Figure 2

The impact of performance on visibility. The Wikipedia page-views \(W(t)\) for all players vs. the various measures of individual performance: (A) the rank of a player \(r(t)\); (B) the tournament value \(V(t)\); (C) the number of matches the player participates in during a tournament \(n(t)\); (D) the rivals term \(\Delta r(t) H(\Delta r) /r(t)\); (E) the number of years active \(Y(t)\). The Wikipedia visits, each corresponding to \(\Delta t\approx17\) day bins, are shown in grey while the red dots correspond to binned averages. In (C), up to \(n(t)=5\) (where most tournaments end) \(W(t)\) increases with \(n(t)\) (Figure 2(C)). The jump for \(n(t)=6\) and 7 corresponds to the semi-final and final matches of the most watched tennis tournaments, offering disproportionately more visibility. In (E), after 15 years the visibility drops slightly, indicating that players with very long professional career no longer benefit from career longevity. (F) The contribution of each performance variable to visibility \(W(t)\) based on (2). Here \(\Delta\tilde {r}(t)\equiv\Delta r(t) H(\Delta r) /r(t)\) and the β-coefficients result from a multivariate regression analysis of the form \(\log y=\sum_{i} a_{i} \log x_{i}+c\). The dependent variable y is the Wikipedia page-view \(W(t)\); \(x_{i}\) represents one of the five independent variables (\(r(t)\), \(V(t)\), \(n(t)\), \(e^{\Delta r(t) H(\Delta r) /r(t)}\), \(Y(t)\)), and the \(a_{i}\) are the corresponding coefficients. All variables are individually significant (\(p<0.001\)).