LDLC ASVEL Villeurbanne vs FC Bayern Munich Prediction · EuroLeague 2026-27 Regular Season · November 5, 2026

LDLC ASVEL Villeurbanne

Home
71.8%
VS

FC Bayern Munich

Away
28.2%
Regular Season EuroLeague 2026-27

Why the Model Favors LDLC ASVEL Villeurbanne

The factors that drove this prediction, measured in win-probability points.

Home court +14.1 LDLC ASVEL Villeurbanne
Team strength (Elo & Glicko) +6.0 LDLC ASVEL Villeurbanne
Ballhandling, steals & fouls +1.7 LDLC ASVEL Villeurbanne
Rebounding & paint presence +1.6 LDLC ASVEL Villeurbanne
Scoring & shooting +1.1 FC Bayern Munich

Starting from an even matchup, these factors move the model to 72% for LDLC ASVEL Villeurbanne. Computed with gradient-based attribution on our neural network, not editorial opinion. How to read this →

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Player Projections

Per-player expected lines and full probability distributions, including PIR, EuroLeague's signature box-score metric. Click a player to view their full distributions.

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HOMELDLC ASVEL Villeurbanne

PTS11.5 REB2.4 AST3.1 3PM1.6 PIR12.6
Distribution (PDF)
Cumulative Probability: P(Points > X)
Distribution (PDF)
Cumulative Probability: P(Rebounds > X)
Distribution (PDF)
Cumulative Probability: P(Assists > X)
Distribution (PDF)
Cumulative Probability: P(3-Pointers Made > X)
Distribution (PDF)
Cumulative Probability: P(PIR > X)
PTS11.6 REB2.1 AST3.7 3PM2.1 PIR12.9
Distribution (PDF)
Cumulative Probability: P(Points > X)
Distribution (PDF)
Cumulative Probability: P(Rebounds > X)
Distribution (PDF)
Cumulative Probability: P(Assists > X)
Distribution (PDF)
Cumulative Probability: P(3-Pointers Made > X)
Distribution (PDF)
Cumulative Probability: P(PIR > X)
PTS9.6 REB2.8 AST1.9 3PM1.2 PIR10.6
Distribution (PDF)
Cumulative Probability: P(Points > X)
Distribution (PDF)
Cumulative Probability: P(Rebounds > X)
Distribution (PDF)
Cumulative Probability: P(Assists > X)
Distribution (PDF)
Cumulative Probability: P(3-Pointers Made > X)
Distribution (PDF)
Cumulative Probability: P(PIR > X)
PTS13.5 REB4.3 AST3.1 3PM1.3 PIR15.4
Distribution (PDF)
Cumulative Probability: P(Points > X)
Distribution (PDF)
Cumulative Probability: P(Rebounds > X)
Distribution (PDF)
Cumulative Probability: P(Assists > X)
Distribution (PDF)
Cumulative Probability: P(3-Pointers Made > X)
Distribution (PDF)
Cumulative Probability: P(PIR > X)
PTS8.3 REB4.9 AST1.2 3PM0.0 PIR11.5
Distribution (PDF)
Cumulative Probability: P(Points > X)
Distribution (PDF)
Cumulative Probability: P(Rebounds > X)
Distribution (PDF)
Cumulative Probability: P(Assists > X)
Distribution (PDF)
Cumulative Probability: P(3-Pointers Made > X)
Distribution (PDF)
Cumulative Probability: P(PIR > X)

AWAYFC Bayern Munich

PTS9.6 REB2.0 AST2.8 3PM2.1 PIR7.6
Distribution (PDF)
Cumulative Probability: P(Points > X)
Distribution (PDF)
Cumulative Probability: P(Rebounds > X)
Distribution (PDF)
Cumulative Probability: P(Assists > X)
Distribution (PDF)
Cumulative Probability: P(3-Pointers Made > X)
Distribution (PDF)
Cumulative Probability: P(PIR > X)
PTS6.4 REB1.9 AST2.2 3PM0.8 PIR6.2
Distribution (PDF)
Cumulative Probability: P(Points > X)
Distribution (PDF)
Cumulative Probability: P(Rebounds > X)
Distribution (PDF)
Cumulative Probability: P(Assists > X)
Distribution (PDF)
Cumulative Probability: P(3-Pointers Made > X)
Distribution (PDF)
Cumulative Probability: P(PIR > X)
PTS7.8 REB3.6 AST1.9 3PM1.2 PIR7.7
Distribution (PDF)
Cumulative Probability: P(Points > X)
Distribution (PDF)
Cumulative Probability: P(Rebounds > X)
Distribution (PDF)
Cumulative Probability: P(Assists > X)
Distribution (PDF)
Cumulative Probability: P(3-Pointers Made > X)
Distribution (PDF)
Cumulative Probability: P(PIR > X)
PTS8.3 REB3.4 AST2.4 3PM1.0 PIR7.8
Distribution (PDF)
Cumulative Probability: P(Points > X)
Distribution (PDF)
Cumulative Probability: P(Rebounds > X)
Distribution (PDF)
Cumulative Probability: P(Assists > X)
Distribution (PDF)
Cumulative Probability: P(3-Pointers Made > X)
Distribution (PDF)
Cumulative Probability: P(PIR > X)
PTS7.4 REB5.4 AST0.8 3PM0.0 PIR9.2
Distribution (PDF)
Cumulative Probability: P(Points > X)
Distribution (PDF)
Cumulative Probability: P(Rebounds > X)
Distribution (PDF)
Cumulative Probability: P(Assists > X)
Distribution (PDF)
Cumulative Probability: P(3-Pointers Made > X)
Distribution (PDF)
Cumulative Probability: P(PIR > X)

Starting Five Matchup

1
Hugo Besson Guard
PTS
11.5
PIR
12.6
REB
2.4
VS
Andreas Obst Guard
PTS
9.6
PIR
7.6
REB
2.0
2
Tremont Waters Guard
PTS
11.6
PIR
12.9
REB
2.1
VS
Kamar Baldwin Guard
PTS
6.4
PIR
6.2
REB
1.9
3
Both Gach Forward
PTS
9.6
PIR
10.6
REB
2.8
VS
Miles Norris Forward
PTS
7.8
PIR
7.7
REB
3.6
4
Jae Crowder Forward
PTS
13.5
PIR
15.4
REB
4.3
VS
Marjon Beauchamp Forward
PTS
8.3
PIR
7.8
REB
3.4
5
Joel Bolomboy Center
PTS
8.3
PIR
11.5
REB
4.9
VS
Austin Wiley Center
PTS
7.4
PIR
9.2
REB
5.4
1-5 = projected starter slot, the order the model expects the five to be named · PTS = Projected Points · PIR = Performance Index Rating (all-round impact) · REB = Projected Rebounds

Key Prediction Insights

LDLC ASVEL Villeurbanne is favored at home, with a 72% chance to beat FC Bayern Munich. The projection gives ASVEL a six-point advantage, with Jae Crowder among its principal contributors.

Total Points & Spread Analysis

The projected 176 combined points point to a game with plenty of scoring. A six-point ASVEL margin suggests a competitive contest, but not a coin flip.

Full probability curves from our Poisson (total) and Negative-Binomial (spread) models: both the distribution (PDF) and the cumulative probability (CDF).

Total Points · expected 175.7

Distribution (PDF)
Cumulative Probability: P(≤ X)

Spread (LDLC ASVEL Villeurbanne − FC Bayern Munich) · expected +6.3

Distribution (PDF)
Cumulative Probability: P(≤ X)

ELO Rating Trends

Both ratings are falling, but Bayern’s momentum is markedly worse: its ELO has dropped 78 points over the last five games, compared with four for ASVEL.

LDLC ASVEL Villeurbanne

-63 +9 over last 5 games

Season-relative ELO (0 = league-average team; resets each season).

FC Bayern Munich

-71 -6 over last 5 games

Season-relative ELO (0 = league-average team; resets each season).

EuroLeague ELO Power Rankings

See how every team stacks up: full ELO ratings, recent form and the season progression chart.

View Full ELO Ratings

Recent Form: Last 5 Games

LDLC ASVEL Villeurbanne

2-1 in last 3
LWW
OpponentPFPADiff
Zalgiris Kaunas 85 105 -20
Partizan Mozzart Bet Belgrade 82 75 +7
Kosner Baskonia Vitoria-Gasteiz 94 79 +15

FC Bayern Munich

0-3 in last 3
LLL
OpponentPFPADiff
Dubai Basketball 91 107 -16
FC Barcelona 84 88 -4
Crvena Zvezda Meridianbet Belgrade 73 103 -30

Game Analysis

Home court and stronger team ratings do most of the work for ASVEL, with recent wins over Baskonia and Partizan reinforcing a better current picture. The model also gets a smaller lift from ASVEL’s ballhandling, steals and foul profile, plus its rebounding and paint presence. Bayern’s scoring and shooting are the counterweight, led by Andreas Obst, projected for 9.6 points and 2.1 threes.

Crowder is projected for 13.5 points and a 15.4 PIR, giving ASVEL its strongest all-round expected contribution. Joel Bolomboy’s projected 4.9 rebounds can support the home side’s inside advantage, while Bayern’s Austin Wiley is projected for 5.4 rebounds and could help contest that area. Bayern’s recent defeats, including a 73-103 loss to Crvena Zvezda, underline the gap in form.

Final Prediction

Bayern can overturn the projection if Obst’s perimeter shooting produces enough scoring to offset ASVEL’s rebounding and paint advantage.

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