Hamburger SVBundesliga · 4 matchdays played
- Automatic relegation
- 46.4%
- Play-off
- 14.1%
- 80% position range
- 12th – 18th
50,000 simulated seasons · dated, archived computation
Risk & insuranceSporting risk,
Sporting risk,
quantified before it is covered.
A relegation, a title, a qualification, an exact score: behind every sports-related cover lies an event and its probability. We compute it across twenty-four competitions, with the full distribution, and we publish the evidence that it holds.
Who it is for
Those who carry a risk tied to the result of a match.
01
Insurers and reinsurers
Independent pricing, as a second opinion alongside your internal models, on events where claims history is thin: a relegation, a title, a qualification.
02
Contingency and performance cover
Results bonuses, prize indemnity, covered win bonuses: the exact probability of the event that triggers payment, as at the date you write the risk.
03
Performance clauses and indexed sponsorship
A contract that pays more if the club finishes in the top four and less if it goes down: the full distribution of the final position, not a prediction.
04
Relegation, promotion and their consequences
Broadcasting revenue, salary clauses, banking covenants: the probability of changing division, recomputed as the season unfolds.
05
Prize competitions and jackpot promotions
A prize promised to whoever finds the exact score or a run of results: we quantify the probability that it will be won, from the full score matrix.
What we provide
A distribution, not a point estimate.
Pricing is not about knowing the mean: it is about knowing the full shape of the uncertainty, and above all its extremes.
01
Event probabilities
Title, relegation, European qualification, final position, exact score, runs of results: the event your contract describes, not a proxy indicator.
02
Full distributions
Every position from 1 to 20 with its probability, and the intervals that go with them: the tail of the distribution, where the loss sits, is quantified.
03
Independent pricing
A second opinion, produced by a model whose calibration is public, to challenge a quotation or document an underwriting decision.
04
Scenarios and stress tests
What happens to the probability if the club loses its next three matches, or if its strength drops a notch? We replay the season under that assumption.
05
Underwriting reports
A dated, signed document: the event, the method, the figures and their limitations. Ready to be filed with the risk.
06
In-season monitoring
The risk moves after every matchday. We recompute and send you the change, so that exposure is managed rather than endured.
Worked example, real data
What is the probability that a club goes down?
These are the projections published today by our model, untouched. Change league or club: every probability comes from the same simulation of the remaining season, replayed tens of thousands of times from the estimated strengths, and carries its computation date.
Hamburger SV
Bundesliga · 16th after 4 matches (3 pts)
- Automatic relegation
- 46.4%
- Play-off
- 14.1%
- Survival without play-off
- 39.5%
- Europe
- 0.6%
- Title
- 0.0%
- Position, 80% interval
- 12th – 18th
28%
The underwriter’s reading
Across 50,000 simulated seasons, Hamburger SV finish 16th at the median, with 31 points on average. Cover that pays out on automatic relegation therefore carries a pure premium of 46.4% of the sum insured (60.5% if the play-off also triggers the cover), before loadings and margin. Read the other way, the same distribution prices a survival bonus indexed to a sponsorship contract.
Computed on 27 September 2026, after 4 matchdays · Dixon-Coles model, Monte Carlo simulation · source: Rondo public feed (competition-classement).
Why you can rely on us
A probability is not taken on trust. It is verified.
A premium is only fair if the stated “20%” really happens one time in five. We test every probability band against what actually happened, over thousands of matches, and we publish the result — including where the model is furthest off.
Each point is a probability band; its size is the number of cases. On the diagonal, the model keeps its word. Here, across 2,094 matches (1X2 result), the mean gap between forecast and observed is 2.3%.
Calibration, event by event
- Home win2,094 matches45.3%44.4%2.3%0.223
- Draw2,094 matches24.3%20.7%3.5%0.165
- Away win2,094 matches30.4%34.9%6.1%0.215
- Both teams score2,094 matches53.4%56.7%3.3%0.248
- Three or more goals in the match2,094 matches52.0%62.0%10.0%0.247
- Home side scores2,094 matches78.0%78.9%1.6%0.159
“Forecast”: the average probability given by the model; “observed”: the actual frequency. The mean deviation weights each band by its number of matches. The Brier score measures squared error (0 would be perfect). Goal totals are currently underestimated — we know it, we say so, and any report that relies on them flags it.
Public calibration
Measured on real matches and served openly through our public feed — you can check it without us.
Published methodology
The goals model, the simulation and their limitations are documented. Read the methodology →
Recomputed every matchday
Strengths and projections are refreshed as soon as a matchday has been played, across all twenty-four competitions we cover.
Dated computations
Every figure carries the date of the computation that produced it: a report is tied to a precise state of the model.
How we work
From contract to event, from event to figure.
- 01
Questionnaire
You describe the insured event, the competition, the inception date and what triggers payment. We check that it can be modelled.
- 02
Modelling
We translate the contract into an event that can be simulated and compute it on the current strengths, with any scenarios you request.
- 03
Signed report
Probabilities, distribution, assumptions and limitations, in a dated report. Every figure traces back to the computation that produced it.
- 04
Monitoring
If you wish, the same measurement is repeated after every matchday until the contract expires.
Please read before any use
Our figures are statistical estimates produced by a model: they describe uncertainty, they do not remove it. They constitute neither insurance advice, nor an underwriting recommendation, nor a guarantee of outcome.
Rondo Research is not an insurer, a broker or an insurance intermediary. The decision to cover a risk, and at what price, rests with the risk carrier. The model learns from observed play: an event the data has not yet seen (a change of ownership, an administrative sanction, a run of injuries) is not in the figure until it has shown up on the pitch.
A risk to price?
Describe the event, the competition and the expiry date. We will tell you whether it can be modelled and what we can deliver.