per match) but also low goals conceded (0.67 per match), producing contests that have been decisive yet not necessarily high-scoring from both sides’ perspectives[^fact-4]. Ghana’s most recent match was low-scoring in the supplied facts (1.00 goals scored, 0.00 conceded in that match), which aligns with the model’s tilt towards an under outcome[^fact-5]. The model’s probability implies it expects a tighter, lower-scoring game than the market does overall[^fact-6][^fact-2]. ## Verdict The model leans to England as the single most likely result (44%), but the probabilities preserve room for a draw or Ghana victory (27% and 29% respectively), and the standout priced edge between model and market is on Under 2.5 goals where the model assigns 54% versus the market price at Pinnacle, an edge of 10.9 percentage points[^fact-2][^fact-6][^fact-9]. Given the Elo cushion for England (+105) and the recent form snapshots, expect a match tilted to the home side but with a reasonable chance of finishing low on goals according to the supplied model outputs[^fact-3][^fact-4][^fact-6]. ### Cited facts [^fact-1]: **Kickoff** — Tue 23 Jun 2026, 20:00 UTC — World Cup [^fact-2]: **Model verdict** — Home 44% / Draw 27% / Away 29% (source: model; confidence high, 15 pp gap to runner-up). [^fact-3]: **Elo edge** — ENG vs GHA — Elo differential +105 points (with home advantage applied). [^fact-4]: **ENG recent form** — WWW last 3: 3-0-0 (W-D-L), 3.00 PPG, 2.67 goals scored / 0.67 conceded per match. [^fact-5]: **GHA recent form** — W last 1: 1-0-0 (W-D-L), 3.00 PPG, 1.00 goals scored / 0.00 conceded per match. [^fact-6]: **Value pick #1** — Under in Goals O/U 2.5 — model 54% vs market price 2.30 at Pinnacle, edge 10.9 pp (high confidence). [^fact-7]: **ENG in-form player** — Harry Kane  — 2 goals, 0 assists in last 1 appearances, avg rating 8.67. [^fact-8]: **GHA in-form player** — Caleb Yirenkyi — 1 goals, 0 assists in last 1 appearances, avg rating 7.74. [^fact-9]: **Markets analysed** — 3 market(s) compared against the model. --- Methodology: . Canonical HTML: .