# South Africa vs Canada > World Cup · Kickoff Sun 28 Jun 2026, 19:00 UTC · [Canonical HTML](https://betsprinter.com/fixtures/37015) **Status:** Scheduled ## Model verdict - **South Africa win:** 58% - **Draw:** 28% - **Canada win:** 15% - **Source:** model ## Pre-match deep dive ### Model leans home: South Africa’s edge backed by Elo gap ## The stage This World Cup fixture kicks off Sun 28 Jun 2026, 19:00 UTC[^fact-1]. The match arrives with clear home/away framing in the model’s probabilities: the home side is favoured, the draw is the second-most likely outcome, and the away win is the longest shot[^fact-2]. The model’s confidence is meaningful, with a substantial gap between the top pick and the runner-up result[^fact-2]. ## Form & momentum Recent results paint a picture of two teams with similar point returns but different goal profiles. South Africa’s last three matches produced one win, one draw and one loss — 1.33 points per game — with 0.67 goals scored and 1.00 conceded per match[^fact-4]. Canada’s three-match sequence is the mirror of results in W-D-L order and the same 1.33 points per game, but with a much higher scoring rate at 2.67 goals scored and the same 1.00 conceded per match[^fact-5]. Those river-deep differences in goals-for show where the match narrative diverges: Canada generates considerably more raw attacking output over the sample while South Africa’s scoring is scarce[^fact-4][^fact-5]. On raw strength adjusted for venue, the Elo differential favours the hosts by a clear margin — South Africa enjoys a +93-point edge once home advantage is applied[^fact-3]. That Elo tilt maps cleanly to the model’s probabilities, where the home outcome is the 58% base case[^fact-2]. ## Personnel The supplied facts flag two players carrying recent form for their countries. Teboho Mokoena has one goal in his last two appearances, no assists, and an average rating of 7.51 across that sample[^fact-6]. Jonathan David has been more prolific: three goals in his last three appearances, no assists, and an average rating of 7.62[^fact-7]. Those are the only player-level form signals provided in the facts and frame where each team’s recent attacking momentum resides[^fact-6][^fact-7]. The supplied facts do not include any explicit absence or suspension information, so heavier personnel caveats cannot be assessed from the data here[^fact-6][^fact-7]. ## Where the model sees value The model’s probability split is Home 58% / Draw 28% / Away 15%, a distribution with a 30-percentage-point gap between favourite and runner-up and high confidence in the lean[^fact-2]. That is the principal market edge to interrogate: the home victory is the central expectation and aligns with a substantive Elo advantage of +93 points for the hosts after adjusting for venue[^fact-3][^fact-2]. Markets were compared in three instances against the model to identify discrepancies[^fact-8]. The core mismatch the model flags is the translation of South Africa’s Elo and home bias into market odds: when the model assigns 58% to the home win, market prices that under or overstate that probability become the primary exploitable lines[^fact-2][^fact-8]. Separately, Canada’s superior recent goals-per-game figure (2.67 in the last three) is a specific signal the model weights differently than simple market narratives that might underplay Canada’s attacking form[^fact-5][^fact-8]. Finally, the concentrated in-form scoring output from Jonathan David (three goals in three) suggests the model is sensitive to single-player firing streaks when comparing expected goals or scorer markets against market prices[^fact-7][^fact-8]. Because only three markets were analysed against the model in the supplied facts, the desk flags those comparisons as the highest-confidence lines where model/market divergence has been explicitly measured[^fact-8]. Exact market odds were not supplied in the facts, so readers should map the model’s 58% home probability and 15% away probability to whichever market prices are available to identify percentile mispricings[^fact-2][^fact-8]. ## Verdict The model leans decisively toward the hosts: a 58% chance for the home result reflects the +93 Elo edge and a high-confidence split between outcomes[^fact-2][^fact-3]. Canada’s recent scoring spike and Jonathan David’s form are meaningful counterpoints, but the supplied metrics still favour the home side as the single most probable outcome[^fact-5][^fact-7] ### Cited facts [^fact-1]: **Kickoff** — Sun 28 Jun 2026, 19:00 UTC — World Cup [^fact-2]: **Model verdict** — Home 58% / Draw 28% / Away 15% (source: model; confidence high, 30 pp gap to runner-up). [^fact-3]: **Elo edge** — RSA vs CAN — Elo differential +93 points (with home advantage applied). [^fact-4]: **RSA recent form** — WDL last 3: 1-1-1 (W-D-L), 1.33 PPG, 0.67 goals scored / 1.00 conceded per match. [^fact-5]: **CAN recent form** — LWD last 3: 1-1-1 (W-D-L), 1.33 PPG, 2.67 goals scored / 1.00 conceded per match. [^fact-6]: **RSA in-form player** — Teboho Mokoena — 1 goals, 0 assists in last 2 appearances, avg rating 7.51. [^fact-7]: **CAN in-form player** — Jonathan David — 3 goals, 0 assists in last 3 appearances, avg rating 7.62. [^fact-8]: **Markets analysed** — 3 market(s) compared against the model. --- Methodology: . Canonical HTML: .