Robust rankings of multi-dimensional performances: An application to Tour de France racing cyclists
There is a general interest in ranking performances (e.g., in sports or policy), which essentially implies aggregating several performance dimensions. The usual approach considers a 'cardinal' linear weighting of the different single-dimensional performance indicators. We present an alternative approach, which merely requires 'ordinal' information regarding the importance of the different performance dimensions. We argue that this approach is robust with respect to alternative specifications of the (possibly non-linear) underlying performance aggregation function. An application to Tour de France racing cyclists (in the period 1953-2004) illustrates the approach. We find that Eddy Merckx, Bernard Hinault and Lance Armstrong (robustly) dominate almost all other racing cyclists in our sample, while they do not dominate each other. A net-dominance metric ranks Bernard Hinault on the first place in our sample; Eddy Merckx and Lance Armstrong follow very closely ex-aequo on the second place.
|Date of creation:||2004|
|Publication status:||Published (revised version) in Journal of Sports Economics|
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