Segunda División23°19 km/h

    Läs på svenska
    MallorcaMallorcaPossession & high press
    vs
    SabadellSabadellPossession control
    The model's lean: 1 · Mallorca (62%)
    Limited dataThe model has few previous matches with these teams in this league — the forecast therefore rests on thinner data than usual.

    MallorcaSabadell · Segunda División

    1 · Mallorca 62%X 22%15% Sabadell · 2

    Analysis: MallorcaSabadell

    Erik Lindberg · · Written from the model's numbers · How the predictions work

    Mallorca's defensive solidity has been a cornerstone of their game, underscored by an impressive xGA of 0.76 per match. This setup will likely be crucial against Sabadell, who come in with the momentum of an xG of 1.8 per game. Despite Sabadell's apparent offensive edge, the hosts' ability to stifle opponents can't be ignored. The expected goals suggest a closely contested affair where Mallorca's defense might just nullify Sabadell’s attacking prowess.

    For the home side, the model suggests a 62% probability of victory, supported by solid defensive numbers and a possession style that could choke Sabadell's opportunities. With their high press, Mallorca will aim to control the game and frustrate their opponents into submission. The most probable scoreline of 1-0 highlights a match that will likely hinge on defensive and tactical discipline.

    Interestingly, Sabadell has managed to collect more points so far, with eight compared to Mallorca's seven, and boasts a better xPoints tally at 8.8 versus 5.2. Yet, it's essential to weigh Mallorca's home advantage and defensive metrics more heavily here, especially given the small head-to-head sample between these teams.

    The over/under 2.5 goals market leans towards the underside with just a 42% probability for over, aligning with the model's expectation of a low-scoring encounter. Given Mallorca’s defensive strengths and Sabadell’s controlled style, the likelihood of a goal-fest is minimal.

    In terms of betting angles, the real value lies with the home side. Betsafe, Betsson, and Nordicbet all offer odds of 1.65 for a Mallorca win, providing a 3% edge over the model's 62% probability. For those seeking a prudent play, backing Mallorca to secure a narrow victory is a bet firmly rooted in the numbers.

    MallorcaMallorca
    Form WLWD
    League ranking xG #13xGA #5xT #8xP/match #14Points #7
    Key players
    • Martin ValjentCBxG 0.00 · xT 0.07
    • Toni LatoLBxG 0.01 · xT 0.15
    • Antonio RailloCBxG 0.07 · xT 0.09
    SabadellSabadell
    Form DDWW
    League ranking xG #2xGA #7xT #18xP/match #1Points #3
    Key players
    • Quadri LiameedFxG 0.08 · xT 0.16
    • Nicholas Selson GioacchiniFxG 0.89 · xT 0.09
    • Joel Priego BorregoFxG 0.20 · xT 0.07

    Match prediction: MallorcaSabadell

    Predicted score matrix

    Sabadell
    Mallorca
    0
    1
    2
    3
    4+
    0
    0–09.8%
    0–16.4%
    0–22.4%
    0–30.6%
    0–4+0.1%
    1
    1–015.2%
    1–111.4%
    1–24.0%
    1–30.9%
    1–4+0.2%
    2
    2–012.8%
    2–19.1%
    2–23.3%
    2–30.8%
    2–4+0.2%
    3
    3–07.0%
    3–15.0%
    3–21.8%
    3–30.4%
    3–4+0.1%
    4+
    4+–04.2%
    4+–13.0%
    4+–21.1%
    4+–30.3%
    4+–4+0.1%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-015%
    2. 2.2-013%
    3. 3.1-111%
    4. 4.0-010%
    5. 5.2-19%
    Expected goals
    1,640,71
    Both teams to score
    41%

    Over/under goals

    Expected goals: 2,4
    Under 2,558%
    @1.66
    Over 2,542%
    @2.40EV+1%

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Mallorca to win62%
    • Under 3.5 goals79%

    Combined probability

    44%

    Fair odds

    2.27

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

    02 · 3 legs

    Balanced

    • Mallorca to win62%
    • Under 2.5 goals58%
    • Vedat Muriqi to score34%

    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 score41%
    • Over 2.5 goals42%
    • Vedat Muriqi to score34%
    • Albert Orriols Cerarols 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+).

    • 1 · Mallorca62% probability@1.80Bet365EV+12%reference odds
    • 1 · Mallorca62% probability@1.70PinnacleEV+6%reference odds
    • 1 · Mallorca62% probability@1.70BetsafeEV+6%reference odds
    Bookmaker1 · MallorcaX2 · Sabadell
    Bet365
    EV+ 12%
    1.80
    3.204.50
    Betsafe
    EV+ 6%
    1.70
    3.354.80
    Betsson
    EV+ 6%
    1.70
    3.354.80
    Nordicbet
    EV+ 6%
    1.70
    3.354.80
    Pinnacle
    EV+ 6%
    1.70
    3.675.04

    Odds updated 11 Sept, 16:34

    Odds movement

    1+2 %
    58 %53 %

    1.671.70

    X0 %
    29 %24 %

    3.663.67

    2-6 %
    21 %16 %

    5.365.04

    Over 2,5+2 %
    45 %40 %

    2.192.23

    Pinnacle · 5 recorded price levels · 08/09/2026 → 11/09/2026 · fixed scale 5 percentage points

    Statistics

    xG & xGA per match — 3-game rolling average

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

    Mallorca
    Sabadell
    When goals are scored and conceded 2026
    Mallorca (52)
    Sabadell (42)
    Pass networks

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

    Mallorca
    Antonio Raillo: 290 passningar, xT 0.35RailloMartin Valjent: 247 passningar, xT 0.26ValjentManu Morlanes: 180 passningar, xT 0.24MorlanesToni Lato: 171 passningar, xT 0.53LatoMiguel Calatayud García: 128 passningar, xT 0.33GarcíaPablo Torre: 126 passningar, xT -0.04TorreÁlex Sala Herrero: 116 passningar, xT 0.19HerreroArnau Tenas Ureña: 112 passningar, xT 0.19UreñaSergi Darder: 88 passningar, xT 0.05DarderZito André Sebastião Luvumbo: 33 passningar, xT 0.09LuvumboAntoniu Roca Vives: 27 passningar, xT 0.04Vives
    Sabadell
    Albert Orriols Cerarols: 122 passningar, xT 0.33CerarolsÓscar Sanz Naval: 98 passningar, xT 0.21NavalArthur Renan Bonaldo: 73 passningar, xT 0.06BonaldoQuadri Liameed: 70 passningar, xT 0.41LiameedEdgar González Estrada: 64 passningar, xT 0.05EstradaDiego Licinio Lázaro Fuoli: 61 passningar, xT 0.21FuoliGastón Andrés Lodico: 61 passningar, xT 0.52LodicoPere Pons Riera: 54 passningar, xT -0.02RieraMiquel Codina Sayol: 53 passningar, xT -0.01SayolJoel Priego Borrego: 48 passningar, xT 0.25BorregoJosé Luis Català Vázquez: 27 passningar, xT 0.05Vázquez
    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.

    Mallorca
    Antonio Raillo: 290 passningar, xT 0.35RailloMartin Valjent: 247 passningar, xT 0.26ValjentManu Morlanes: 180 passningar, xT 0.24MorlanesToni Lato: 171 passningar, xT 0.53LatoMiguel Calatayud García: 128 passningar, xT 0.33GarcíaPablo Torre: 126 passningar, xT -0.04TorreÁlex Sala Herrero: 116 passningar, xT 0.19HerreroArnau Tenas Ureña: 112 passningar, xT 0.19UreñaSergi Darder: 88 passningar, xT 0.05DarderZito André Sebastião Luvumbo: 33 passningar, xT 0.09LuvumboAntoniu Roca Vives: 27 passningar, xT 0.04Vives
    Sabadell
    Albert Orriols Cerarols: 122 passningar, xT 0.33CerarolsÓscar Sanz Naval: 98 passningar, xT 0.21NavalArthur Renan Bonaldo: 73 passningar, xT 0.06BonaldoQuadri Liameed: 70 passningar, xT 0.41LiameedEdgar González Estrada: 64 passningar, xT 0.05EstradaDiego Licinio Lázaro Fuoli: 61 passningar, xT 0.21FuoliGastón Andrés Lodico: 61 passningar, xT 0.52LodicoPere Pons Riera: 54 passningar, xT -0.02RieraMiquel Codina Sayol: 53 passningar, xT -0.01SayolJoel Priego Borrego: 48 passningar, xT 0.25BorregoJosé Luis Català Vázquez: 27 passningar, xT 0.05Vázquez

    The teams in numbers

    PerformanceMallorcaSabadell
    Points78
    xPoints5.28.8
    xG per match0.961.8
    xGA per match0.760.9
    xG within 8s of winning the ball0.350.28
    xGA within 8s of losing the ball0.090.17
    Playing styleMallorcaSabadell
    Build-up efficiency0.30.36
    Field tilt0.630.41
    xT per match0.80.68
    xTA per match0.610.93
    Won balls, offensive half2430
    Pressing intensity0.230.21
    Pressing efficiency0.30.31
    Pressing efficiency, offensive half0.260.3
    Entries into the box per match1111
    Entries into the box against79
    Pass completion %0.820.59
    Pass completion % under pressure0.750.53
    Passes per match416198
    Passes against per match330388
    Switches of play per match18.112.8
    Long balls per match2622
    Set piecesMallorcaSabadell
    xG from free kicks0.020
    Corners per match3.84.4
    Corners against per match4.33.2
    xG per corner0.040.04
    xGA per corner against0.040
    First touch, offensive corners %0.330.39
    First touch, defensive corners %0.590.69
    OtherMallorcaSabadell
    Throw-in control0.630.64
    The goalkeepersArnau Tenas Ureña (Mallorca)Diego Licinio Lázaro Fuoli (Sabadell)
    Saves1010
    Save %91%83%
    xG prevented73%52%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Mallorca vs Sabadell according to our model?

    The model gives Mallorca a 62% win probability. Full 1X2 picture: Mallorca 62%, draw 22%, Sabadell 15%.

    What is the most likely scoreline?

    The model's most likely final score is 1-0 at 15% probability.

    Over or under 2.5 goals?

    The model rates over 2.5 goals at 42% and under at 58%.

    Will both teams score?

    The probability of both teams scoring is 41% 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.

    More matches in the league

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