Group K · Matchday 3
DR CongovsUzbekistan
2026-06-27·19:00 localPredictions finalised
The forecast
Match-outcome probability
- DR Congo win30.7%
- Draw34.5%
- Uzbekistan win34.8%
The model projects one of the most closely-contested fixtures of the round — DR Congo and Uzbekistan are separated by fine margins across every outcome.
Why the model says this
Favoring DR Congo
- ·DR Congo has a strong recent record of 4 wins, 1 draw, and 1 loss in their last 6 matches.
- ·In their last 6 matches, DR Congo conceded only 2 goals, keeping 4 clean sheets.
- ·DR Congo shows a high reliance on set pieces, with 20.5% of their xG coming from these situations, placing them in the 93.4 percentile.
- ·DR Congo's attacking approach is highly direct, with an index in the 86.2 percentile.
Favoring Uzbekistan
- ·Uzbekistan is favoured by 72 ELO points over DR Congo.
- ·Uzbekistan holds a FIFA rank of 50, while DR Congo's rank is not provided, suggesting Uzbekistan is the higher-ranked side.
- ·The ELO model gives Uzbekistan a 49.2% chance of winning, significantly higher than DR Congo's 28.8%.
- ·Uzbekistan's expected goals (0.94) are slightly higher than DR Congo's (0.9).
What the model can't fully price
- ·The venue is not specified, meaning potential home advantage for DR Congo cannot be fully accounted for.
- ·No information on squad availability, such as injuries or suspensions, is provided for either team.
- ·The specific match context within Group K, such as qualification implications, is not detailed, which could influence team motivation.
Form check
DR Congo
ImprovingDR Congo enters this match in strong form, having secured four wins and one draw in their last six outings. Their defensive solidity is notable, conceding only two goals during this period.
4 wins in last 6 matches
Uzbekistan
SteadyUzbekistan's recent form is mixed, with two wins, three draws, and one loss in their last six fixtures. They have shown resilience with multiple draws but have not consistently secured victories.
3 draws in last 6 matches
Analysis
How it plays out
Uzbekistan's balanced setup will need to hold shape against DR Congo's direct transition game. The risk for Uzbekistan: getting caught between attacking and defending.
What decides it
DR Congo will concede possession willingly and attack in transition. Their defensive block needs to hold without fouling in dangerous areas. Yoane Wissa's 10.9% scoring probability is the highest in this fixture. Containing that output is Uzbekistan's primary defensive task.
Off the pitch
Sébastien Desabre (4 years in charge of DR Congo) vs Fabio Cannavaro (1 years). That tenure gap shows up in squad familiarity and set-piece coordination.
The angle
A Group K fixture where the result matters more for the standings than the headlines.
▸Goals & scorelines
Likeliest score 0–0 (20.3%) · xG 0.9 - 0.7
Expected goals
Mean of the Dixon-Coles joint goal distribution. Same fit that produces the most-likely-scoreline list below.
Most likely scorelines
- 0–020.3%
- 1–016.7%
- 1–113.7%
- 0–113.6%
- 2–07.8%
From the Dixon-Coles joint Poisson with the low-score correction. Scorelines are listed in probability order; this is a description of the model's distribution, not a recommendation.
Most likely half-time scorelines
- 0–044.6%
- 1–019.3%
- 0–115.9%
- 1–17.8%
- 2–04.4%
Same Dixon-Coles fit as the full-time list above, with rates halved to a 45-minute window and the low-score correction applied to that 1st-half block. The 0-0 row sits higher here than at full-time because fewer minutes have elapsed.
Goal totals
- More than 0.5 goals79.7%
- More than 1.5 goals49.4%
- More than 2.5 goals22.5%
- More than 3.5 goals8.3%
- More than 4.5 goals2.6%
- More than 5.5 goals0.7%
- Both teams score31.7%
Each row is the probability the match finishes with more than the listed number of goals. Both-teams-to-score is the probability each side scores at least once. All values are marginals of the Dixon-Coles joint goal grid that produces the scoreline list above — not market lines or any other operator construct.
Event-typed probabilities
- DR Congo clean sheetOpposing team scores zero47.8%
- Uzbekistan clean sheetOpposing team scores zero40.9%
Derived from the same Dixon-Coles joint distribution as the scoreline list. These are descriptive event probabilities — see CLAUDE.md §3/§4 (formerly COMPLIANCE.md §4.2.7) for the framing the project uses.
Win-margin probability
- DR Congo by 4+0.7%
- DR Congo by 3+3.5%
- DR Congo by 2+13.1%
- DR Congo by 1+36.3%
- Draw36.3%
- Uzbekistan by 1+27.4%
- Uzbekistan by 2+8.5%
- Uzbekistan by 3+1.9%
- Uzbekistan by 4+0.3%
Each row is the probability the match ends with the listed margin or larger in that direction. Marginal of the Dixon-Coles joint goal grid; the “by 1+” rows plus the draw row sum to 1.
▸How the match unfolds
Over 2.5 goals 22.5% · BTTS 31.7%
Game state through the match
- DR Congo ahead37.0%
- Level34.7%
- Uzbekistan ahead28.2%
Probability of each game state at minutes 0, 15, 30, 45, 60, 75, 90 — derived from two independent thinned-Poisson processes with the Dixon-Coles per-team rates. The three lines always sum to 1 at each minute. The right column shows the state at the match's closing minute.
When the first goal arrives
- 0–1523.8%
- 15–3018.2%
- 30–4513.8%
- 45–6010.5%
- 60–758.0%
- 75–906.1%
- No goal19.5%
Probability the match's first goal arrives in each 15-minute window. Homogeneous Poisson with combined rate λ = λh + λa from the Dixon-Coles fit; the seven rows (six windows + no-goal tail) sum to 1.
Half-time / full-time grid
| HT ↓ / FT → | HDR Congo win | DDraw | AUzbekistan win |
|---|---|---|---|
| HDR Congo ahead | 21.8% | 3.9% | 0.8% |
| DLevel | 14.2% | 27.3% | 11.2% |
| AUzbekistan ahead | 1.0% | 3.9% | 16.1% |
Each cell is P(half-time result, full-time result). All nine cells sum to 1. Derived from a halved-λ Dixon-Coles fit for the first half plus an independent-Poisson second-half convolution.
Comeback probability
- DR Congo trail at HT, avoid defeat at FT4.8%
- Uzbekistan trail at HT, avoid defeat at FT4.7%
Joint probability — P(side trailing at half-time AND avoiding defeat at full-time). NOT conditional on trailing at HT. Derived from the same half-time / full-time decomposition that produces the HT/FT grid above; a tied first half is neither a home nor an away comeback opportunity.
Cards
- Expected yellow cardsMean of the Poisson on total yellow cards.3.45
- Total yellows over 2.567.0%
- Total yellows over 3.545.3%
- Total yellows over 4.526.5%
- Any red cardP(at least one red card in the match).9.5%
Referee not yet assigned. Using the 2026 pool-mean per-match rate as a placeholder; the model picks up the referee's personal rate once the assignment is published. Total yellow cards modelled as a Poisson with mean equal to two team baselines plus the referee's deviation from the pool mean. Reds are modelled the same way, independently. See /docs/methodology/.
▸Teams & players
Top scorer: Wissa (10.9%)
Match detail
DR Congo
Model-rated key players: Yoane Wissa (FW) — P(scores) 10.9%; Cédric Bakambu (FW) — P(scores) 5.7%; Jackson Muleka (FW) — P(scores) 3.4%.
DR Congo under Sébastien Desabre play a counter attacker game with 46% possession. They apply moderate pressing intensity (PPDA 20.9) and move the ball forward quickly at 4.9 passes per attack. They favour high-quality chances (xG/shot 0.200, among the best in the field) and rely heavily on set pieces (20% of their xG).
DR Congo rely on defensive discipline and quick transitions — absorbing pressure and converting turnovers into attacking chances. Concentration and defensive organisation for full 90-minute stretches will determine whether the approach holds against top opposition.
Uzbekistan
Model-rated key players: Eldor Shomurodov (FW) — P(scores) 3.8%; Abbosbek Fayzullaev (FW) — P(scores) 2.8%; Dostonbek Khamdamov (FW) — P(scores) 2.8%.
Limited recent tournament data is available for Uzbekistan's tactical profile. Early indicators suggest a balanced approach.
Uzbekistan will need to leverage their strengths while managing the physical demands of a tournament spread across three host countries.
DR Congo historically converts 20.5% of xG from set-pieces, contributing 0.18 expected set-piece goals in this fixture. Combined, the model expects 0.18 set-piece goals across the 90 minutes.
- P(DR Congo scores set-piece goal) 16.7%
- P(set-piece goal in match) 16.7%
If a penalty is awarded to DR Congo, the model gives 73.3% conversion, 76.0% for Uzbekistan.
DR Congo primary PK: Yoane Wissa (4/5 in 2020-21, per fbref 2020 21).
Derived from the model's per-fixture forecast joint and supporting reference data (predicted squads, set-piece xG share, PK posteriors, club minutes). See /docs/methodology/ for the full methodology.
Tactical forecast
- PPDA
- 20.9
- Possession
- 46%
- Directness (yds/pass)
- 7.6
- Long balls/90
- 36
- Set-piece xG
- 20%
Partial coverage from FotMob match stats (recent qualifiers and friendlies): possession and shot volume only. Press and build-up metrics are not available for this side.
- PPDA
- —
- Possession
- 44%
- Directness (yds/pass)
- —
- Long balls/90
- —
- Set-piece xG
- —
Style profile per side from StatsBomb open-data aggregation across recent international tournaments (Euro 2020/2024, Copa America 2024, AFCON 2023, World Cup 2018/2022). The tactical-fingerprint badge maps each team’s observed style vector into one of eight canonical archetypes via a rule-based classifier; teams with fewer than three matches of qualifying coverage carry an “insufficient-data” label rather than being forced into a default. Sides outside the StatsBomb-open corpus use FotMob team match stats from recent qualifiers and friendlies instead (possession and shot volume only), marked as partial coverage. PPDA = passes the side allows per defensive action (lower = more intense press). Formation distributions are not yet produced — that head of the §2.7 classifier is pending its own data pull. See /docs/methodology/.
Squad depth
Most irreplaceable starters
DR Congo
- Meschak EliaAttacking midfieldNo natural backup0.20gap
- Gaël KakutaAttacking midfieldNo natural backup0.16gap
- Yoane WissaStrikerCover: Simon Banza · 0.750.14gap
Uzbekistan
- Abdukodir KhusanovCentre-backCover: Umar Eshmurodov · 0.280.53gap
- Eldor ShomurodovStrikerNo natural backup0.22gap
- Odiljon HamrobekovDefensive midfieldCover: Abdulla Abdullaev · 0.310.03gap
Gap = how far a side's rating at the position falls from the starter to his likely in-squad replacement (named under each name). Larger = harder to replace. Descriptive metric, does not feed the published probabilities. Methodology →
Match conditions
- AltitudeNear sea level320 m
- Avg temperatureFive-year mean over the tournament window25.7 °C
- Avg humidity73%
- Heat stressShade WBGT ~27.9 °CLow heat stress
- Pitch surfacetemporary natural grass over artificial turf
Indoor artificial-turf stadium converting to a temporary natural-grass pitch for the tournament.
Heat stress is a shade Wet-Bulb Globe Temperature proxy from the venue's climatology mean temperature and humidity; FIFA mandates cooling breaks at WBGT 32 °C. Evening kickoff (local time). These are long-window averages, not a match-day forecast, and they are not inputs to the forecast.
Top scorers · P(scores in this match)
- Yoane WissaPKFW10.9%
- Cédric BakambuFW5.7%
- Jackson MulekaFW3.4%
- Eldor ShomurodovFW3.8%
- Abbosbek FayzullaevFW2.8%
- Dostonbek KhamdamovFW2.8%
Per-player scoring rate from Model #5 (`p_score_per_match`). Reflects each player's npxG/90, expected minutes, team xG share, and the average opposing-team defence. See /docs/methodology/.
Recent match form
Last match player ratings
DR Congo
vs England · avg 7.7
Uzbekistan
vs Portugal · avg 3.0
Player scores from official highlight analysis of each team's most recent match. Observational, not a model input. Methodology →
Video analysis: player performance
Per-player ratings and event breakdowns from official highlights analysis. Tap a player to see their full match timeline.
8Cédric Bakambu34'–34'Scored a crucial equalizer with individual brilliance, demonstrating clinical finishing and dribbling skill.
1goals▼
Scored a crucial equalizer with individual brilliance, demonstrating clinical finishing and dribbling skill.
Match timeline
8Lionel Mpasi11'–147'Delivered an exceptional performance with numerous crucial saves, keeping his team in the game against relentless pressure.
8saves▼
Delivered an exceptional performance with numerous crucial saves, keeping his team in the game against relentless pressure.
Match timeline
8MunozScored the decisive goal for Colombia, showcasing good attacking positioning to secure the win.
Scored the decisive goal for Colombia, showcasing good attacking positioning to secure the win.
7Luis DiazA constant attacking threat who created several chances and had a goal disallowed for offside.
A constant attacking threat who created several chances and had a goal disallowed for offside.
6PuertaContributed to Colombia's attacking efforts with two shots on target, showing offensive intent from midfield.
Contributed to Colombia's attacking efforts with two shots on target, showing offensive intent from midfield.
6AlijonovInvolved in general defensive efforts, attempting to halt opposition advances without specific notable actions.
Involved in general defensive efforts, attempting to halt opposition advances without specific notable actions.
Match observations
- The match was an attacking spectacle, featuring multiple goals and dynamic offensive movements from both sides.
- The atmosphere in the stadium was vibrant, with a large crowd and flags representing both nations.
- COD demonstrated a strong comeback, overturning an early deficit to secure a commanding lead.
▸Under the hood
Model-by-model comparison
DR Congo vs Uzbekistan
| Model | Weight | Home | Draw | Away |
|---|---|---|---|---|
| EloRating-based strength estimate | 32% | 38.1% | 22.0% | 39.9% |
| Dixon-ColesGoal-process model with low-score correction | 63% | 36.2% | 35.8% | 28.0% |
| Hierarchical PoissonBayesian model with confederation pooling | 6% | 35.8% | 34.6% | 29.6% |
| Bayesian stackingLearned-weight combination | — | 36.5% | 35.9% | 27.6% |
| Ensemble (published)Uniform average + isotonic calibration | — | 37.0% | 34.4% | 28.6% |
How each model works
- Elo
- Each team carries a single strength rating updated after every match by a margin-aware K-factor. Match probabilities come from the logistic function of the rating gap. Elo is fast-adapting but coarse — it sees only who won and by how much, not how the goals were scored.
- Dixon-Coles
- A Poisson regression on team-level attack and defence parameters, fitted via maximum likelihood with an exponential time-decay weighting. The Dixon-Coles correction adjusts the four low-score cells (0-0, 1-0, 0-1, 1-1) where independent Poisson underestimates dependence. Produces full scoreline distributions, not just H/D/A.
- Hierarchical Poisson
- A Bayesian Poisson model fitted via MCMC (PyMC) with hierarchical priors that pool attack and defence parameters within confederations. Shrinks small-sample teams toward their confederation mean — helpful for nations with few recent competitive fixtures. Slower to fit but better-calibrated on the tails.
- Bayesian stacking
- Optimises simplex weights (w_elo, w_dc, w_hp) to maximise the leave-one-out log-score across a walk-forward backtest (Yao et al. 2018). The result is a weighted average of the three component models' probabilities, then isotonic-calibrated. Adds no extra features — just learns which component to trust more from historical accuracy.
- Ensemble (published)
- Equal-weight average of all three component models, followed by per-class isotonic regression calibration fitted on 24 months of walk-forward out-of-fold predictions. This is the probability published on the site. The uniform mean is deliberately simple — it avoids overfitting to the stacking weights' training window.
Three independent component models feed two combination strategies. The uniform ensemble is the published probability; Bayesian stacking uses learned weights. Amber bars flag >5pp divergence from the published number. Full methodology
Probability decomposition (transparency surface)
- Baseline ensemble — P(DR Congo win)28.5%
- + Lineup contribution0.0pp
- + Style-matchup contribution0.0pp
- Published P(DR Congo win)28.5%
Decomposition of the published P(DR Congo win) into the calibrated- baseline plus contributions from the §2.3 expected-XI lineup delta and the §2.7 style-matchup interaction. The §2.7 roadmap is explicit that style effects are second-order to team strength — single-digit-percentage P(win) shifts on extreme style matchups, near-zero on balanced ones. We surface the decomposition for transparency even when the contributions are small; the baseline carries the prediction. Methodology: /docs/methodology.
For this fixture both contributions round to under 0.05pp — the fitted style-matchup pair effect is in the small-magnitude regime the model expects to dominate.
Latest news & match context
No recent headlines for DR Congo or Uzbekistan.
- Stage:
- Group K · Matchday 3
- Date:
- 27 Jun
DR Congo
DR Congo come in at close to full strength.
Uzbekistan
Uzbekistan come in at close to full strength.
Both DR Congo and Uzbekistan report full strength squads for this fixture.
With no significant availability concerns, the forecast relies on the baseline team strengths of both sides.
Availability from the predicted squads and injury feed; forecast adjustments from the model's own decomposition. See /docs/methodology/.
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