Padova vs Carrarese Prediction: Home win 43% (10 Oct 2026)

Serie B10 October 2026Stadio Euganeo, Padova

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PadovaBalanced & physical

CarraresePossession control

The model's lean: 1 · Padova (43%)Best value by the model: 2 · Carrarese @ 3.98 (+20 %)

1 · Padova 43%X 27%30% Carrarese · 2

43%

27%

30%

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Analysis: Padova – Carrarese

Oscar Nilsson · 2 October 2026 · Model-assisted analysis, fact-checked · How the predictions work

TEXT: Carrarese's three-match losing streak casts a shadow on their visit to Padova, who have a balanced and physical approach that might exploit the visitors' recent vulnerabilities. While the head-to-head record since 2023 is a mere two matches, with Padova winning one and drawing the other, it adds a slight psychological edge for the hosts despite being a small sample size.

The expectation of a close contest is underscored by the xG figures: Padova's 0.99 per match slightly outpaces Carrarese's 0.91, hinting at a marginal offensive edge for the home side. However, the xGA numbers reveal a defensive frailty in Padova, conceding 1.8 goals per match compared to Carrarese's 1.4. This defensive gap could be crucial, especially if Carrarese capitalizes on their possession-oriented style to control the game.

The most enticing betting angle here lies in the match outcome probabilities. With Padova favored at 43%, yet Carrarese not far behind at 30%, the visitors might be undervalued. The model's lean towards under 2.5 goals at 53% also suggests a cautious match, likely settling at 1-1.

Padova

Form WDLWL

League ranking xG #16xGA #20xT #9xP/match #20Points #8

Key players

Kevin LasagnaFxG 0.25 · xT 0.15
Pietro FusiLWxG 0.03 · xT 0.13
Marco PompettiRWxG 0.24 · xT 0.02

Carrarese

Form LDLLL

League ranking xG #17xGA #17xT #17xP/match #10Points #20

Key players

Jonas Jakob RouhiLWxG 0.01 · xT 0.14
Fabio AbiusoFxG 0.33 · xT 0.08
Elhadj Moustapha CisseFxG 0.16 · xT 0.04

Match prediction: Padova – Carrarese

Predicted score matrix

Carrarese →

Padova →

0–08.2%

0–18.7%

0–25.3%

0–32.1%

0–4+0.8%

1–010.4%

1–113.0%

1–27.3%

1–32.9%

1–4+1.1%

2–07.5%

2–18.7%

2–25.1%

2–32.0%

2–4+0.7%

3–03.5%

3–14.0%

3–22.3%

3–30.9%

3–4+0.3%

4+–01.6%

4+–11.9%

4+–21.1%

4+–30.4%

4+–4+0.2%

Probability per final score. Rows = home goals, columns = away goals.

Most likely scorelines

1.1-113%
2.1-010%
3.0-19%
4.2-19%
5.0-08%

Expected goals

1,38–1,17

Both teams to score

52%

Over/under goals

Expected goals: 2,5

08%

119%

226%

322%

414%

5+12%

Under 2,553%

@1.92EV+2%

Over 2,547%

@1.93

Ready-made bet suggestions

More combos & build your own →

01 · 2 legs

Safe

Double chance Padova or draw (1X)69%
Under 3.5 goals75%

02 · 3 legs

Balanced

Double chance Padova or draw (1X)69%
Under 2.5 goals53%
Pietro Fusi to score24%

03 · 4 legs

Bold

Both teams to score52%
Over 2.5 goals47%
Pietro Fusi to score24%
Filippo Oliana to be booked21%

Odds & value

The model's value spots

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

2 · Carrarese30% probability@3.98PinnacleEV+20%reference odds
2 · Carrarese30% probability@3.75BetsafeEV+14%reference odds
2 · Carrarese30% probability@3.75NordicbetEV+14%reference odds

Bookmaker	1 · Padova	X	2 · Carrarese
Betsafe	1.92	3.35	EV+ 14% 3.75
Nordicbet	1.92	3.35	EV+ 14% 3.75
Pinnacle	2.01	3.26	EV+ 20% 3.98

Odds updated 2 Oct, 07:36

Statistics

Head-to-head

2 matches

Padova 1Draw 1Carrarese 0

Goals: 1–0 (⌀ 0,5)

Head-to-head based on Serie B data since 2023.

Key facts

Carrarese Calcio 1908 have lost 3 in a row.

xG & xGA per match — 3-game rolling average

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

Padova

Carrarese

When goals are scored and conceded — 2026

Padova (5–6)

Carrarese (2–6)

Pass networks

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

Padova

Carrarese

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.

Padova

Carrarese

The teams in numbers

Performance	Padova	Carrarese
Points	7	1
xPoints	4.7	6.6
xG per match	0.99	0.91
xGA per match	1.8	1.4
xG within 8s of winning the ball	0.28	0.19
xGA within 8s of losing the ball	0.17	0.39

Playing style	Padova	Carrarese
Build-up efficiency	0.29	0.3
Field tilt	0.42	0.28
xT per match	0.98	0.67
xTA per match	1.1	1.4
Won balls, offensive half	26	19
Pressing intensity	0.23	0.23
Pressing efficiency	0.28	0.22
Pressing efficiency, offensive half	0.21	0.17
Entries into the box per match	13	11
Entries into the box against	13	16
Pass completion %	0.74	0.73
Pass completion % under pressure	0.68	0.62
Passes per match	297	287
Passes against per match	424	494
Switches of play per match	22.9	17.5
Long balls per match	31	22

Set pieces	Padova	Carrarese
xG from free kicks	0.01	0.02
Corners per match	5.3	5.6
Corners against per match	5.7	5
xG per corner	0.02	0.07
xGA per corner against	0.04	0.02
First touch, offensive corners %	0.58	0.46
First touch, defensive corners %	0.57	0.56

Other	Padova	Carrarese
Throw-in control	0.72	0.72

The goalkeepers	Alessandro Sorrentino (Padova)	Giovanni Gabriele Garofani (Carrarese)
Saves	22	8
Save %	79%	73%
xG prevented	46%	65%
Claims	0 (0%)	0 (0%)

Teams & more matches this round

Padova

Fixtures, form & tips

Carrarese

Fixtures, form & tips

Frequently asked questions

Who wins Padova vs Carrarese according to our model?

The model gives Padova a 43% win probability. Full 1X2 picture: Padova 43%, draw 27%, Carrarese 30%.

What is the most likely scoreline?

The model's most likely final score is 1-1 at 13% probability.

Over or under 2.5 goals?

The model rates over 2.5 goals at 47% and under at 53%.

Will both teams score?

The probability of both teams scoring is 52% 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.