Dortmund vs Hamburg prediction & probabilities (2026-08-29)

Bundesliga

Dortmund vs Hamburg Win to Nil

2026-08-29 · 17:30
Win to Nil33.0%Most likely win to nil
Best predictionMost likely win to nil · 33.0%A moderate lean, nothing emphatic. Calibrated, not a tip.
33%

model probability

ConvictionModerate

Expert AI analysis

The headline read is Most likely win to nil at 33.0%, its strongest read on the Win to Nil market. On the result, Dortmund are favoured at 71.6%, so game state could swing this market. Their last 5 meetings have averaged 3.0 goals a game. These are the model’s own calibrated numbers, not betting advice.

Win to Nil

Dortmund win to nil33.0%

Hamburg win to nil6.3%

Probability a side wins without conceding, derived from the model score matrix. Calibration-graded, not a tip.

In-depth analysis

71.6%Favoured: Dortmund
55.1%Both Teams to Score
61.4%Over 2.5 goals

These are calibrated model probabilities, not tips. Calibration is our edge, not beating the market.

Model lenses

Different analytical lenses our model applies to the same calibrated data, not separate tipsters, and never a tip.

The CalibratorRaw model read: 33.0% on Win to Nil, graded against real out-of-sample results, no odds attached.
The TacticianSees an open, higher-tempo game from the 61.4% over 2.5 read.
The ScoutDortmund are the model’s pick on the result at 71.6%, a lean on probability, never on price.
The RealistThis one sits near a coin-flip, the honest read is low conviction, no strong lean.

Match outlook

Dortmund71.6%

Draw17.3%

Hamburg11.1%

The model leans Dortmund to win. See the full prediction →

Form & head-to-head

DortmundLWLWW
HamburgLLWWD

Last 5 meetings: Dortmund 4 · 1 draws · Hamburg 0 · 3.0 goals/game.

FAQ

How is this probability calculated?
We fit a goals and markets model (Dixon-Coles plus an xG strength model and an ensemble) on real match data, then calibrate the output against out-of-sample results. It is a calibrated model probability, not an odds-derived tip.

Is this a betting tip?
No – these are calibrated model probabilities, graded against real results. We publish our full track record, including the misses, and never claim to beat the closing market.

Overall model accuracy

We don’t yet publish a graded Win to Nil-specific track record, so this is our overall accuracy across every 1X2 call, graded out-of-sample, updated daily.

0.0097Calibration error (1X2)
47.7%Top-pick hit rate (1X2)
54,671Matches graded

Predictions & track record updated 29 Jul 2026. See the full, dated track record →

AI experts on this match

Open paper-trading picks from our model-strategy experts, a transparent lab, never advice.

Expert Pick
sot_specialist v1.0 sot_over_6.5

See all experts & their track records →

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Model probabilities, calibration-graded, not a tip. We publish our track record, including the misses. 18+. For information only, not betting advice. If gambling is a problem, visit BeGambleAware.