Conference League

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    Győri ETOGyőri ETOBalanced & physical
    11
    Riga FCRiga FCPossession control
    The model's lean: 2 · Riga FC (48%)

    Győri ETO vs Riga FC · Conference League

    1 · Győri ETO 30%X 22%48% Riga FC · 2

    Analysis: Győri ETORiga FC

    Oscar Nilsson · · Model-assisted analysis, fact-checked · How the predictions work

    Riga FC's possession-centric style meets Gyori ETO's balanced approach in a clash that sees the visitors favored, albeit without overwhelming dominance. With a 48% chance of victory according to the model, Riga FC has the upper hand. The last and only head-to-head encounter saw Riga FC secure a win, but with just one match in this sample, its significance is limited. Instead, current form and expected goals should steer our expectations.

    Despite Gyori ETO's slight edge in points and xPoints, Riga FC's resilience in defense stands out. Their xGA per match sits at a stingy 0.08, indicating a well-drilled backline that could thwart Gyori's attempts to break through. Gyori ETO, however, remains competitive, with a nearly balanced xG per match of 1.4.

    Riga FC might dominate possession, yet Gyori ETO's physicality could disrupt their rhythm. The expected goals paint a picture of a closely fought contest — 1.27 for Gyori and 1.55 for Riga. The probabilities suggest a narrow Riga victory, with 1-2 or 0-1 as plausible outcomes. With a 54% chance of over 2.5 goals, there's a hint of an open game, but caution prevails due to the strength of Riga’s defense.

    Gyori ETO may find some solace in their home advantage, but Riga FC's odds of 2.82 with Betsafe, Betsson, and Nordicbet, present exceptional value for those siding with the model's 48% prediction. This 36% edge positions Riga as an intriguing pick for bettors with an eye for value. As the match unfolds, the calculated edge and disciplined structure of Riga FC might just tip the scales in their favor.

    Győri ETOGyőri ETO
    Form WLWDL
    League ranking xG #20xGA #12xT #22xP/match #16Points #12
    Key players
    • Nfansu NjieFxG 0.22 · xT 0.06
    • Daniel StefuljLBxG 0.06 · xT 0.27
    • Milan VitalisCMxG 0.18 · xT -0.01
    Riga FCRiga FC
    Form LWLLW
    League ranking xG #16xGA #1xT #21xP/match #3Points #15
    Final score
    11
    The model missed the outcome
    Predicted probabilities: Győri ETO 30% · Draw 22% · Riga FC 48%

    How the bookmaker bet builders went

    The verdict on the pre-built bet builders for this match, priced against the model’s score matrix before kickoff. Graded on the 90-minute result.

    Matchresultat - Riga FCBåda lagen gör mål - JaTotalt antal mål - Över 3.5
    odds 8,11fair 7,94+2 %
    Miss
    Matchresultat - Győri ETOBåda lagen gör mål - JaTotalt antal mål - Över 3.5
    odds 7,19fair 11,86-39 %
    Miss

    Match prediction: Győri ETORiga FC

    Predicted score matrix

    Riga FC
    Győri ETO
    0
    1
    2
    3
    4+
    0
    0–06.3%
    0–18.9%
    0–27.2%
    0–33.7%
    0–4+2.0%
    1
    1–07.2%
    1–112.1%
    1–29.1%
    1–34.7%
    1–4+2.6%
    2
    2–04.8%
    2–17.4%
    2–25.8%
    2–33.0%
    2–4+1.6%
    3
    3–02.0%
    3–13.1%
    3–22.4%
    3–31.3%
    3–4+0.7%
    4+
    4+–00.8%
    4+–11.3%
    4+–21.0%
    4+–30.5%
    4+–4+0.3%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-112%
    2. 2.1-29%
    3. 3.0-19%
    4. 4.2-17%
    5. 5.1-07%
    Expected goals
    1,271,55
    Both teams to score
    57%

    Over/under goals

    Expected goals: 2,8
    Under 2,546%
    @1.99
    Over 2,554%
    @1.76

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Riga FC to win48%
    • Over 1.5 goals78%

    Combined probability

    35%

    Fair odds

    2.89

    Two legs pulling the same way — the probability is computed exactly from the score matrix, not multiplied.

    02 · 3 legs

    Balanced

    • Riga FC to win48%
    • Over 2.5 goals54%
    • Muhammed Cray Badamosi to score26%

    Combined probability

    Fair odds

    The whole slip is priced jointly via 20,000 simulated matches — the scorer interacts with result and total goals, never naive multiplication.

    03 · 4 legs

    Bold

    • Both teams to score57%
    • Over 2.5 goals54%
    • Muhammed Cray Badamosi to score26%
    • Karl Gameni Wassom to be booked21%

    Combined probability

    Fair odds

    The goal-fest: both teams score with at least three goals, plus the match's most likely scorer and card candidate — all priced jointly via 20,000 simulated matches.

    Odds & value

    The model's value spots

    Bets where the model's probability beats what the odds imply (EV+).

    • 2 · Riga FC48% probability@2.96PinnacleEV+43%reference odds
    • 2 · Riga FC48% probability@2.82BetsafeEV+36%reference odds
    • 2 · Riga FC48% probability@2.82BetssonEV+36%reference odds
    Bookmaker1 · Győri ETOX2 · Riga FC
    Betsafe2.223.50
    EV+ 36%
    2.82
    Betsson2.223.50
    EV+ 36%
    2.82
    Nordicbet2.223.50
    EV+ 36%
    2.82
    Pinnacle2.213.28
    EV+ 43%
    2.96

    Odds updated 13 Aug, 11:35

    Odds movement

    1+1 %
    43 %38 %

    2.182.21

    X+1 %
    31 %26 %

    3.263.28

    2-2 %
    34 %29 %

    3.032.96

    Over 2,50 %
    56 %51 %

    1.761.76

    Pinnacle · 6 recorded price levels · 09/08/2026 → 12/08/2026 · fixed scale 5 percentage points

    Statistics

    Head-to-head

    1 matches
    Győri ETO 0Draw 0Riga FC 1
    Goals: 01 (⌀ 1)

    Head-to-head based on Conference League data since 2023.

    xG & xGA per match — 3-game rolling average

    Solid line = created (xG), dashed = conceded (xGA).

    Győri ETO
    Riga FC
    When goals are scored and conceded 2026
    Győri ETO (74)
    Riga FC (10)
    Pass networks

    Last 5 matches. Circle size = pass volume, line width = combinations between players. Attacking left to right.

    Győri ETO
    Miljan Krpić: 206 passningar, xT 0.38KrpićÁdám Umathum: 157 passningar, xT 0.24UmathumDaniel Stefulj: 108 passningar, xT 0.52StefuljAdam Decsy: 79 passningar, xT 0.04DecsySzabolcs Gergő Schön: 77 passningar, xT 0.02SchönBarnabas Biro: 76 passningar, xT 0.24BiroMilan Vitalis: 70 passningar, xT -0.01VitalisSamuel Petras: 55 passningar, xT 0.06PetrasClaudiu Bumba: 52 passningar, xT 0.09BumbaMárton Szép: 47 passningar, xT 0SzépNfansu Njie: 37 passningar, xT 0.08Njie
    Riga FC
    Paulo Eduardo Ferreira Godinho: 76 passningar, xT 0.09GodinhoBaba Musah: 70 passningar, xT 0.05MusahAndrés Salazar Osorio: 63 passningar, xT 0.1OsorioAhmed Ankrah: 50 passningar, xT 0AnkrahRaivis Jurkovskis: 47 passningar, xT 0.09JurkovskisIago Siqueira: 44 passningar, xT 0.15SiqueiraOrlando Galo: 41 passningar, xT 0.05GaloRaki Aouani: 23 passningar, xT 0.17AouaniMeissa Diop: 20 passningar, xT 0.01DiopFrenks Orols: 16 passningar, xT 0.02OrolsReginaldo Ramires: 11 passningar, xT -0.03Ramires
    xT networks

    The same network weighted by offensive threat (xT): circle size = threat created by the player, line width = threat of the combinations. Last 5 matches, attacking left to right.

    Győri ETO
    Miljan Krpić: 206 passningar, xT 0.38KrpićÁdám Umathum: 157 passningar, xT 0.24UmathumDaniel Stefulj: 108 passningar, xT 0.52StefuljAdam Decsy: 79 passningar, xT 0.04DecsySzabolcs Gergő Schön: 77 passningar, xT 0.02SchönBarnabas Biro: 76 passningar, xT 0.24BiroMilan Vitalis: 70 passningar, xT -0.01VitalisSamuel Petras: 55 passningar, xT 0.06PetrasClaudiu Bumba: 52 passningar, xT 0.09BumbaMárton Szép: 47 passningar, xT 0SzépNfansu Njie: 37 passningar, xT 0.08Njie
    Riga FC
    Paulo Eduardo Ferreira Godinho: 76 passningar, xT 0.09GodinhoBaba Musah: 70 passningar, xT 0.05MusahAndrés Salazar Osorio: 63 passningar, xT 0.1OsorioAhmed Ankrah: 50 passningar, xT 0AnkrahRaivis Jurkovskis: 47 passningar, xT 0.09JurkovskisIago Siqueira: 44 passningar, xT 0.15SiqueiraOrlando Galo: 41 passningar, xT 0.05GaloRaki Aouani: 23 passningar, xT 0.17AouaniMeissa Diop: 20 passningar, xT 0.01DiopFrenks Orols: 16 passningar, xT 0.02OrolsReginaldo Ramires: 11 passningar, xT -0.03Ramires

    The teams in numbers

    PerformanceGyőri ETORiga FC
    Points43
    xPoints4.12.3
    xG per match1.41.5
    xGA per match1.30.08
    xG within 8s of winning the ball0.450.2
    xGA within 8s of losing the ball0.220.03
    Playing styleGyőri ETORiga FC
    Build-up efficiency0.330.37
    Field tilt0.490.66
    xT per match0.860.86
    xTA per match0.890.21
    Won balls, offensive half2526
    Pressing intensity0.240.21
    Pressing efficiency0.230.3
    Pressing efficiency, offensive half0.220.23
    Entries into the box per match617
    Entries into the box against145
    Pass completion %0.810.83
    Pass completion % under pressure0.770.71
    Passes per match408480
    Passes against per match443269
    Switches of play per match36.538.1
    Long balls per match3540
    Set piecesGyőri ETORiga FC
    xG from free kicks00.08
    Corners per match2.38
    Corners against per match5.71
    xG per corner0.020.06
    xGA per corner against0.030
    First touch, offensive corners %0.290.57
    First touch, defensive corners %0.561
    OtherGyőri ETORiga FC
    Throw-in control0.720.79
    The goalkeepersSamuel Petras (Győri ETO)Frenks Orols (Riga FC)
    Saves132
    Save %87%100%
    xG prevented85%100%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Győri ETO vs Riga FC according to our model?

    The model gives Riga FC a 48% win probability. Full 1X2 picture: Győri ETO 30%, draw 22%, Riga FC 48%.

    What is the most likely scoreline?

    The model's most likely final score is 1-1 at 12% probability.

    Over or under 2.5 goals?

    The model rates over 2.5 goals at 54% and under at 46%.

    Will both teams score?

    The probability of both teams scoring is 57% according to the model.

    Why are some legs locked in the bet builder?

    The same rules as the bookmakers’ builders: legs that contradict or already follow from your slip cannot be combined — for example correct score 2–1 with under 2.5 goals. The difference is that we don’t look the rules up in a table; we compute them straight from the score matrix.

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    Predictions come from PlaymakerAI's match model and reflect the model's assessment — not betting advice. Gamble responsibly.