# Grasshopper vs Winterthur > Super League · Kickoff Tue 12 May 2026, 18:30 UTC · [Canonical HTML](https://betsprinter.com/fixtures/813) **Status:** Finished **Final score:** Grasshopper 3–2 Winterthur ## Model verdict - **Grasshopper win:** 53% - **Draw:** 29% - **Winterthur win:** 17% - **Source:** model ## Pre-match deep dive ### Home edges but goals market divided — model prefers control ## The stage This Super League fixture kicks off on Tue 12 May 2026 at 18:30 UTC[^fact-1]. The model grades the home side as the favourite with a clear probability split: Home 53% / Draw 29% / Away 17%, and notes a high confidence level with a 24 percentage-point gap to the runner-up[^fact-2]. The Elo framework, with home advantage applied, also gives the hosts a meaningful edge, an advantage of +113 points[^fact-3]. ## Form & momentum Recent results paint a picture of two teams struggling for consistency. The home side’s last ten read LLLWL, which converts to 2-0-8 (W-D-L), yielding 0.60 points per game with an average of 0.80 goals scored and 2.40 conceded per match[^fact-4]. The visitors’ last ten are WDLLL, equivalent to 2-3-5 (W-D-L), producing 0.90 points per game with 1.30 goals scored and 1.90 conceded per match[^fact-5]. On pure form numbers the visitors are marginally better in points per game and scoring rate, but the combination of the model’s probability split and the Elo advantage points toward the home side holding the overall edge[^fact-2][^fact-3]. ## Personnel Offensive form is concentrated in two players. Jonathan Asp Jensen has contributed 1 goal and 1 assist across his last five appearances and carries an average match rating of 6.85[^fact-9]. For the visitors, Nishan Burkart arrives in hotter scoring streak: 3 goals in his last five appearances and a 7.20 average rating[^fact-10]. Availability issues remove established minutes from both sides: Michael Frey is absent through injury after contributing 629 minutes in the recent run[^fact-11], while Luca Zuffi is also out injured after 616 minutes in the same period[^fact-12]. Those absences strip out familiar minutes for each team and should influence how each coach approaches rotations and attacking responsibility[^fact-11][^fact-12]. ## Where the model sees value The model highlights three market edges after comparing three markets against market prices[^fact-13]. First, the strongest discrepancy sits on Over 2.5 goals: the model assigns 46% probability versus a market price implying 67.00 at Paddy Power, producing an edge of 44.1 percentage points and flagged with high confidence[^fact-6]. Second, the model favors Under 2.5 goals with 54% probability against a market price of 2.50 at Betfair Exchange, yielding a 14.4 percentage-point edge and also rated with high confidence[^fact-7]. Third, the match-winner market shows the model’s Home pick at 53% versus a Betfair Exchange market price of 2.04, an edge of 4.5 percentage points and described with mid confidence[^fact-8]. The juxtaposition of the first two edges is notable: the model splits marginally in favour of a lower-scoring outcome while also flagging a large market mispricing on the Over 2.5 line[^fact-6][^fact-7]. That tension echoes the teams’ defensive records — the home side concedes 2.40 goals per match while scoring only 0.80[^fact-4], and the visitors concede 1.90 while scoring 1.30[^fact-5] — creating plausible routes both for a low-scoring contest and for volatility that could push totals above 2.5[^fact-4][^fact-5]. The match-winner edge sits smaller and with lower confidence, reflecting the close split between a statistical favourite and the inherent variability in single matches[^fact-8][^fact-2]. ## Verdict The model leans to the home side at 53% while signalling clear uncertainty across goal markets: a modest home match-winner edge sits alongside a strong market distortion that simultaneously points to both Under and an overpriced Over 2.5 line[^fact-2][^fact-8][^fact-6][^fact-7]. Personnel absences and the contrasting goals-for/against profiles explain why the model favours control and caution, even as the Elo differential supports the home advantage[^fact-11][^fact-12][^fact-4][^fact-5][^fact-3]. ### Cited facts [^fact-1]: **Kickoff** — Tue 12 May 2026, 18:30 UTC — Super League [^fact-2]: **Model verdict** — Home 53% / Draw 29% / Away 17% (source: model; confidence high, 24 pp gap to runner-up). [^fact-3]: **Elo edge** — GRA vs Winterthur — Elo differential +113 points (with home advantage applied). [^fact-4]: **GRA recent form** — LLLWL last 10: 2-0-8 (W-D-L), 0.60 PPG, 0.80 goals scored / 2.40 conceded per match. [^fact-5]: **Winterthur recent form** — WDLLL last 10: 2-3-5 (W-D-L), 0.90 PPG, 1.30 goals scored / 1.90 conceded per match. [^fact-6]: **Value pick #1** — Over in Goals O/U 2.5 — model 46% vs market price 67.00 at Paddy Power, edge 44.1 pp (high confidence). [^fact-7]: **Value pick #2** — Under in Goals O/U 2.5 — model 54% vs market price 2.50 at Betfair Exchange, edge 14.4 pp (high confidence). [^fact-8]: **Value pick #3** — Home in Match Winner — model 53% vs market price 2.04 at Betfair Exchange, edge 4.5 pp (mid confidence). [^fact-9]: **GRA in-form player** — Jonathan Asp Jensen — 1 goals, 1 assists in last 5 appearances, avg rating 6.85. [^fact-10]: **Winterthur in-form player** — Nishan Burkart — 3 goals, 0 assists in last 5 appearances, avg rating 7.20. [^fact-11]: **GRA key absence** — Michael Frey out (injury), 629 minutes in recent run. [^fact-12]: **Winterthur key absence** — Luca Zuffi out (injury), 616 minutes in recent run. [^fact-13]: **Markets analysed** — 3 market(s) compared against the model. --- Methodology: . Canonical HTML: .