# New inequality indicators for team ranking in multi-stage female professional cyclist races

## TL;DR

This paper introduces new inequality indicators for ranking female cycling teams in multi-stage races, providing a methodology and numerical illustrations to analyze team strategies and competitiveness.

## Contribution

It develops novel inequality measures and a methodology for their construction, applied to hierarchical team rankings in major female cycling races.

## Key findings

- New indicators like 'leadership gap' and 'competition temperature' reveal team strategy differences.
- Numerical illustrations on 2023 races demonstrate the indicators' effectiveness.
- Analysis highlights the 'crucial core' of most competitive teams.

## Abstract

Cycling competition is highly interesting since the team ranking is based on the best performance of some subset of team members. The paper develops new inequality indicators, a methodology to construct them, and numerical illustrations allowing to provide operative arguments in their favor. The numerical illustrations subsequently deal with hierarchical ranking indicators of (female) cyclist teams, competing in multi-stage races. For the illustration, the 2023 editions of the most famous long races for females are considered: 34th Giro d'Italia Donne, 2nd Tour de France Femmes, 9th Vuelta Femenina. Several classical ranking indicators are recalled and adapted to the study cases. The most usual indicator, $T_L$, is based on the riders arriving time for the various stages, i.e., according to Union Cycliste Internationale (UCI) standard rules. One also uses another indicator, $A_L$, which requires that the riders finish the race, whence each stage, in order to define the race best team. Another contribution of the paper derives from specific developments of these indicators, thereby leading to new measures: the ''leadership gap" based on $A_L-T_L$, and the ''competition temperature", based on entropy. It is argued that the numerical values point to differences in team strategy based on rider skill levels. The ranking of contributions to indicators allow to observe the "crucial core" made of the most competitive teams.