· Thai League 1
Sisaket United
ATT
4/10
DEF
5/10
vs
Ratchaburi Mitr Phol FC
8/10
ATT
6/10
DEF
Scheduled· Fri 30 Oct · 12:00
Best Pick
BTTS
53%
Correct Score
Top
1-1
12.5%
8.02
Top
0-1
10.1%
9.86
1-0
9%
11.13
1-2
8.6%
11.57
2-1
7.7%
13.06
0-0
7.3%
13.68
0-2
7%
14.22
2-0
5.5%
18.11
133%
3.01
X26%
3.82
241%
2.46TOP
1X59%
X267%
1274%
Probable XI4-4-2
Pakkarano
Carneiro
Jaiphet
Bua-ngam
Klinjumpasri
Matsui
Wongma
Kamnet
Lopez
Nandje
Fernandes
Impact Player Hot Head
Lineups not yet announced — full squad analysis below
Sisaket United24 players
49.2/ 99Average
Top Rated
1Narongrit KamnetMID77
2JefinhoFWD73
3Anderson CarneiroDEF63
Ratchaburi Mitr Phol FC34 players
52.6/ 99Average
Top Rated
1Njiva Tsilavina Martin RakotoharimalalaFWD92
2Robert ZuljFWD88
3Adison PromrakDEF83
Sisaket United31
PlayerOverall RatingImpactAggressionDiscipline
Narongrit Kamnet77625991
Jefinho73694883
Anderson Carneiro63793950
Sebas Moyano63655256
Deyvison Fernandes62732850
Denis Darbellay59565361
Isaac Honny56773637
Pakornkiat Kaena54534461
Anusak Jaiphet53623651
Steven van Dijk51512350
Suphaphon Sutthisak49475251
Chutikom Klinjumpasri48434756
Sakkranvit Nimma48523950
Ratchaburi Mitr Phol FC40
PlayerOverall RatingImpactAggressionDiscipline
Njiva Tsilavina Martin Rakotoharimalala92995472
Robert Zulj88904191
Adison Promrak83767175
Sorawit Panthong70587665
Roque Mesa66637754
Gleyson64623778
Denílson61743337
Todsawat Limwanasthian59475769
Kevin Deeromram58305191
Kampol Pathomakkakul55546656
Nopphon Lakhonphon5557950
Sanchai Nontasila55487349
Ukrit Wongmeema54543950
Player Rankings
Snipers
Top goal threats
1
Njiva Tsilavina Martin RakotoharimalalaRatchaburi Mitr Phol FC
99
2
Robert ZuljRatchaburi Mitr Phol FC
90
3
DenílsonRatchaburi Mitr Phol FC
74
4
Deyvison FernandesSisaket United
73
5
JefinhoSisaket United
69
Wall
Top defenders
1
Anderson CarneiroSisaket United
79
2
Isaac HonnySisaket United
77
3
Adison PromrakRatchaburi Mitr Phol FC
76
4
Jonathan KhemdeeRatchaburi Mitr Phol FC
73
5
Anusak JaiphetSisaket United
62
Control
Top playmakers
1
Thanawat SuengchitthawonRatchaburi Mitr Phol FC
71
2
TanaRatchaburi Mitr Phol FC
68
3
Siwakorn JakkuprasatRatchaburi Mitr Phol FC
64
4
Roque MesaRatchaburi Mitr Phol FC
63
5
Narongrit KamnetSisaket United
62
Bad Boys
Most likely to get booked
1
Thanison PaibulkijcharoenSisaket United
1
2
Sittichok Kannoo Sisaket United
1
3
Siwakorn JakkuprasatRatchaburi Mitr Phol FC
1
4
Thanawat SuengchitthawonRatchaburi Mitr Phol FC
3
5
Kritsanon SrisuwanRatchaburi Mitr Phol FC
10
Power Rankings
Strongest overall
1
Njiva Tsilavina Martin RakotoharimalalaRatchaburi Mitr Phol FC
92
2
Robert ZuljRatchaburi Mitr Phol FC
88
3
Adison PromrakRatchaburi Mitr Phol FC
83
4
Narongrit KamnetSisaket United
77
5
JefinhoSisaket United
73

Frequently Asked Questions

Our Poisson model calculates the probability of every possible scoreline for Sisaket United vs Ratchaburi Mitr Phol FC based on each team's expected goals (xG). The top-3 most likely scorelines are shown above with their probability percentages. Even the highest-probability score rarely exceeds 12-15% chance, as football is a low-scoring sport.

The Bet Builder combines multiple selections from the Sisaket United vs Ratchaburi Mitr Phol FC match into one bet. Our AI identifies outcomes that complement each other — for example, a home win paired with over 2.5 goals and both teams to score. All selections must win for the combined bet to pay out, which means higher combined odds but also higher risk.

xG (expected goals) measures the quality of scoring chances. If Sisaket United has an xG of 1.8, it means they are expected to score around 1-2 goals based on chance quality. The model uses pre-match xG to build a probability table for all possible scorelines. A team can overperform xG (score more than expected) or underperform xG (score fewer).

Yes, all predictions on ProSoccer are completely free. You can view predicted scorelines, over/under probabilities, and bet builder suggestions for Sisaket United vs Ratchaburi Mitr Phol FC without paying or registering. Odds values are revealed after a tap to keep the page compliant with search engine guidelines.

A value bet occurs when the probability of an outcome is higher than what the bookmaker odds suggest. For example, if our model gives Sisaket United a 55% chance of winning but the odds imply only 40%, that is a value bet. Our AI highlights selections where the model probability exceeds the implied probability from the odds.

AI predictions use statistical modeling (Poisson distribution) based on historical data and pre-match metrics. They are more reliable over large samples than for any single match. No prediction is guaranteed — football has inherent unpredictability. Our model typically identifies the correct top-3 scorelines in 25-30% of matches, which is significantly better than random chance.

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