How the ranking works

Transparent and reproducible: data sources, matching logic, indicators and limitations.

Step 1 of 4

Key definitions

Startup

Newly founded, innovative and growth-oriented companies, at most 10 years old. Germany: checked manually by startupdetector. Austria: Austrian Startup Monitor. Switzerland: Startupticker.ch and Startup.ch. Extended with Dealroom and PitchBook.

Counts: a newly founded software or tech company

Does not count: craft businesses, one-person companies

Founder

A person who studied or worked at an academic institution in the DACH region and founded a startup in the DACH region.

Counts: a person from the U.S. with a Master's degree from a DACH university who founded in the DACH region

Does not count: a person who studied in the DACH region but founded in the U.S.

Academic institution

Higher education and research institutions that are state-recognized in Germany, Austria or Switzerland.

Counts: public and private universities, applied-research institutions

Does not count: secondary schools, accelerator programs

Step 2 of 4

From raw data to the ranking

Base data

Startups

n = 39,782n = 4,371n = 7,134

Academic institutions

n = 312n = 75n = 50

Signals

1Founder studied at the institution

Public LinkedIn profiles, Dealroom, Crunchbase, Startup.ch

2Founder worked at the institution

Public LinkedIn profiles, Dealroom, Crunchbase, Startup.ch

3Institution named on the startup website

Web scraping of up to 50 subpages, only used if signals 1 and 2 give no match

Score

Score per startup-institution pair: share of the founding team's degrees and jobs at that institution. Pairs from 0.2 are counted for DACH institutions.

Ranking

AAbsolute ranking (all startups in the DACH region)

BRelative ranking (per student, per employee and per €1m budget)

Step 4 of 4

Indicators and limitations

1. Automated matching

Not every match was validated manually. Random checks found no structural or systematic bias.

2. Commercial databases

Results depend on the databases and their startup definitions, which differ slightly by country. Recent Austrian and Swiss startups may appear with a time lag.

3. Correlation, not causation

The study does not measure how much an institution actually contributed to a startup, for example through IP or an accelerator program.

Weighting

There is no composite index and no weighting. Each indicator is reported and ranked on its own.

Indicators

Startups founded, active startups, funded startups, total and median funding, startups with more than 50 employees, startup employees and time to funding. Each absolute and relative to students, employees and budget.

Data sources

StartupDetector, Austrian Startup Monitor, Startupticker.ch, Startup.ch, Dealroom, PitchBook and LinkedIn (as of Dec 2024), Crunchbase (May 2025), company websites (March 2025). Institution data: federal statistical offices of DE, AT and CH (university year 2022/23).

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FAQ

Why is a university missing?

Only state-recognized institutions are included. Relative rankings require at least 500 students, 100 employees and a €1m budget. Purely theological universities and art colleges in Germany are excluded.

Can one startup count for several universities?

Yes. If founders studied or worked at several institutions, the startup counts for each institution above the threshold. Counts are therefore not additive.

Does the ranking measure how well a university supports founders?

No. It measures entrepreneurial outcomes linked to an institution's students, alumni and staff, not the quality of support programs.

What counts as funded?

A startup is funded if financing information (dates or amounts) exists in PitchBook or Dealroom. This includes angels, VC, corporates and grants.

I found an error. Who do I contact?

Write to the contact person below. We review every reported case.

How the ranking works

Key definitions

Startup

Founder

Academic institution

FAQ

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