Backtesting software statistics (2026)
Every figure below is measured by BacktestScore, from executed engine benchmarks and from pricing and capability data verified against 18 vendors' official pages. Nothing here is quoted from another publication.
Last updated August 2026. Free to cite with attribution to BacktestScore and a link to this page.
Engine benchmark statistics
- 770×In BacktestScore's August 2026 benchmark, the same SMA crossover 10/50, long-only ran 770× faster on NumPy/pandas (vectorized baseline) (0.021s) than on Backtrader (event-driven) (16.17s) over 250,000 bars.
- 3,439Across the 4 engines BacktestScore benchmarked in August 2026, each executed 3,439 trades on identical data, and all produced byte-identical trade sequences (verified by SHA-256 parity hash).
- 4BacktestScore re-runs an identical strategy specification across 4 backtesting engines and publishes the trade-parity hash for each; the benchmark harness is open source and reproducible from a fixed seed (run date 2026-08-04).
Capability statistics
- 28%Only 5 of 18 backtesting platforms (28%) support options backtesting. It is the single biggest capability gap in the category (BacktestScore, August 2026).
- 50%9 of 18 platforms (50%) ship built-in walk-forward analysis; on the rest, traders must hand-roll it around the optimiser (BacktestScore, August 2026).
- 72%13 of 18 backtesting tools (72%) can also execute live trades, meaning 5 are research-only and require a separate execution stack (BacktestScore, August 2026).
- 89%16 of 18 platforms (89%) support tick-resolution backtesting; the remainder cap out at bar data (BacktestScore, August 2026).
Pricing statistics
- 83%15 of the 18 backtesting platforms tracked by BacktestScore (83%) offer a free tier or are entirely free, as verified against official pricing pages in August 2026.
- 66 of 18 tracked backtesting tools (33%) are open source, making the backtesting category unusually open compared with the rest of retail trading software (BacktestScore, August 2026).
- 3Only 3 of 18 backtesting platforms still sell a one-time perpetual licence; the rest have moved to subscriptions or are free/open source (BacktestScore, August 2026).
Ecosystem statistics
- 28%5 of 18 backtesting tools (28%) bundle no market data at all, leaving data sourcing and its cost entirely to the trader (BacktestScore, August 2026).
- 44%Python is usable on 8 of 18 tracked backtesting platforms (44%), more than any other language (BacktestScore, August 2026).
- 56%10 of 18 backtesting platforms (56%) run an affiliate programme. That is why most "best backtesting software" rankings are written by parties paid to rank them (BacktestScore, August 2026).
- 6.6Across 18 platforms, the average ease-of-use score is 6.6/10 against an average overall score of 7.2/10. The category's defining weakness is usability, not capability (BacktestScore, August 2026).
Methodology in one paragraph
Speed and trade-parity figures come from running one identical strategy specification on every engine, on the same synthetic dataset, with the same execution assumptions and zero costs, then hashing each engine's ordered trade list to confirm they produced the same trades. Capability and pricing figures come from each vendor's official documentation and pricing page, re-verified on a rolling basis, with the verification date shown on every review. The benchmark harness is open source and reproducible from a fixed seed. Full protocol on themethodology page; raw results on thebenchmarks page.
Citing these statistics
Journalists, YouTubers and newsletter writers are welcome to use these figures. Please cite as: BacktestScore, “Backtesting software statistics 2026”, August 2026, linking tohttps://www.backtestscore.com/statistics. If you need the underlying per-platform data as CSV or a figure re-run against a specific engine version, the benchmark harness in our public repository produces both.
Educational content only, not investment advice. Benchmarks measure software behaviour, not strategy quality.