Kılcı Abdullah, Koç Muhammed Emin, Binokay Hülya, Erdoğan Ali, Kamiş Okan, Oliveira Rafael
Faculty of Sport Sciences, Department of Coaching Education, Cukurova University, Adana, 01250, Turkey.
Faculty of Sport Sciences, Department of Coaching Education, Aksaray University, Aksaray, 68100, Turkey.
BMC Sports Sci Med Rehabil. 2025 May 2;17(1):109. doi: 10.1186/s13102-025-01162-x.
The study main aim was to investigate: the relationship between running performances and market values of soccer players playing in the 2022 FIFA World Cup, by playing position and all players; the comparisons by playing position; to analyse the relationship between running metrics and market values of the highest and lowest players ranked players. The relationship between running metrics and market values of 306 soccer players who participated in the tournament and played full time, as well as the 40 players with the highest (n = 20) and lowest (n = 20) market values was analysed. Overall, there was a very weak correlation between market values and total distance (r = 0.149), zone 3 (r = 0.153), zone 4 (r = 0.139), zone 5 (r = 0.160), high-speed runs (r = 0.132), sprints (r = 0.147), and top speed (r = 0.194) for all players (p < 0.05). Defenders showed very weak positive correlation between market values and top speed (r = 0.155, p < 0.05). Midfielders showed weak positive correlations between market values and zone 4 (r = 0.302, p < 0.05) and zone 5 (r = 0.369, p < 0.001), sprints (r = 0.367, p < 0.001), and top speed (r = 0.304, p < 0.05). Forwards showed no correlations (p > 0.05). While there is no significant correlation between running metrics and market value for players with the lowest market value (p > 0.05), there was a moderate negative correlation between total distance (r=-0.577) and zone 2 (r=-0.612) for the 20 players with the highest market value (p < 0.05). Moreover, there was a weak correlation with zone 5 (r = 0.450) and a moderate correlation with the top speed values (r = 0.596) (p < 0.05). Weak correlations between soccer players' running performance and market values suggest that different running thresholds are important metrics, although other factors (e.g., technical skill, age, national and team club) may influence this relationship. In conclusion, since coaches and scouts aim to recruit relatively talented players within the limits of their budgets, selecting athletes with high aerobic and anaerobic performance, particularly those with a strong high-intensity running profile, can contribute to team success and potentially generate high transfer revenues in the future.
参加2022年国际足联世界杯的足球运动员的跑步表现与市场价值之间的关系，按比赛位置和所有球员进行分析；按比赛位置进行比较；分析排名最高和最低的球员的跑步指标与市场价值之间的关系。分析了306名参加比赛并全场出战的足球运动员以及市场价值最高（n = 20）和最低（n = 20）的40名球员的跑步指标与市场价值之间的关系。总体而言，所有球员的市场价值与总距离（r = 0.149）、3区（r = 0.153）、4区（r = 0.139）、5区（r = 0.160）、高速奔跑（r = 0.132）、冲刺（r = 0.147）和最高速度（r = 0.194）之间的相关性非常弱（p < 0.05）。后卫的市场价值与最高速度之间显示出非常弱的正相关性（r = 0.155，p < 0.05）。中场球员的市场价值与4区（r = 0.302，p < 0.05）和5区（r = 0.369，p < 0.001）、冲刺（r = 0.367，p < 0.001）以及最高速度（r = 0.304，p < 0.05）之间显示出弱正相关性。前锋之间没有相关性（p > 0.05）。虽然市场价值最低的球员的跑步指标与市场价值之间没有显著相关性（p > 0.05），但市场价值最高的20名球员的总距离（r = -0.577）和2区（r = -0.612）之间存在中度负相关性（p < 0.05）。此外，与5区存在弱相关性（r = 0.450），与最高速度值存在中度相关性（r = 0.596）（p < 0.05）。足球运动员的跑步表现与市场价值之间的弱相关性表明，不同的跑步阈值是重要指标，尽管其他因素（如技术技能、年龄、国籍和球队俱乐部）可能会影响这种关系。总之，由于教练和球探旨在在预算范围内招募相对有天赋的球员，选择具有高有氧和无氧表现的运动员，特别是那些具有强大高强度跑步能力的运动员，有助于球队取得成功，并有可能在未来产生高额转会收入。
