The paper presents a model for estimating the transfer fees of professional footballers. We seek to improve on the literature in two dimensions. First, we utilise advanced player performance metrics to better capture the playing ability of footballers. Second, we adopt machine learning algorithms to improve out-of-sample prediction accuracy. The model proves to be a considerable improvement on linear regression, and the advanced performance metrics further improve the predictions. We use the model to identify value-for-money transfers, before assessing the past records of clubs in identifying value-for-money and find that, Liverpool and Atlético Madrid, for example, are successful at identifying value-for-money, whilst Manchester United and Barcelona are not.

本文提出了一个模型来估算职业足球运动员的转会费。我们寻求在两个方面改进文献。首先，我们利用先进的球员表现指标来更好地捕捉足球运动员的比赛能力。其次，我们采用机器学习算法来提高样本外预测的准确性。该模型被证明是对线性回归的重大改进，高级性能指标进一步改进了预测。我们使用该模型来确定转会是否物有所值，然后再评估俱乐部过去在确定物有所值方面的记录，并发现，例如，利物浦和马德里竞技在确定物有所值方面是成功的，而曼联和巴塞罗那不是。