In the last years, prediction of sport records has received increased attention by the scientific community. In particular, it is of great interest the evaluation of the goodness of a record. The application of extreme value theory in this context is quite natural. In this work, we use the Gumbel model to analyze the annual speed records in men’s and women’s 100-meter sprint races from 2001 to 2024. We propose the use of a new calibration procedure in order to correctly estimate the probability of future records and the expected time needed to break the current world record.
Improved prediction of 100-meter sprint records
Giovanni FonsecaPrimo
;Michele Lambardi di San MiniatoPenultimo
;Valentina MameliUltimo
2025-01-01
Abstract
In the last years, prediction of sport records has received increased attention by the scientific community. In particular, it is of great interest the evaluation of the goodness of a record. The application of extreme value theory in this context is quite natural. In this work, we use the Gumbel model to analyze the annual speed records in men’s and women’s 100-meter sprint races from 2001 to 2024. We propose the use of a new calibration procedure in order to correctly estimate the probability of future records and the expected time needed to break the current world record.File in questo prodotto:
| File | Dimensione | Formato | |
|---|---|---|---|
|
Book_IES25_Definitivo_contibuto.pdf
non disponibili
Tipologia:
Versione Editoriale (PDF)
Licenza:
Non pubblico
Dimensione
1.73 MB
Formato
Adobe PDF
|
1.73 MB | Adobe PDF | Visualizza/Apri Richiedi una copia |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
