What changed?
I organize the story around observable outcomes: jump height, sprint time, segment speed, and strength.
A small dataset needs stricter honesty.
This is a longitudinal case study of one developing athlete—not a controlled experiment and not a training prescription.
What might be noise?
Daily readiness, equipment, surface, warm-up, hand timing, and remembered measurements can all shift a result.
What changed together?
Training, maturation, technique, body composition, injury, and rehabilitation overlap, preventing a clean causal conclusion.
Will it repeat?
The next official races and repeated standardized tests matter more than any single prediction.
01
Keep estimates visible
Use ≈ or ~ and explain their origin.
02
Preserve old observations
The 11.45 PB does not erase the 12.30 first race; together the official marks show change.
03
Do not fill gaps
Missing 30m data stays missing.
04
Separate association from cause
A change point is a hypothesis generator, not proof.