Liga MXEstadio Hidalgo, Pachuca13°4,1 mm14 km/h

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    PachucaPachucaPossession control
    vs
    Cruz AzulCruz AzulPossession & high press
    The model's lean: 2 · Cruz Azul (47%)

    Pachuca vs Cruz Azul · Liga MX

    1 · Pachuca 25%X 28%47% Cruz Azul · 2

    Prediction summary

    BetBuilders AI model prediction for Pachuca vs Cruz Azul (Liga MX, Thursday, 22 October 2026): Pachuca win 25%, draw 28%, Cruz Azul win 47%. Expected goals (xG): Pachuca 1.27, Cruz Azul 1.67. Most likely score: 1-1 (12%). Over 2.5 goals 56%, both teams to score 59%. Double chance: Pachuca or draw 53%, Cruz Azul or draw 75%. Prediction updated Wednesday, 14 October 2026.

    Bet on this match

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    Analysis: Pachuca – Cruz Azul

    Sofia Andersson · · The model's read on the match · How the predictions work

    Cruz Azul's 47% win probability sets the stage, emphasizing their statistical edge. The visitors' tenacious high press contrasts with Pachuca's possession-centric style, creating a tactical clash. A small sample of head-to-head encounters since 2023 reveals Cruz Azul's dominance, winning three of four meetings. This pattern aligns with their superior expected goals and points metrics, reinforcing the model's preference for the visitors.

    The expected goals tally of 1.67 for Cruz Azul against Pachuca’s 1.27 signals a likely advantage in the attacking department, despite the rain-soaked forecast potentially dampening goal-scoring opportunities. Yet, with a 56% probability for over 2.5 goals and a 59% likelihood of both teams scoring, the numbers still lean towards a relatively open contest. The most probable scorelines of 1-1 and 1-2 subtly underscore a narrow win for Cruz Azul.

    The sharpest angle here is the value on Cruz Azul winning, with a 6% edge at odds of 2.25 with LeoVegas, marking the visitors as a worthwhile punt. Both Betsafe and Nordicbet offer slightly lower value at odds of 2.22, yet remain solid options for an outcome the model finds favorable.

    PachucaPachuca
    Form WDLDL
    League ranking xG #13xGA #17xT #4xP/match #17Points #14
    Key players
    • Salomon RondonFxG 0.61 · xT 0.02
    • Oussama IdrissiLWxG 0.10 · xT 0.26
    • Eduardo BauermannCBxG 0.10 · xT 0.04
    Cruz AzulCruz Azul
    Form WLDDW
    League ranking xG #3xGA #6xT #1xP/match #6Points #5
    Key players
    • Carlos RodriguezCAMxG 0.09 · xT 0.31
    • Jesus Orozco ChiqueteCBxG 0.07 · xT 0.12
    • Erik LiraCDMxG 0.03 · xT 0.12

    Match prediction: Pachuca – Cruz Azul

    Predicted score matrix

    Cruz Azul →
    Pachuca →
    0
    1
    2
    3
    4+
    0
    0–05.6%
    0–18.5%
    0–27.4%
    0–34.1%
    0–4+2.5%
    1
    1–06.4%
    1–111.6%
    1–29.4%
    1–35.2%
    1–4+3.1%
    2
    2–04.3%
    2–17.1%
    2–25.9%
    2–33.3%
    2–4+2.0%
    3
    3–01.8%
    3–13.0%
    3–22.5%
    3–31.4%
    3–4+0.8%
    4+
    4+–00.8%
    4+–11.3%
    4+–21.1%
    4+–30.6%
    4+–4+0.4%
    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. 4.0-27%
    5. 5.2-17%
    Expected goals
    1,27–1,67
    Both teams to score
    59%

    Over/under goals

    Expected goals: 2,9
    Under 2,544%
    @2.35EV+2%
    Over 2,556%
    @1.63

    Ready-made bet suggestions

    More combos & build your own →

    01 · 2 legs

    Safe

    • Cruz Azul to win47%
    • Over 1.5 goals79%

    Combined probability

    38%

    Fair odds

    2.65

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

    02 · 3 legs

    Balanced

    • Cruz Azul to win47%
    • Over 2.5 goals56%
    • Luka Romero Bezzana to score22%

    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 score59%
    • Over 2.5 goals56%
    • José Salomón Rondón Giménez to score24%
    • Christian Hernando Rivera Cuéllar to be booked24%

    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 · Cruz Azul47% probability@2.50BetMGM UKEV+18%reference odds
    • Under 3.566% probability@1.57LeoVegasEV+4%reference odds
    • 2 · Cruz Azul47% probability@2.19PinnacleEV+4%reference odds
    Bookmaker1 · PachucaX2 · Cruz Azul
    BetMGM UK2.503.40
    EV+ 18%
    2.50
    Betsafe3.153.45
    EV+ 0%
    2.12
    LeoVegas3.003.60
    EV+ 0%
    2.12
    Nordicbet3.153.45
    EV+ 0%
    2.12
    Pinnacle3.25
    EV+ 1%
    3.65
    EV+ 4%
    2.19

    Odds updated 22 Oct, 06:10

    Odds movement

    1+9 %
    33 %28 %

    2.97 → 3.25

    X0 %
    28 %23 %

    3.66 → 3.65

    2-3 %
    45 %40 %

    2.25 → 2.19

    Pinnacle · 13 recorded price levels · 20/10/2026 → 22/10/2026 · fixed scale 5 percentage points

    Statistics

    Head-to-head

    4 matches
    Pachuca 1Draw 0Cruz Azul 3
    Goals: 5–8 (⌀ 3,2)

    Head-to-head based on Liga MX data since 2023.

    xG & xGA per match — 3-game rolling average

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

    Pachuca
    Cruz Azul
    When goals are scored and conceded — 2026
    Pachuca (19–16)
    Cruz Azul (27–21)
    Pass networks

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

    Pachuca
    Christian Rivera: 238 passningar, xT 0.26RiveraSergio Barreto: 190 passningar, xT 0.6BarretoEduardo Bauermann: 185 passningar, xT 0.24BauermannFrancisco Venegas: 141 passningar, xT 0.47VenegasOussama Idrissi: 127 passningar, xT 0.75IdrissiRodolfo Pizarro: 126 passningar, xT 0.62PizarroCarlos Moreno: 113 passningar, xT 0.22MorenoAlan Bautista: 106 passningar, xT 0.84BautistaSergio Lenin Rodríguez Rodelas: 80 passningar, xT 0.03RodelasCarlos Sanchez: 77 passningar, xT 0.22SanchezSebastian Santos: 65 passningar, xT 0.09Santos
    Cruz Azul
    Erik Lira: 211 passningar, xT 0.37LiraCarlos Rodriguez: 209 passningar, xT 0.86RodriguezAgustin Palavecino: 177 passningar, xT 1.24PalavecinoGonzalo Piovi: 167 passningar, xT 0.39PioviWiller Ditta: 159 passningar, xT 0.33DittaOmar Campos: 128 passningar, xT 0.71CamposJeremy Marquez: 104 passningar, xT 0.4MarquezJesus Orozco Chiquete: 96 passningar, xT 0.26ChiqueteKevin Mier: 84 passningar, xT 0.05MierAlan Mozo: 74 passningar, xT 0.2MozoAmaury Garcia: 71 passningar, xT 0.07Garcia
    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.

    Pachuca
    Christian Rivera: 238 passningar, xT 0.26RiveraSergio Barreto: 190 passningar, xT 0.6BarretoEduardo Bauermann: 185 passningar, xT 0.24BauermannFrancisco Venegas: 141 passningar, xT 0.47VenegasOussama Idrissi: 127 passningar, xT 0.75IdrissiRodolfo Pizarro: 126 passningar, xT 0.62PizarroCarlos Moreno: 113 passningar, xT 0.22MorenoAlan Bautista: 106 passningar, xT 0.84BautistaSergio Lenin Rodríguez Rodelas: 80 passningar, xT 0.03RodelasCarlos Sanchez: 77 passningar, xT 0.22SanchezSebastian Santos: 65 passningar, xT 0.09Santos
    Cruz Azul
    Erik Lira: 211 passningar, xT 0.37LiraCarlos Rodriguez: 209 passningar, xT 0.86RodriguezAgustin Palavecino: 177 passningar, xT 1.24PalavecinoGonzalo Piovi: 167 passningar, xT 0.39PioviWiller Ditta: 159 passningar, xT 0.33DittaOmar Campos: 128 passningar, xT 0.71CamposJeremy Marquez: 104 passningar, xT 0.4MarquezJesus Orozco Chiquete: 96 passningar, xT 0.26ChiqueteKevin Mier: 84 passningar, xT 0.05MierAlan Mozo: 74 passningar, xT 0.2MozoAmaury Garcia: 71 passningar, xT 0.07Garcia

    The teams in numbers

    PerformancePachucaCruz Azul
    Points1320
    xPoints13.117.6
    xG per match1.31.8
    xGA per match1.71.3
    xG within 8s of winning the ball0.30.28
    xGA within 8s of losing the ball0.140.36
    Playing stylePachucaCruz Azul
    Build-up efficiency0.320.32
    Field tilt0.510.63
    xT per match1.31.6
    xTA per match10.92
    Won balls, offensive half2727
    Pressing intensity0.230.22
    Pressing efficiency0.260.28
    Pressing efficiency, offensive half0.210.24
    Entries into the box per match1317
    Entries into the box against1210
    Pass completion %0.750.78
    Pass completion % under pressure0.720.72
    Passes per match325407
    Passes against per match370296
    Switches of play per match33.436.7
    Long balls per match4640
    Set piecesPachucaCruz Azul
    xG from free kicks0.10.02
    Corners per match5.35.8
    Corners against per match4.25.4
    xG per corner0.030.03
    xGA per corner against0.010.03
    First touch, offensive corners %0.530.4
    First touch, defensive corners %0.570.38
    OtherPachucaCruz Azul
    Throw-in control0.680.75
    The goalkeepersCarlos Moreno (Pachuca)Kevin Mier (Cruz Azul)
    Saves3929
    Save %71%66%
    xG prevented33%45%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Pachuca vs Cruz Azul according to our model?

    The model gives Cruz Azul a 47% win probability. Full 1X2 picture: Pachuca 25%, draw 28%, Cruz Azul 47%.

    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 56% and under at 44%.

    Will both teams score?

    The probability of both teams scoring is 59% according to the model.

    How many goals are expected in Pachuca vs Cruz Azul?

    The model expects 1.27 goals (xG) for Pachuca and 1.67 for Cruz Azul, 2.94 in total.

    What does the model say about double chance?

    Pachuca or draw (1X) 53%, Cruz Azul or draw (X2) 75% and no draw (12) 72%.

    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.