# Wisła Kraków vs Katowice > Ekstraklasa · Kickoff Sun 26 Jul 2026, 18:15 UTC · [Canonical HTML](https://betsprinter.com/fixtures/37246) **Status:** Scheduled ## Model verdict - **Wisła Kraków win:** 17% - **Draw:** 20% - **Katowice win:** 63% - **Source:** model ## Top published picks | Market | Selection | Best odds | Bookmaker | Model % | Edge | | --- | --- | ---: | --- | ---: | ---: | | totals | Under | 1.95 | bet365 | 54% | +3.1 pp | ## Pre-match deep dive ### Model leans heavily to the visitors after decisive statistical gap ## The stage This Ekstraklasa fixture kicks off Sun 26 Jul 2026, 18:15 UTC — a fixture that the model treats as strongly skewed despite home advantage being applied in the calculations[^fact-1][^fact-3]. The only official competition tag available for the match in the data is Ekstraklasa, and the model’s probabilities frame the pre-match narrative more than any other single item in the file[^fact-1][^fact-2]. ## Form & momentum Recent results and expected strength point in the same direction. Wisła Kraków’s last ten read LLDDL, recorded as 1-5-4 (W-D-L) with 0.80 points per game, and they have averaged 1.40 goals scored and 1.80 conceded per match across that span[^fact-4]. Katowice enter with a steadier run of DDDWD, recorded as 3-5-2 (W-D-L) with 1.40 points per game, and a goals profile of 1.70 scored and 1.30 conceded per match[^fact-5]. The Elo differential after applying home advantage still sits at -100 in favour of the visitors, a substantial gap that aligns with the lopsided model probabilities and quantifies the quality gap the model is using[^fact-3][^fact-2]. Put bluntly: Katowice are on noticeably better recent form on points and defensive balance, and the Elo metric — already adjusted for home influence — gives the visitors a clear edge[^fact-5][^fact-3]. The model’s posterior is decisive: Home 12% / Draw 21% / Away 67%, a 46 percentage-point gap from the winner to the runner-up that signals high model confidence[^fact-2]. ## Personnel Wisła’s most in-form attacking outlet in the sample is Giorgi Tsitaishvili, who has contributed 1 goal and 1 assist in his last five appearances and carries an average match rating of 7.34 in that window[^fact-7]. That influence will matter for a side that has struggled for points and concedes at a higher clip than it scores in recent matches[^fact-4][^fact-7]. Katowice’s standout contributor in form is Eman Markovic, with 2 goals and 1 assist in his last five appearances and an average rating of 7.12 across those games[^fact-8]. Absences change context. Wisła will be without Piotr Starzyński, listed as out with an injury and showing only 24 minutes in a recent run, a note that limits a depth option on the attacking flank or rotation pool[^fact-9]. Katowice’s key missing player is Rafal Straczek, also out injured but with a much larger recent presence of 630 minutes recorded in the data, implying a heavier importance to that absence in terms of minutes lost[^fact-10]. Each absence is flagged in the dataset and must be read against the players who remain available and in form[^fact-9][^fact-10]. ## Where the model sees value Markets were scanned and compared to the model in three instances according to the dataset[^fact-11]. The clearest mispricing the model identifies is on the Under 2.5 goals line: the model assigns a 54% probability to Under 2.5 while the market price shown in the data sits at 1.95 on bet365, producing an edge of 3.1 percentage points for the model’s projection (noted as low confidence in the file)[^fact-6][^fact-11]. That single quantified market discrepancy is the only enumerated edge in the supplied comparisons; no other market-level edges are provided in the facts[^fact-6][^fact-11]. Given the model’s heavy lean toward the away side and the Under 2.5 angle being the only flagged market edge, the statistical picture in the dataset points toward a game that the model expects to be controlled enough by the visitors to suppress combined scoring slightly below the 2.5 threshold while still producing an away win probability that dominates the outcome space[^fact-2][^fact-6]. ## Verdict The model’s projection is unambiguous: Away 67% with the runner-up far behind at 21% for a draw and 12% for a home win, and an Elo shortfall of 100 points for the hosts after home adjustment underpins that gap[^fact-2][^fact-3]. The only market the model marks as an exploitable edge in the supplied file is Under 2.5 goals versus a market price of 1.95, though that edge is flagged with low confidence in the dataset[^fact-6][^fact-11]. ### Cited facts [^fact-1]: **Kickoff** — Sun 26 Jul 2026, 18:15 UTC — Ekstraklasa [^fact-2]: **Model verdict** — Home 12% / Draw 21% / Away 67% (source: model; confidence high, 46 pp gap to runner-up). [^fact-3]: **Elo edge** — WKR vs KAT — Elo differential -100 points (with home advantage applied). [^fact-4]: **WKR recent form** — LLDDL last 10: 1-5-4 (W-D-L), 0.80 PPG, 1.40 goals scored / 1.80 conceded per match. [^fact-5]: **KAT recent form** — DDDWD last 10: 3-5-2 (W-D-L), 1.40 PPG, 1.70 goals scored / 1.30 conceded per match. [^fact-6]: **Value pick #1** — Under in Goals O/U 2.5 — model 54% vs market price 1.95 at bet365, edge 3.1 pp (low confidence). [^fact-7]: **WKR in-form player** — Giorgi Tsitaishvili — 1 goals, 1 assists in last 5 appearances, avg rating 7.34. [^fact-8]: **KAT in-form player** — Eman Markovic — 2 goals, 1 assists in last 5 appearances, avg rating 7.12. [^fact-9]: **WKR key absence** — Piotr Starzyński out (injury), 24 minutes in recent run. [^fact-10]: **KAT key absence** — Rafal Straczek out (injury), 630 minutes in recent run. [^fact-11]: **Markets analysed** — 3 market(s) compared against the model. --- Methodology: . Canonical HTML: .