· Friendly International
Congo DR
ATT
5/10
DEF
6/10
vs
Uganda
5/10
ATT
4/10
DEF
Scheduled· Fri 2 Oct · 13:00
Best Pick
BTTS
52%
Correct Score
Top
1-1
11.8%
8.48
Top
1-0
11.1%
8.99
2-1
9.5%
10.49
2-0
9%
11.12
0-1
7.3%
13.71
0-0
6.9%
14.54
1-2
6.2%
16.00
3-1
5.1%
19.46
150%
1.99TOP
X25%
4.03
225%
4.02
1X75%
X250%
1275%
Probable XI4-4-2
Siadi
Wan-Bissaka
Masuaku
Tuanzebe
Bayeye
Tshibola
Amongo
Ngalamulume
Pickel
Cipenga
Bakambu
Impact Player Hot Head
Lineups not yet announced — full squad analysis below
Congo DR8 players
50.8/ 99Average
Top Rated
1Lionel Mpasi-NzauGK54
2Steve KapuadiDEF54
3Gédéon KaluluDEF53
Uganda10 players
48.1/ 99Average
Top Rated
1Denis Onyango GK52
2Baba AlhassanMID52
3Khalid AuchoMID52
Congo DR64
PlayerOverall RatingImpactAggressionDiscipline
Lionel Mpasi-Nzau54554550
Steve Kapuadi54614550
Gédéon Kalulu53455361
Axel Tuanzebe51544550
Chancel Mbemba49514550
Ngal'ayel Mukau49454856
Samuel Moutoussamy49454856
Cédric Bakambu47474550
Baggio Siadi————
Brudel Efonge————
Dimitry Bertaud————
Esdras Kabamba————
Jackson Lunanga————
Uganda63
PlayerOverall RatingImpactAggressionDiscipline
Denis Onyango 52524550
Baba Alhassan52534950
Khalid Aucho52495056
Allan Okello51525150
U. Ikpeazu51457056
Jordan Obita49494750
Steven Mukwala47474750
Toby Sibbick46464550
Hilary Mukundane44565526
Kenneth Semakula37536713
Crispus Kusiima————
Hannington Sebwalunyo————
Ismail Watenga————
Player Rankings
Snipers
Top goal threats
1
Cédric BakambuCongo DR
47
2
Steven MukwalaUganda
47
3
U. IkpeazuUganda
45
Wall
Top defenders
1
Steve KapuadiCongo DR
61
2
Hilary MukundaneUganda
56
3
Axel TuanzebeCongo DR
54
4
Chancel MbembaCongo DR
51
5
Jordan ObitaUganda
49
Control
Top playmakers
1
Baba AlhassanUganda
53
2
Kenneth SemakulaUganda
53
3
Allan OkelloUganda
52
4
Khalid AuchoUganda
49
5
Ngal'ayel MukauCongo DR
45
Bad Boys
Most likely to get booked
1
Kenneth SemakulaUganda
13
2
Hilary MukundaneUganda
26
3
Lionel Mpasi-NzauCongo DR
50
4
Axel TuanzebeCongo DR
50
5
Chancel MbembaCongo DR
50
Power Rankings
Strongest overall
1
Lionel Mpasi-NzauCongo DR
54
2
Steve KapuadiCongo DR
54
3
Gédéon KaluluCongo DR
53
4
Denis Onyango Uganda
52
5
Baba AlhassanUganda
52

Frequently Asked Questions

Our Poisson model calculates the probability of every possible scoreline for Congo DR vs Uganda 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 Congo DR vs Uganda 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 Congo DR 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 Congo DR vs Uganda 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 Congo DR 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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