Pisa vs Modena – Prediction, Odds & Live Stats

	Date	Home	Score	Away	1x2	Drop	Home Asian Handicap	Goal Line	Asian Corners	Dangerous Attacks	Total Shots	Shots on Target	Corners
	05-04-2025 15:15	3 ^[2] Pisa	1 - 2 0 - 1	Modena ^[10] 2	S: - 3.25 ? K: ?3.50 -	11%	? 1.875 ? 2.000	- ?	? 1.975, 1.825	?-? 38-6	14-9 4-2	?-? 1-1	4-1 0-0
	21-12-2024 16:15	^[11] Modena	1 - 0 0 - 0	Pisa ^[2] 4	S: - 3.00 ? K: ?2.88 -	4%	? 1.825 ? 2.125	- ?	? 1.850, 1.950	?-? 16-34	7-15 4-5	?-? 1-0	3-2 3-1
	11-03-2023 13:00	3 ^[12] Modena	1 - 0 1 - 0	Pisa ^[5] 2	S: - 3.25 ? K: ?3.10 -	0%	? 1.875 ? 1.825	- ?	? 1.975, 1.825	?-? 17-31	8-16 6-7	?-? 2-0	3-5 3-3
	23-10-2022 14:15	4 ^[19] Pisa	4 - 2	Modena ^[11] 2	S: - 3.25 ? K: ?3.25 -	14%	? 1.875 ? 1.950	- ?	? 1.925, 1.875	?-?	14-9	?-?	5-5
No games found

- Minutes
{{home}}	{{h_corners}}	{{h_ycards}}	{{h_rcards}}	{{h_pen}}	{{h_sub}}	{{h_goals}}
{{away}}	{{a_corners}}	{{a_ycards}}	{{a_rcards}}	{{a_pen}}	{{a_sub}}	{{a_goals}}

Full-Time	xG							Saves	Shots Blocked	Fouls	Ball Safe
Pisa	0.89	3	2	1	0	0	1	2	1	11	71	2	2
Modena	1.53	6	6	0	0	0	3	2	1	12	56	0	2

1st Half
Pisa	2	1	0	0	0	1
Modena	1	1	0	0	0	0

2nd half
Pisa	1	1	1	0	0	1
Modena	5	5	0	0	2	2

Last 5 minutes
Pisa	1	1	1	0	0	1
Modena	5	5	0	0	0	2

Since Last Goal
Pisa	0	0	0	0	0	0
Modena	0	0	0	0	0	0

P	Team	W	D	L	Goals	PO
1	Palermo	7	1	0	18:8	22
2	Modena	6	1	2	17:9	19
3	Ascoli	5	3	1	16:6	18
4	Mantova	5	2	2	14:10	17
5	Benevento	4	3	2	14:8	15
6	Pisa	4	2	2	15:10	14
7	Sudtirol	3	4	2	10:9	13
8	Padova	4	1	4	9:10	13
9	Avellino	3	3	3	13:10	12
10	Cesena	2	5	2	10:13	11
11	Virtus Entella	2	4	3	11:10	10
12	Arezzo	3	1	4	8:17	10
13	Verona	2	3	3	15:13	9
14	Cremonese	2	3	4	8:11	9
15	Vicenza	2	3	4	12:17	9
16	Juve Stabia	3	3	2	9:8	8
17	Carrarese	2	1	5	7:9	7
18	Empoli	2	1	6	8:15	7
19	Sampdoria	1	2	6	8:18	5
20	Catanzaro	1	2	6	10:21	5

P	Team	W	D	L	Goals	PO
1	Palermo	4	0	0	8:3	12
2	Ascoli	3	2	0	8:3	11
3	Modena	3	0	1	8:4	9
4	Benevento	2	3	1	10:7	9
5	Sudtirol	2	3	0	5:2	9
6	Verona	2	2	1	11:6	8
7	Avellino	2	1	2	9:5	7
8	Cesena	1	4	0	7:6	7
9	Mantova	2	1	2	7:7	7
10	Padova	2	1	2	5:5	7
11	Pisa	2	0	2	6:7	6
12	Juve Stabia	1	1	1	4:4	4
13	Cremonese	1	1	2	3:5	4
14	Vicenza	1	1	2	5:8	4
15	Sampdoria	1	0	2	4:5	3
16	Virtus Entella	0	3	2	5:7	3
17	Carrarese	1	0	3	3:5	3
18	Empoli	1	0	3	3:7	3
19	Catanzaro	1	0	2	3:9	3
20	Arezzo	0	1	3	3:10	1

P	Team	W	D	L	Goals	PO
1	Palermo	3	1	0	10:5	10
2	Modena	3	1	1	9:5	10
3	Mantova	3	1	0	7:3	10
4	Arezzo	3	0	1	5:7	9
5	Pisa	2	2	0	9:3	8
6	Juve Stabia	2	2	1	5:4	8
7	Ascoli	2	1	1	8:3	7
8	Virtus Entella	2	1	1	6:3	7
9	Benevento	2	0	1	4:1	6
10	Padova	2	0	2	4:5	6
11	Cremonese	1	2	2	5:6	5
12	Avellino	1	2	1	4:5	5
13	Vicenza	1	2	2	7:9	5
14	Carrarese	1	1	2	4:4	4
15	Sudtirol	1	1	2	5:7	4
16	Empoli	1	1	3	5:8	4
17	Cesena	1	1	2	3:7	4
18	Catanzaro	0	2	4	7:12	2
19	Sampdoria	0	2	4	4:13	2
20	Verona	0	1	2	4:7	1

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Variance Stats: Shows average differences from starting lines for Asian Handicap, Goal Line, and Asian Corners to identify mispriced teams in seconds
Comeback Factor: Measures how effectively teams recover after falling behind by tracking how often they score the next goal
xG Stats: Expected goals available on both match pages and in-play pages within the likelihood stats column
Pressure Index: Combines dangerous attacks, total shots, and corners to measure which team is dominating the match

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Example notification: Alert for home underdogs losing by 1 goal but with 66%+ Pressure Index, Asian Handicap +0.5, and kick-off odds under 5.00. This specific notification has achieved a 71% win rate (52 wins, 21 losses) in backtesting.

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Massive Data Analysis: Every test analyzes the last 100,000 finished games (approximately 5-6 months of matches) from the database
Live Scenario Simulation: Simulates live betting scenarios based on your custom notification rules for each game
Retrospective Likelihood Stats: Each game's likelihood stats are calculated retrospectively from that particular match for accurate testing
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Advanced Filtering: Filter results by Asian Handicap, Goal Line, Asian Corners, specific days, goals scored within 2 minutes, or missing dangerous attacks

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The Comeback Factor is a unique BetBallers metric that measures how effectively a team can recover after falling behind in a match:

What it measures: Tracks how often a team scores the next goal after the opponent has taken the lead
How it works: Every time a team falls behind, the system records whether they manage to score the next goal or not
Enhanced accuracy: You can exclude 0-0 games from calculations for more accurate statistics (feature added January 2025)
Transparency: Hover over any Comeback Factor stat to see the complete list of games used in the calculation

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Likelihood Stats are one of BetBallers' most powerful features, using an eye-catching color-coding system to show whether current odds are backed by historical statistics:

Comprehensive Market Coverage: Covers all possible markets from First Half Overs to Corners and everything in between
Color-Coded Indicators: Visual system makes it easy to spot at a glance whether odds represent good value or not
Historical Validation: Shows how current match statistics compare to historical performance patterns
In-Play Integration: Now includes xG stats directly in the likelihood stats column for even more insights

Combine Likelihood Stats with live statistics to avoid situations where real-time stats aren't backed up by historical performance. This dual approach helps identify genuinely profitable betting opportunities rather than statistical anomalies.

What are Variance Stats and how do they identify mispriced teams?

Variance Stats (also called Error Stats) show the average difference from starting lines, helping you identify mispriced teams in seconds:

Asian Handicap Variance: Shows which teams consistently outperform or underperform their handicap lines
Goal Line Variance: Identifies teams whose matches regularly go over or under expected totals
Asian Corners Variance: Reveals teams that generate more or fewer corners than bookmakers expect
Quick Identification: Find the most mispriced teams in your league or competition instantly

Variance Stats help you exploit consistent market inefficiencies by showing which teams the bookmakers systematically misprice across the most popular betting markets.

What is the Pressure Index and how is it calculated?

The Pressure Index is a composite statistic that measures which team is dominating a match by combining multiple attacking metrics:

Dangerous Attacks: Genuine scoring opportunities where the attacking team gets into dangerous positions
Total Shots: All shot attempts including both on-target and off-target efforts
Corners: Corner kicks awarded, indicating sustained attacking pressure
Percentage Display: Shows as a percentage (e.g., 66% means one team has twice the combined attacking stats)

Use Pressure Index in custom notifications to identify matches where one team is dominating but hasn't scored yet. For example, a notification for home teams with 66%+ Pressure Index while losing 1-0 achieved a 71% win rate in backtesting across 100,000 games.

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Comeback Factor and Pressure Index statistics
xG Stats on match and in-play pages

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What are xG (Expected Goals) stats and how can I use them for betting?

Expected Goals (xG) is an advanced metric that measures the quality of scoring chances by calculating the probability that a shot will result in a goal:

Available on Multiple Pages: View xG stats on both the match page and the in-play page for comprehensive analysis
Likelihood Stats Integration: Enable xG display to see these valuable insights directly in the likelihood stats column during live matches
Quality vs Quantity: xG reveals whether a team is creating genuine scoring opportunities or just accumulating low-quality shots
Value Betting Indicator: When a team has high xG but hasn't scored, it often indicates the score doesn't reflect match dominance

How to use xG for in-play betting:

Compare xG to actual score - if Team A has 2.3 xG but is losing 0-1, they may be unlucky and due for goals
Look for xG gaps between teams - a 1.5+ xG difference suggests one team is creating significantly better chances
Combine with Pressure Index - high xG plus 66%+ Pressure Index confirms genuine dominance
Use in notifications - create alerts for matches where xG doesn't match the scoreline for value betting opportunities

xG stats were added to the in-play page in August 2024, making BetBallers one of the few platforms to provide real-time expected goals data during live matches for immediate betting decisions.

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Creating effective custom notifications involves combining different statistics and using the backtesting system to validate profitability:

Mix Different Stats: Combine real-time stats, likelihood stats, averages, and odds for more accurate filtering
Use Likelihood Validation: Include likelihood stats to ensure real-time performance is backed by historical patterns
Test Thoroughly: Run backtests on your notifications to validate profitability across 100,000 historical matches
Refine and Iterate: If results are unsatisfactory, tweak your rules and run backtests again until you find winning combinations
Filter Results: Use filters to exclude games with incomplete stats or where goals were scored within 2 minutes of notification

Example winning notification:

Home underdog, losing by 1 goal, with 66%+ Pressure Index, current Asian Handicap +0.5 (minimum odds 1.80), and kick-off 1X2 odds under 5.00. This achieved 71% win rate (52 wins from 73 matches).

Fine-tuning takes time, but the backtesting system dramatically speeds up the process by providing instant validation instead of waiting months for real-world results.

Lineup
3-4-2-1	3-4-2-1
22 - Leonardo Loria	Andrea Seculin - 12
33 - Arturo Calabresi	Alessandro Riccio - 27
4 - António Caracciolo	Giovanni Zaro - 19
5 - Simone Canestrelli	Cristian Cauz - 33
20 - Pietro Beruatto	Simone Santoro - 8
51 - Andrea Barberis	Fabio Gerli - 16
17 - Jan Mlakar	Antonio Palumbo - 5
7 - Lisandru Tramoni	Niccolo Corrado - 91
36 - Gabriele Piccinini	Fabio Abiuso - 90
27 - Mattia Valoti	Thomas Battistella - 23
9 - Nicholas Bonfanti	Ettore Gliozzi - 9
Substitutes
19 - Tomas Esteves	Antonio Pergreffi - 4
16 - Mattia Sala	Lorenzo Di Stefano - 73
34 - Matteo Campani	Lukas Mondele - 42
15 - Idrissa Toure	Riccardo Gagno - 26
42 - Tommaso Barbieri	Luca Tremolada - 10
14 - Miha Trdan	Edoardo Duca - 7
3 - Maxime Leverbe	Luca Strizzolo - 32
1 - Nicolas	Luca Magnino - 6
26 - Gaetano Masucci	Kleis Bozhanaj - 30
32 - Stefano Moreo	Jacopo Manconi - 17
77 - Marco D`Alessandro	Fabio Ponsi - 3
44 - Miguel Veloso	Shady Oukhadda - 99

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[15] Pisa 2 2 Modena [8]

Lineups

Lineup

Substitutes

1X2 Odds

Dangerous Attacks

Shots on Target

Shots off Target

Possession

Attacks

Pisa vs Modena Statistics

Statistics based on last 5 10 15 games

Italy Serie B

Serie B 26/27

Serie B 26/27

Serie B 26/27

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Modena Reply_copy_4_2_ Created with Sketch.

Match notes Reply_copy_4_2_ Created with Sketch.

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^[15] Pisa 2

2 Modena ^[8]

Statistics based on last games

Pisa

Modena

Match notes