Group J · Matchday 3
AlgeriavsAustria
2026-06-27·21:00 localPredictions finalised
The forecast
Match-outcome probability
- Algeria win37.1%
- Draw28.9%
- Austria win34.0%
A clash of identities: Algeria's possession-dominant approach meets Austria's high-press style in a fixture the model gives to Austria at 43%.
Why the model says this
Favoring Algeria
- ·Algeria exhibits a highly aggressive pressing style, indicated by a 98.8 percentile PPDA (Passes Per Defensive Action).
- ·A significant portion of Algeria's attacking threat comes from set pieces, accounting for 20.0% of their xG, placing them in the 90.8 percentile for set-piece reliance.
- ·The Direct Comparison (DC) model component assigns Algeria a 33.0% chance of winning, slightly higher than the ensemble's overall 31.2%.
Favoring Austria
- ·Austria holds a higher FIFA ranking at 24th, compared to Algeria's 35th.
- ·The Elo rating system indicates Austria as the favoured side with a delta of 84 points.
- ·The historical head-to-head record shows Austria winning the only previous encounter 2-0.
- ·Austria's expected goals (xG) for this fixture are marginally higher at 1.2, compared to Algeria's 1.12.
What the model can't fully price
- ·The model does not account for the fitness doubts surrounding two projected starters across both squads, as its lineup channel currently contributes zero to the forecast.
Form check
Algeria
ImprovingAlgeria enters this match with a strong recent record, securing four wins, one draw, and one loss in their last six fixtures. This run includes a dominant 7-0 victory in a friendly, showcasing their attacking capabilities, alongside a 0-0 draw and a 0-2 defeat in the African Cup of Nations.
Scored 7 goals in a single friendly match on 2026-03-27.
Austria
ImprovingAustria also demonstrates robust form, with four wins, one draw, and one loss in their last six outings. Their recent performances include consecutive friendly victories, scoring 6 goals and conceding only 1 across these two matches, alongside important results in World Cup qualification.
Scored 6 goals and conceded 1 in their last two friendly matches.
Analysis
How it plays out
Algeria want to build from the back; Austria press high to prevent exactly that. If Algeria play through the press they'll find dangerous space. If they don't, turnovers come in costly areas. Algeria's aggressive press (PPDA 11.1) against Austria's deeper build-up (PPDA 17.0) creates a clear territory question: can Algeria force errors high up, or will Austria play through the press and find space behind it?
What decides it
Algeria's possession game (68% avg) requires patience in the final third and quick ball recovery when they lose it. Austria press high (PPDA 17.0). If the press doesn't win the ball early, the space behind their back line becomes exposed. The scoring threat is evenly split: Amine Gouiri (8.0%) and Marcel Sabitzer (6.5%).
Off the pitch
No major off-pitch asymmetries. This one is decided by the football.
The angle
Likely the last World Cup for Riyad Mahrez. Tournament experience at this level is hard to quantify but hard to replace.
▸Goals & scorelines
Likeliest score 1–1 (13.7%) · xG 1.2 - 1.3
Expected goals
Mean of the Dixon-Coles joint goal distribution. Same fit that produces the most-likely-scoreline list below.
Most likely scorelines
- 1–113.7%
- 0–110.2%
- 0–09.4%
- 1–09.4%
- 1–28.2%
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
- 0–030.1%
- 0–118.0%
- 1–016.6%
- 1–111.7%
- 0–25.9%
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 goals90.6%
- More than 1.5 goals71.0%
- More than 2.5 goals44.3%
- More than 3.5 goals23.1%
- More than 4.5 goals10.2%
- More than 5.5 goals3.9%
- Both teams score50.5%
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
- Algeria clean sheetOpposing team scores zero28.1%
- Austria clean sheetOpposing team scores zero30.8%
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
- Algeria by 4+1.2%
- Algeria by 3+4.6%
- Algeria by 2+14.2%
- Algeria by 1+33.3%
- Draw28.9%
- Austria by 1+37.8%
- Austria by 2+17.1%
- Austria by 3+5.9%
- Austria by 4+1.6%
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 44.3% · BTTS 50.5%
Game state through the match
- Algeria ahead34.1%
- Level27.3%
- Austria ahead38.6%
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
- 0–1533.5%
- 15–3022.3%
- 30–4514.8%
- 45–609.8%
- 60–756.6%
- 75–904.4%
- No goal8.6%
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 → | HAlgeria win | DDraw | AAustria win |
|---|---|---|---|
| HAlgeria ahead | 20.5% | 4.9% | 1.8% |
| DLevel | 11.9% | 17.8% | 13.2% |
| AAustria ahead | 1.6% | 4.9% | 23.5% |
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
- Algeria trail at HT, avoid defeat at FT6.5%
- Austria trail at HT, avoid defeat at FT6.7%
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: Gouiri (8.0%)
Match detail
Algeria
Model-rated key players: Amine Gouiri (FW) — P(scores) 8.0%; Riyad Mahrez (FW) — P(scores) 3.0%; Mohamed Amoura (FW) — P(scores) 2.4%.
Algeria under Vladimir Petković play a possession dominant game, holding 68% of the ball — among the highest in the tournament field. They press intensely (PPDA 11.1, highest in the field). They generate a high volume of shots (14.1 per 90) and rely heavily on set pieces (20% of their xG).
To succeed, Algeria must control tempo and territory in midfield — their possession-dominant approach depends on dictating the rhythm of each match. Managing minutes for Riyad Mahrez across what could be seven matches will test the coaching staff's rotation planning.
Austria
Model-rated key players: Marcel Sabitzer (MF) — P(scores) 6.5%; Marko Arnautović (FW) — P(scores) 4.7%; Michael Gregoritsch (FW) — P(scores) 4.6%.
Austria under Ralf Rangnick play a high press game with 53% possession. They apply moderate pressing intensity (PPDA 17.0).
Austria need their high press to force turnovers in dangerous areas — if opponents can play through the press, the space left behind is vulnerable. Physical conditioning and squad rotation will be critical to sustain pressing intensity across a long tournament. Managing minutes for Marko Arnautović across what could be seven matches will test the coaching staff's rotation planning.
Austria's predicted XI averages 1,262 club minutes over the 2024-25 season (light load).
Algeria coverage: 33.0% (6/11 XI matched against the FBref Big-5) · Austria: 89.0% (10/11).
Algeria historically converts 20.0% of xG from set-pieces, contributing 0.24 expected set-piece goals in this fixture. Austria converts 11.2% from set-pieces (0.14 expected). Combined, the model expects 0.38 set-piece goals across the 90 minutes.
- P(Algeria scores set-piece goal) 21.0%
- P(Austria scores set-piece goal) 13.2%
- P(set-piece goal in match) 31.5%
Algeria: Ilan Kebbal on corners (30 corners), Nabil Bentaleb on free kicks (per fbref 2021 22) · Austria: Alessandro Schöpf on corners (24 corners), Florian Grillitsch on free kicks (per fbref 2021 22)
If a penalty is awarded to Algeria, the model gives 71.4% conversion, 72.0% for Austria.
Algeria primary PK: Amine Gouiri (3/5 in 2021-22, per fbref 2021 22) · Austria primary PK: Marcel Sabitzer (4/4 in 2020-21, per fbref 2021 22).
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
- 11.1
- Possession
- 68%
- Directness (yds/pass)
- 6.1
- Long balls/90
- 32
- Set-piece xG
- 20%
- PPDA
- 17.0
- Possession
- 53%
- Directness (yds/pass)
- 5.7
- Long balls/90
- 34
- Set-piece xG
- 11%
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
Algeria
- Mohamed AmouraStrikerCover: Amin Chiakha · 0.160.64gap
- Amine GouiriStrikerCover: Amin Chiakha · 0.160.59gap
- Rayan Aït-NouriFull-backCover: Mehdi Dorval · 0.530.45gap
Austria
- Konrad LaimerFull-backCover: Phillipp Mwene · 0.280.58gap
- Saša KalajdžićStrikerNo natural backup0.55gap
- Michael GregoritschStrikerNo natural backup0.50gap
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 level229 m
- Avg temperatureFive-year mean over the tournament window25.8 °C
- Avg humidity69%
- Heat stressShade WBGT ~27.5 °CLow heat stress
- Pitch surfacenatural grass
Natural-grass NFL stadium; FIFA-standard hybrid 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. Night 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)
- Amine GouiriPKFW8.0%
- Riyad MahrezFW3.0%
- Mohamed AmouraFW2.4%
- Marcel SabitzerPKMF6.5%
- Marko ArnautovićFW4.7%
- Michael GregoritschFW4.6%
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
Algeria
vs Switzerland · avg 6.2
Austria
vs Spain · avg 9.0
Worked well: The performance of their goalkeeper, Alexander Schlager, was exceptional, keeping the team in the match for extended periods with crucial saves.
Struggled: Austria struggled significantly to retain possession and mount any sustained offensive movements, remaining largely on the back foot throughout the encounter.
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.
8Maza37'–82'Was a persistent attacking threat, creating multiple chances and directly contributing to a goal.
3shots3on target1headers▼
Was a persistent attacking threat, creating multiple chances and directly contributing to a goal.
Match timeline
8ChaibiScored a vital go-ahead goal and showed attacking intent by hitting the post.
Scored a vital go-ahead goal and showed attacking intent by hitting the post.
7Aouar80'–80'His shot created the rebound opportunity from which Mahrez scored a vital equalizer.
1shots▼
His shot created the rebound opportunity from which Mahrez scored a vital equalizer.
Match timeline
6BelghaliContributed to the attack with a dangerous cross that created a scoring opportunity.
Contributed to the attack with a dangerous cross that created a scoring opportunity.
5BenbotConceded three goals against Austria and struggled to contain their clinical finishing.
Conceded three goals against Austria and struggled to contain their clinical finishing.
8Arnautović19'–19'Opened the scoring for Austria with a well-taken goal, demonstrating excellent movement.
1goals▼
Opened the scoring for Austria with a well-taken goal, demonstrating excellent movement.
Match timeline
8KalajdzicSecured a crucial late equalizer with a well-placed header, showcasing his aerial ability.
Secured a crucial late equalizer with a well-placed header, showcasing his aerial ability.
7LaimerProvided an assist for Austria's second goal after an effective attacking run and delivery.
Provided an assist for Austria's second goal after an effective attacking run and delivery.
Match observations
- This was a highly entertaining and high-scoring match, with both teams showing strong attacking intent.
- The lead changed hands multiple times, creating a dramatic contest for the fans.
- Austria showed their fighting spirit by securing a last-minute equaliser.
▸Under the hood
Model-by-model comparison
Algeria vs Austria
| Model | Weight | Home | Draw | Away |
|---|---|---|---|---|
| EloRating-based strength estimate | 32% | 28.1% | 22.0% | 49.9% |
| Dixon-ColesGoal-process model with low-score correction | 63% | 33.3% | 28.6% | 38.0% |
| Hierarchical PoissonBayesian model with confederation pooling | 6% | 32.6% | 27.9% | 39.5% |
| Bayesian stackingLearned-weight combination | — | 31.0% | 27.6% | 41.4% |
| Ensemble (published)Uniform average + isotonic calibration | — | 31.9% | 25.5% | 42.6% |
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(Algeria win)32.2%
- + Lineup contribution0.0pp
- + Style-matchup contribution0.0pp
- Published P(Algeria win)32.2%
Decomposition of the published P(Algeria 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.
Head-to-head history
| Date | Competition | Venue | Score | Result | xG |
|---|---|---|---|---|---|
| 21 Jun 1982 | FIFA World Cup | NOviedo | 0–2 | L | — |
Algeria vs Austria, every senior international meeting in the martj42 results dataset (score from Algeria's perspective; H/A/N = home/away/neutral).
Latest news & match context
No recent headlines for Algeria or Austria.
- Stage:
- Group J · Matchday 3
- Date:
- 27 Jun
Ranked by likely importance. None of these feed the forecast: the probabilities rest on team strength, venue conditions and the style matchup.
- 1.Squad availability: 1 carrying a fitness doubt across the two squads, 1 of them projected starters. The forecast does not adjust for who is missing: its lineup channel currently contributes zero, so this is context the probabilities do not include.
Algeria
Algeria: 1 carrying a fitness doubt.
- DoubtAnthony Mandrea, the first-choice goalkeeper, is recovering from Shoulder injury and is a fitness watch item; if unavailable the projected XI shifts.
Austria
Austria come in at close to full strength.
Availability runs in Austria's favour here: Algeria are managing a fitness concern over Anthony Mandrea, while Austria's projected XI looks intact.
Availability from the predicted squads and injury feed; forecast adjustments from the model's own decomposition. See /docs/methodology/.
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