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| Format: | Preprint |
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2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2601.15327 |
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| _version_ | 1866908780540723200 |
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| author | Yoshizawa, Masatsugu Kawamoto, Yuta Takeshita, Daisuke |
| author_facet | Yoshizawa, Masatsugu Kawamoto, Yuta Takeshita, Daisuke |
| contents | In many competitive settings, from education to politics, rules do not reward effort evenly, and thresholds (e.g., grade cutoffs or electoral majorities) make some moments disproportionately important. Success thus depends on efficiently allocating limited resources. However, empirical demonstration has been difficult because effort allocation is rarely observable and feedback is often delayed, limiting our understanding of expertise. Professional tennis provides an ideal natural experiment. Because each game resets after a player wins four points and points in a lost game are wasted, the value of a point varies sharply across scores. Efficient allocation should therefore win games without wasting points, conserving resources for future games. Such allocation manifests in score-dependent point-winning probabilities, from which we derive each player's Pareto frontier-the theoretical limit of the trade-off between game-winning probability and the expected points per game. Here, we show that top players operate closer to this frontier, converting points to game wins more efficiently. Optimal strategies reduce the probability of winning points when the player is far behind (e.g.,0-2, 0-3). This behavior is psychologically difficult-letting go of the current game-but represents a rational energy conservation strategy. Top players exhibit this pattern especially in return games, where winning points is harder than in service games, requiring them to drastically vary their efforts, consistent with game-theoretic predictions. These findings suggest that elite performance reflects efficient adaptation to rule-created value structures; knowing when to give up may be as fundamental to expertise as knowing when to compete. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_15327 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Rules Create Unequal Rewards: Elite Tennis Players Allocate Resources Efficiently Yoshizawa, Masatsugu Kawamoto, Yuta Takeshita, Daisuke Computer Science and Game Theory 91A05, 60J20, 90C29 G.3; J.4; G.1.6 In many competitive settings, from education to politics, rules do not reward effort evenly, and thresholds (e.g., grade cutoffs or electoral majorities) make some moments disproportionately important. Success thus depends on efficiently allocating limited resources. However, empirical demonstration has been difficult because effort allocation is rarely observable and feedback is often delayed, limiting our understanding of expertise. Professional tennis provides an ideal natural experiment. Because each game resets after a player wins four points and points in a lost game are wasted, the value of a point varies sharply across scores. Efficient allocation should therefore win games without wasting points, conserving resources for future games. Such allocation manifests in score-dependent point-winning probabilities, from which we derive each player's Pareto frontier-the theoretical limit of the trade-off between game-winning probability and the expected points per game. Here, we show that top players operate closer to this frontier, converting points to game wins more efficiently. Optimal strategies reduce the probability of winning points when the player is far behind (e.g.,0-2, 0-3). This behavior is psychologically difficult-letting go of the current game-but represents a rational energy conservation strategy. Top players exhibit this pattern especially in return games, where winning points is harder than in service games, requiring them to drastically vary their efforts, consistent with game-theoretic predictions. These findings suggest that elite performance reflects efficient adaptation to rule-created value structures; knowing when to give up may be as fundamental to expertise as knowing when to compete. |
| title | Rules Create Unequal Rewards: Elite Tennis Players Allocate Resources Efficiently |
| topic | Computer Science and Game Theory 91A05, 60J20, 90C29 G.3; J.4; G.1.6 |
| url | https://arxiv.org/abs/2601.15327 |