EFL League TwoPeninsula Stadium, Salford16°0,2 mm18 km/h

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    Salford CitySalford CityPossession control
    21
    Newport CountyNewport CountyLow block & direct
    The model's lean: 1 · Salford City (57%)Best value by the model: 2 · Newport County @ 5.86 (+16 %)

    Salford CityNewport County · EFL League Two

    1 · Salford City 57%X 24%20% Newport County · 2

    Analysis: Salford CityNewport County

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

    Salford City's recent form is a glaring concern as they host Newport County, with the home side grappling with a four-match losing streak. Despite their control-oriented style, they've been unable to convert possession into results. The probabilities favor Salford with a 57% chance of victory, but their recent slump casts a shadow over this prediction. Most likely scorelines are tight, with both 1-1 and 1-0 outcomes given an 11% chance each.

    Newport County, on the other hand, have shown a slight edge in head-to-head encounters since 2023, albeit from a small sample of four matches. They've earned four points to Salford's zero, a clear indication of their ability to disrupt the hosts' rhythm. Their direct, defensive approach has yielded better xG (1.3) compared to Salford's meager 0.84 per match. Yet, both sides show vulnerabilities at the back, with Newport slightly better in terms of expected goals against (xGA).

    The expected goals for this match project Salford at 1.76 and Newport at 0.95, suggesting a tighter game than the model probabilities might imply. The hosts are more likely to score, yet Newport's resilience can't be overlooked. Given this, a cagey affair with a 1-0 scoreline seems probable, although a 1-1 draw isn't far off.

    The over/under 2.5 goals and both teams to score markets sit evenly at 51%, reflecting the tight nature of this matchup. While goals might be scarce, the odds for a Newport win at 5.4 with Betsafe, Betsson, and Nordicbet present a tantalizing value bet, showing a 7% edge over the model's rating of a 20% chance for the visitors. For those willing to stake on Salford's ongoing struggles, this option offers potential reward amidst the uncertainties.

    Salford CitySalford City
    Form DLLLL
    League ranking xG #20xGA #20xT #20xP/match #24Points #23
    Key players
    • Adebola OluwoCBxG 0.16 · xT 0.08
    • Joe James PowellCAMxG 0.05 · xT 0.09
    • William Stewart AimsonCBxG 0.06 · xT 0.08
    Newport CountyNewport County
    Form WWWLD
    League ranking xG #14xGA #14xT #12xP/match #8Points #14
    Key players
    • Ciaran BrennanFxG 0.05 · xT 0.05
    • Shaquille GwengweLWxG 0.33 · xT 0.04
    • Harrison BigginsCAMxG 0.10 · xT 0.24
    Final score
    21
    The model called the outcome
    Predicted probabilities: Salford City 57% · Draw 24% · Newport County 20%

    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 - Newport CountyBåda lagen gör mål - JaTotalt antal mål - Över 3.5
    odds 16,37fair 23,47-30 %
    Miss
    Matchresultat - Salford City FCBåda lagen gör mål - JaTotalt antal mål - Över 3.5
    odds 4,49fair 6,90-35 %
    Miss

    Match prediction: Salford CityNewport County

    Predicted score matrix

    Newport County
    Salford City
    0
    1
    2
    3
    4+
    0
    0–07.0%
    0–16.0%
    0–23.0%
    0–30.9%
    0–4+0.3%
    1
    1–011.5%
    1–111.5%
    1–25.3%
    1–31.7%
    1–4+0.5%
    2
    2–010.4%
    2–19.8%
    2–24.6%
    2–31.5%
    2–4+0.4%
    3
    3–06.1%
    3–15.7%
    3–22.7%
    3–30.9%
    3–4+0.2%
    4+
    4+–04.0%
    4+–13.7%
    4+–21.8%
    4+–30.6%
    4+–4+0.2%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-111%
    2. 2.1-011%
    3. 3.2-010%
    4. 4.2-110%
    5. 5.0-07%
    Expected goals
    1,760,95
    Both teams to score
    51%

    Over/under goals

    Expected goals: 2,7
    Under 2,549%
    @2.22EV+10%
    Over 2,551%
    @1.60

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Salford City to win57%
    • Over 1.5 goals75%

    Combined probability

    45%

    Fair odds

    2.24

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

    02 · 3 legs

    Balanced

    • Salford City to win57%
    • Over 2.5 goals51%
    • Dominic Daniel Udoh to score36%

    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 score51%
    • Over 2.5 goals51%
    • Dominic Daniel Udoh to score36%
    • Matthew Baker 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 · Newport County20% probability@5.86PinnacleEV+16%reference odds
    • Under 2.549% probability@2.22BetsafeEV+10%reference odds
    • Under 2.549% probability@2.22BetssonEV+10%reference odds
    Bookmaker1 · Salford CityX2 · Newport County
    Betsafe1.583.85
    EV+ 7%
    5.40
    Betsson1.583.85
    EV+ 7%
    5.40
    Nordicbet1.583.85
    EV+ 7%
    5.40
    Pinnacle1.52
    EV+ 4%
    4.43
    EV+ 16%
    5.86

    Odds updated 1 Sept, 11:35

    Odds movement

    1-1 %
    64 %59 %

    1.541.52

    X+7 %
    24 %19 %

    4.154.43

    2+6 %
    19 %14 %

    5.535.86

    Pinnacle · 8 recorded price levels · 30/08/2026 → 01/09/2026 · fixed scale 5 percentage points

    Statistics

    Head-to-head

    4 matches
    Salford City 1Draw 1Newport County 2
    Goals: 47 (⌀ 2,8)

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

    Key facts

    • Salford City have lost 4 in a row.
    xG & xGA per match — 3-game rolling average

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

    Salford City
    Newport County
    When goals are scored and conceded 2026
    Salford City (15)
    Newport County (87)
    Pass networks

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

    Salford City
    Adebola Oluwo: 172 passningar, xT 0.24OluwoWilliam Stewart Aimson: 169 passningar, xT 0.25AimsonWilliam James Norris: 107 passningar, xT 0.11NorrisJoe James Powell: 87 passningar, xT 0.19PowellOliver Anthony Turton: 87 passningar, xT 0.27TurtonJorge Edward Grant: 79 passningar, xT -0.01GrantLuke Garbutt: 77 passningar, xT 0.03GarbuttLuke James Molyneux: 62 passningar, xT 0.28MolyneuxBrendan Nana Akwasi Sarpong Wiredu: 47 passningar, xT 0.01WireduElliot Bonds: 40 passningar, xT 0.21BondsBen Woodburn: 31 passningar, xT 0.07Woodburn
    Newport County
    Harrison Biggins: 54 passningar, xT 0.71BigginsJordan Wright: 45 passningar, xT 0.15WrightCameron Pearce Norman: 44 passningar, xT 0.48NormanCiaran Brennan: 38 passningar, xT 0.15BrennanKyle Milne Cameron: 36 passningar, xT 0.08CameronLee Thomas Jenkins: 31 passningar, xT 0.04JenkinsCameron Evans: 27 passningar, xT 0.06EvansThomas Alfred Davies: 27 passningar, xT 0.06DaviesDaniel Sassi: 16 passningar, xT -0.01SassiYahaya Abdoul Bamba: 13 passningar, xT 0.25BambaAlfie Merritt: 12 passningar, xT 0.13Merritt
    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.

    Salford City
    Adebola Oluwo: 172 passningar, xT 0.24OluwoWilliam Stewart Aimson: 169 passningar, xT 0.25AimsonWilliam James Norris: 107 passningar, xT 0.11NorrisJoe James Powell: 87 passningar, xT 0.19PowellOliver Anthony Turton: 87 passningar, xT 0.27TurtonJorge Edward Grant: 79 passningar, xT -0.01GrantLuke Garbutt: 77 passningar, xT 0.03GarbuttLuke James Molyneux: 62 passningar, xT 0.28MolyneuxBrendan Nana Akwasi Sarpong Wiredu: 47 passningar, xT 0.01WireduElliot Bonds: 40 passningar, xT 0.21BondsBen Woodburn: 31 passningar, xT 0.07Woodburn
    Newport County
    Harrison Biggins: 54 passningar, xT 0.71BigginsJordan Wright: 45 passningar, xT 0.15WrightCameron Pearce Norman: 44 passningar, xT 0.48NormanCiaran Brennan: 38 passningar, xT 0.15BrennanKyle Milne Cameron: 36 passningar, xT 0.08CameronLee Thomas Jenkins: 31 passningar, xT 0.04JenkinsCameron Evans: 27 passningar, xT 0.06EvansThomas Alfred Davies: 27 passningar, xT 0.06DaviesDaniel Sassi: 16 passningar, xT -0.01SassiYahaya Abdoul Bamba: 13 passningar, xT 0.25BambaAlfie Merritt: 12 passningar, xT 0.13Merritt

    The teams in numbers

    PerformanceSalford CityNewport County
    Points04
    xPoints1.94.8
    xG per match0.841.3
    xGA per match1.71.5
    xG within 8s of winning the ball0.150.13
    xGA within 8s of losing the ball0.740.41
    Playing styleSalford CityNewport County
    Build-up efficiency0.370.33
    Field tilt0.590.38
    xT per match0.60.85
    xTA per match0.720.94
    Won balls, offensive half2130
    Pressing intensity0.250.23
    Pressing efficiency0.440.33
    Pressing efficiency, offensive half0.480.32
    Entries into the box per match1412
    Entries into the box against1316
    Pass completion %0.750.48
    Pass completion % under pressure0.680.51
    Passes per match382126
    Passes against per match201306
    Switches of play per match29.413.8
    Long balls per match3732
    Set piecesSalford CityNewport County
    xG from free kicks0.130.21
    Corners per match4.34.7
    Corners against per match47.7
    xG per corner0.010.05
    xGA per corner against0.020.01
    First touch, offensive corners %0.460.29
    First touch, defensive corners %0.670.74
    OtherSalford CityNewport County
    Throw-in control0.80.76
    The goalkeepersWilliam James Norris (Salford City)Jordan Wright (Newport County)
    Saves77
    Save %58%54%
    xG prevented28%22%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Salford City vs Newport County according to our model?

    The model gives Salford City a 57% win probability. Full 1X2 picture: Salford City 57%, draw 24%, Newport County 20%.

    What is the most likely scoreline?

    The model's most likely final score is 1-1 at 11% probability.

    Over or under 2.5 goals?

    The model rates over 2.5 goals at 51% and under at 49%.

    Will both teams score?

    The probability of both teams scoring is 51% 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.