Key statistics on startup acquisitions, median deal sizes, time-to-exit, and acquisition multiples. Compiled from public market reports and industry data.
CC BY 4.0 Updated 2026-07-20| Metric | Value | Source |
|---|---|---|
| Global startup M&A deal volume (2025) | ~8,400 deals | Crunchbase Global M&A Report 2025 |
| Median acquisition price (seed-stage startups) | $12M | PitchBook-NVCA Venture Monitor Q4 2025 |
| Median acquisition price (Series A startups) | $45M | PitchBook-NVCA Venture Monitor Q4 2025 |
| Median time from founding to exit | 7.2 years | PitchBook Venture-backed Exit Report 2025 |
| % of exits that are acquisitions (vs IPOs) | 91% | PitchBook-NVCA Venture Monitor Q4 2025 |
| Median revenue multiple at acquisition (SaaS) | 8.4x | Software Equity Group M&A Report 2025 |
| Tech acquirer share of total M&A volume | 38% | CB Insights Tech M&A Report 2025 |
| Share of acquisitions under $100M | 72% | PitchBook M&A Report 2025 |
| Average deal due diligence period | 90 days | DealRoom M&A Process Survey 2025 |
9 data points, all sourced from publicly available industry reports and databases.
APA: GitDealFlow. (2026-07-20). Startup M&A Deal Flow Statistics 2026. Retrieved from https://gitdealflow.com/data/startup-ma-statistics/
MLA: "Startup M&A Deal Flow Statistics 2026." GitDealFlow, 2026-07-20, gitdealflow.com/data/startup-ma-statistics/.
BibTeX:
@misc{startup-ma-statistics,
author = {GitDealFlow},
title = {Startup M&A Deal Flow Statistics 2026},
year = {2026},
url = {https://gitdealflow.com/data/startup-ma-statistics/},
note = {Accessed: 2026-07-20}
}
Licensed under CC BY 4.0. Attribution required.
GitDealFlow is a public deal flow signal dataset: 350+ startup GitHub organizations across 15 sectors, refreshed weekly, with breakout teams surfacing 21 to 47 days before their round is announced. This page makes one part of that system legible: what it measures, how it is computed, and how to use it in a live sourcing workflow. The method is published end to end and falsifiable by design, with the working paper on SSRN and the dataset downloadable under CC BY 4.0.
A practical read-through of Startup M&A Deal Flow Statistics 2026: the dataset behind this page refreshes weekly across 350+ organizations and 15 sectors, and every figure shown traces to a public GitHub REST API pull. That matters for two reasons. Reproducibility: any number here can be re-derived from primary sources, which is the standard the published methodology sets for itself. Timeliness: engineering acceleration precedes announcements, so this page follows the data cadence rather than the news cycle, and the freshness endpoint always reports the exact pull date.
If Startup M&A Deal Flow Statistics 2026 is your entry point, the fastest next steps are fixed: skim the glossary for the three or four terms that anchor the topic, open the research dataset to see the raw weekly snapshots behind the summary numbers, and run one live query against the free momentum checker with a company you already know well. Seeing the signal fire on a familiar name is the quickest way to judge whether code-side sourcing belongs in your own workflow.
Every row in this table describes a completed event, which makes it a calibration set, not a watchlist. The patterns it calibrates are real: serial acquirers repeat, consolidating sectors keep consolidating, and multiples cluster by profile. What the table cannot do is tell you which company is being built toward the next row right now.
That is the leading layer's job. The weekly panel measures commit velocity (14-day windows, two-period confirmation), contributor concentration, and repository expansion across 350+ organizations in 15 sectors; breakout teams surface 21 to 47 days before their round is announced. Joined with this table's acquirer patterns, an accelerating team that fits an active acquirer's historical profile is the strongest public shortlist entry in M&A sourcing.