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It seems that one cannot find many papers relating entropy to sportcompetitions. Thus, in this paper, I use (i) the Shannon intrinsic entropy($S$) as an indicator of "teams sporting value" (or "competition performance")and (ii) the Herfindahl-Hirschman index (HHi) index as a "teams competitivebalance" indicator, in the case of (professional) cyclist multi-stage races.The 2022 Tour de France and 2023 Tour of Oman are used for numericalillustrations and discussion. The numerical values are obtained from classicaland and new ranking indices which measure the teams "final time", on one hand,and "final place", on the other hand, based on the "best three" riders in eachstage, but also the corresponding times and places throughout the race, forthese finishing riders.  The analysis data demonstrates that the constraint, "only the finishingriders count", makes much sense for obtaining a more objective measure of "teamvalue" and team performance", at the end of a multi-stage race. A graphicalanalysis allows to distinguish various team levels, with in each aFeller-Pareto distribution, thereby pointing to self-organized processes. In sodoing, one hopefully better relates objective scientific measures to sport teamcompetitions, and, besides, even proposes some paths to elaborate onforecasting through standard probability concepts.

Shannon Entropy and Herfindahl-Hirschman Index as Team's Performance and Competitive Balance Indicators in Cyclist Multi-Stage Races