Submitted:
18 October 2024
Posted:
21 October 2024
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Abstract
Keywords:
1. Introduction. The Question of Cooperation between “Teammates”
2. Methods. The Implementation of a Motor Action Dilemma
2.1. The Mechanism of Dilemma
| Prisoner’s dilemma | Cooperate | Defect |
| Cooperate | (S, S) | (VP, VS) |
| Defect | (VS, VP) | (P, P) |
| Bluegill Game | Guardian | Sneaker |
| Guardian | Satisfying for both even if each miss opportunities (S, S) | Bad for the Guardian who makes the dirty work for the benefit of the Sneaker, Very Satisfied (P, VS) |
| Sneaker | Bad for the Guardian who makes the dirty work for the benefit of the Sneaker, Very Satisfied (VS, P) | Very bad for both: it is the anarchy (‘every man for himself’) (VP, VP) |
2.2. A Motor Implementation of the Bluegill Game
2.3. The Players’ Characteristics
3. Results. Which Sports Players are the Most Egotistical?
3.1. Harsanyi vs. Nash
3.2. Logistic Regression
4. Discussion. Bad Guys Finish First
5. Conclusion. A Perverse Effect of Cooperation
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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| TeamSport: Specialists collective sports (football, basketball, etc.). The student had taken the Game Theory course module. |
N= 25 16 male players, 9 female players, 20 years (sd=0,83) |
3 mixed teams of 8 (1 replacing male) |
| IndividualSport: Specialists individual sports (gymnastics, athletics, etc.). The student had taken the Game Theory course module. |
N= 23 11 male players, 12 female players, 20 years (sd=0,26) |
3 mixed teams of 8 (1 male player who replays) |
| NoSport : Non-sporting students. The student had not taken the Game Theory course module. |
N=24 12 male players, 12 female players, 20 years (sd=0,91) |
3 mixed teams of 8 (4 male players, 4 female players) |
| TeamSport: Specialists collective sports (football, basketball, etc.). The student had taken the Game Theory course module. |
N= 25 16 male players, 9 female players, 20 years (sd=0,83) |
3 mixed teams of 8 (1 replacing male) |
| IndividualSport: Specialists individual sports (gymnastics, athletics, etc.). The student had taken the Game Theory course module. |
N= 23 11 male players, 12 female players, 20 years (sd=0,26) |
3 mixed teams of 8 (1 male player who replays) |
| NoSport : Non-sporting students. The student had not taken the Game Theory course module. |
N=24 12 male players, 12 female players, 20 years (sd=0,91) |
3 mixed teams of 8 (4 male players, 4 female players) |
| chi2=53,4 ddl=2 p<.01 | Guardian actions | Sneaker actions | Total |
| TeamSpor | 166 (with 27 shots) | 84 (with 21 shots) | 250 |
| IndividualSpor | 187 (with 24 shots) | 20 (with 4 shots) | 207 |
| NoSport | 143 (with 11 shots) | 16 (with 3 shots) | 159 |
| chi2=5,8 ddl=1 p<.04 | Nashian | Harsanyian | Total |
| Male | 13 (33,3%) | 26 (66,6%) | 39 |
| Female | 4 (12,1%) | 29 (87,9%) | 33 |
| Total | 17 (23,6%) | 55 (76,4%) | 72 |
| chi2=3,6 ddl=3 ns | Nashian | Harsanyian | Total |
| GameT+ | 5 (29,4%) | 12 (70,6%) | 17 |
| GameT= | 6 (26,1%) | 17 (73,9%) | 23 |
| GameT- | 1 (12,5%) | 7 (87,5%) | 8 |
| NoGameT | 5 (20,8%) | 19 (79,2%) | 24 |
| Total | 17 (23,6%) | 55 (76,4%) | 72 |
|
************************************* Parameters of the regression in percentages Logistic regression Modality to be explained : Nashian Reference situation: Male NoSport NoGameT ChancesRef -0.9030 0.4053 28.8 Marginal effects Odds-ratio Female -1.0137 0.36 -16.0 SportCo 0.8794 2.41 20.6 SportIn -0.4112 0.66 -7.7 GameT+ 0.2293 1.26 4.9 GameT= -0.0853 0.92 -1.7 GameT- -0.6696 0.51 -11.7 Log-v -32.6938 Cst only 80.4051 Complete model 65.3875 Khi2 15.0175 Degree freedom 6 Prob.=0.020 ** Female Khi2 3.8092, p=0.048 ** TeamSpor Khi2 4.0720, p=0.041 ** IndividualSpor Khi2 0.2812, p=0.603 ns GameT+ Khi2 0.1472, p=0.703 ns GameT= Khi2 0.0271, p=0.864 ns GameT- Khi2 0.3166, p=0.581 ns Nb of iterations= 770 |
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