Institute
Reading a single estimate
What an adjusted time is, what its interval tells you, and what it doesn't — worked through on one real figure.
Take one number from this site: Thomas Ceccon’s adjusted time for the men’s 100 m backstroke is 51.60 s, 95% interval [51.49–51.71], computed 2026-08-20. Four things are worth knowing about that figure before you read any other number on this site.
It isn’t the time he swam
51.60 s isn’t a recorded time. Ceccon’s 14 recorded times in the window run from 50.44 s to 52.01 s, each one tied to a specific meet, date and pool length. 51.60 s is what the age–sex–pool adjustment v3.0 estimates his time would be on a common scale, once you account for age, sex category and pool length — built from all 14 races together, not any single one of them. The recorded races are listed on his page.
The interval isn’t a footnote — it’s part of the number
[51.49–51.71] is the range of values the estimate is compatible with, at 95% confidence. It isn’t a best case and a worst case, and it isn’t a prediction for his next race. It’s a statement about how precisely 14 races and the surrounding cohort pin down this particular figure. A swimmer with only 5 races in the window gets a wider interval for the same reason a poll of 50 people is noisier than a poll of 5 000: not because the smaller sample was measured less carefully, but because there’s less evidence behind it.
51.60 on its own would tell you less, not more
Drop the interval and “51.60 s” reads like a fact. It isn’t one — it’s the middle of a range, and the range is what stops us from telling you more than the data actually supports. That’s why every adjusted time on this site comes with its interval printed at the same size, plus the model version and the date that produced it. Leave any of those out and you don’t get a shorter version of the same number — you get a different, weaker one. More terms, defined the same way everywhere.
What it doesn’t tell you
It doesn’t tell you whether Ceccon will swim faster next season — this site doesn’t publish a figure that would. A development curve model shows how swimmers of his age and event have historically improved, as a spread rather than a single path. That’s a description of the cohort’s history, not a forecast for one person, and we never draw it forward for a swimmer under 18.
It also doesn’t tell you whether his club or coach caused the 51.60 s. Aniene Roma’s estimated programme effect is a separate, narrower figure with its own interval and its own limits: an association inside a fitted model, not a claim about who’s responsible for the time.