Reaction time and memory norms, open data

Lab references

These are not compared with your score directly, because the formats differ, but they anchor the online figures.

The Headgame norm

Headgame will publish its own norm, split by type of screen, touch or mouse, and by language, once each test reaches 1,000 games. Each version will carry its date and its exact sample. The collection is not switched on yet. When it is, each game will send only the test, the raw score, the type of pointer, the language of the page and the day, with no identifier, no cookie and no IP address kept.

Limits of these norms

Human Benchmark players are volunteers who chose to play, on every kind of device, with no control for cheating. The reaction time distribution still contains 79 games under 100 ms, which are anticipations (Human Benchmark, 2026). Human Benchmark also states a median of 273 ms on its own page, computed over all clicks, while the distribution embedded in its code, the one used here, has a median of 228 ms. It is most likely a subset, such as best scores, and its exact origin is not documented.

Headgame rejects reaction times under 100 ms, and never shows a percentile for a test without a named norm.

Download and citation

The CSV file below lists every bin of the four distributions, test, score and number of games. It restates public Human Benchmark distributions for reference, so cite Human Benchmark as the origin of the data. The Headgame norm, once published, will be released under the Creative Commons BY 4.0 licence. Suggested citation, Headgame (2026), Reaction time and memory norms, from Human Benchmark distributions read on 13 October 2026, brainovr.app/science/norms.

Reaction time test

n 70,940, median 228 ms

Human Benchmark, 70,940 games, score distribution read on 13 October 2026.

Percentile	Score	Reading
P10	178 ms	10% of games are this fast or faster
P25	199 ms	25% of games are this fast or faster
P50	228 ms	50% of games are this fast or faster
P75	264 ms	75% of games are this fast or faster
P90	308 ms	90% of games are this fast or faster
P99	552 ms	99% of games are this fast or faster

Play the test →

Sequence memory test

n 35,868, median 9

Human Benchmark, 35,868 games, score distribution read on 13 October 2026.

Percentile	Score	Reading
P10	5	at least 10% of games end at this score or lower
P25	7	at least 25% of games end at this score or lower
P50	9	at least 50% of games end at this score or lower
P75	12	at least 75% of games end at this score or lower
P90	15	at least 90% of games end at this score or lower
P99	25	at least 99% of games end at this score or lower

Play the test →

Chimp test

n 27,233, median 10

Human Benchmark, 27,233 games, score distribution read on 13 October 2026.

Percentile	Score	Reading
P10	8	at least 10% of games end at this score or lower
P25	9	at least 25% of games end at this score or lower
P50	10	at least 50% of games end at this score or lower
P75	11	at least 75% of games end at this score or lower
P90	13	at least 90% of games end at this score or lower
P99	19	at least 99% of games end at this score or lower

Play the test →

Number memory test

n 24,084, median 9

Human Benchmark, 24,084 games, score distribution read on 13 October 2026.

Percentile	Score	Reading
P10	7	at least 10% of games end at this score or lower
P25	8	at least 25% of games end at this score or lower
P50	9	at least 50% of games end at this score or lower
P75	10	at least 75% of games end at this score or lower
P90	12	at least 90% of games end at this score or lower
P99	17	at least 99% of games end at this score or lower

Play the test →

Download the norms as CSV

Sources

1. Woods D.L., Wyma J.M., Yund E.W., Herron T.J., Reed B. (2015). Factors influencing the latency of simple reaction time. Frontiers in Human Neuroscience 9, 131. doi.org/10.3389/fnhum.2015.00131
2. Human Benchmark, score distributions embedded in humanbenchmark.com, read on 13 October 2026. Reaction time n 70 940, sequence memory n 35 868, chimp test n 27 233, number memory n 24 084. humanbenchmark.com
3. Woods D.L., Kishiyama M.M., Yund E.W. et al. (2011). Improving digit span assessment of short-term verbal memory. Journal of Clinical and Experimental Neuropsychology 33(1), 101 to 111. PMC2978794. doi.org/10.1080/13803395.2010.493149
4. Tombaugh T.N., Kozak J., Rees L. (1999). Normative data stratified by age and education for two measures of verbal fluency. Archives of Clinical Neuropsychology 14(2), 167 to 177. doi.org/10.1093/arclin/14.2.167