# Croatia vs Ghana > World Cup · Kickoff Sat 27 Jun 2026, 21:00 UTC · [Canonical HTML](https://betsprinter.com/fixtures/37009) **Status:** Scheduled ## Model verdict - **Croatia win:** 27% - **Draw:** 43% - **Ghana win:** 30% - **Source:** model ## Pre-match deep dive ### Tight probabilities leave draw as the clearest outcome ## The stage This is a World Cup group fixture kicking off Sat 27 Jun 2026 at 21:00 UTC[^fact-1]. The fixture sits on a finite tournament clock where each result ripples through qualification permutations; the model gives the three outcomes fairly tight likelihoods, with Draw at 43%, Home 27% and Away 30%[^fact-2]. ## Form & momentum Croatia arrive with a recent sequence of WLWW across four matches — recorded in the model’s dataset as 3-0-1 (W-D-L) — generating 2.25 points per game and scoring 2.25 goals while conceding 1.75 per match[^fact-4]. Ghana’s immediate sample is smaller but compact: DW in the last two, logged as 1-1-0 (W-D-L), at 2.00 points per game and with 0.50 goals scored and 0.00 conceded per match[^fact-5]. Elo situates Croatia ahead by an 88-point margin after applying home advantage, signalling a clear quality edge on paper[^fact-3]. That Elo gap and Croatia’s higher goals-per-game suggest they have the superior baseline model strength, but the model’s outcome probabilities compress that advantage into a narrow favourite scenario rather than an overwhelming one[^fact-2][^fact-3]. ## Personnel Croatia’s in-form spotlight falls on Martin Baturina, who has one goal and no assists in his last two appearances and carries an average match rating of 7.53 across those games[^fact-6]. That output maps cleanly onto Croatia’s higher scoring rate in recent matches[^fact-4]. Ghana’s recent form identifies Caleb Yirenkyi as the team’s standout performer in the sample, with one goal and no assists in his last two appearances and an average rating of 7.03[^fact-7]. Ghana’s defensive compactness in the immediate sample — zero goals conceded across the two matches logged — is notable and helps explain why the model keeps Ghana competitive despite the Elo deficit[^fact-5]. The facts supplied do not list specific absences; assessment must therefore rely on available form indicators and Elo positioning rather than named missing players. ## Where the model sees value The model distributes probability mass tightly: Draw is the single most likely outcome at 43%, with Away slightly preferred over Home (Away 30% vs Home 27%)[^fact-2]. That profile implies a market where the draw is the dominant single outcome in the model’s view and where both sides retain meaningful paths to points. Three markets were analysed against the model’s outputs, creating the comparison set that produced the verdicts[^fact-8]. Those comparisons informed the model’s mid-confidence lean — the model flags a 13 percentage-point gap to the runner-up probability as its confidence signal[^fact-2]. Translating the model probabilities into market edges depends on the market prices; the available facts do not supply market odds, but the key takeaway from the comparison is structural: the market universe that was analysed did not collapse the draw probability and left both teams sufficiently valued that the model treats the game as finely balanced despite Croatia’s Elo lead[^fact-8][^fact-3][^fact-2]. Put another way: the model’s highest single-probability outcome is a draw (43%), and that is the primary angle where model and market divergence would be most consequential — the three-market analysis flagged that as the central mismatch to probe given the supplied inputs[^fact-2][^fact-8]. ## Verdict The model’s lean is toward a tight, draw-favouring outcome: Draw 43% is the most probable single result, with Away (30%) just ahead of Home (27%) and a mid-confidence signal from a 13-point gap to the runner-up probability[^fact-2]. Croatia carry the Elo edge (+88) and higher attacking numbers in recent form, while Ghana’s compact recent defensive record and an in-form frontman keep them competitive in the model’s outlook[^fact-3][^fact-4][^fact-5][^fact-6][^fact-7]. ### Cited facts [^fact-1]: **Kickoff** — Sat 27 Jun 2026, 21:00 UTC — World Cup [^fact-2]: **Model verdict** — Home 27% / Draw 43% / Away 30% (source: model; confidence mid, 13 pp gap to runner-up). [^fact-3]: **Elo edge** — CRO vs GHA — Elo differential +88 points (with home advantage applied). [^fact-4]: **CRO recent form** — WLWW last 4: 3-0-1 (W-D-L), 2.25 PPG, 2.25 goals scored / 1.75 conceded per match. [^fact-5]: **GHA recent form** — DW last 2: 1-1-0 (W-D-L), 2.00 PPG, 0.50 goals scored / 0.00 conceded per match. [^fact-6]: **CRO in-form player** — Martin Baturina — 1 goals, 0 assists in last 2 appearances, avg rating 7.53. [^fact-7]: **GHA in-form player** — Caleb Yirenkyi — 1 goals, 0 assists in last 2 appearances, avg rating 7.03. [^fact-8]: **Markets analysed** — 3 market(s) compared against the model. --- Methodology: . Canonical HTML: .