We developed an artificial intelligence approach to predict the transfer fee of a football player. This model can help clubs make better decisions about which players to buy and sell, which can lead to improved performance and increased club budgets. Having collected data on player performance, transfer fees, and other factors that might affect a player's value, we then used this data to train a machine learning model that can accurately predict a player's impact on the game. We further passed the obtained results as one of the features to the predictor of transfer fees. The model can help clubs identify players who are undervalued and who could be sold for a profit. It can also help clubs avoid overpaying for players. We believe that our model can be a valuable tool for football clubs. It can help them make better decisions about player recruitment and transfers.

我们开发了一种人工智能方法来预测足球运动员的转会费。该模型可以帮助俱乐部在购买和出售球员时做出更好的决策，从而提高球队的表现并增加俱乐部的预算。我们采集了关于球员表现、转会费和其他可能影响球员价值的因素的数据，然后使用这些数据训练了一个可以准确预测球员对比赛影响的机器学习模型。我们进一步将得到的结果作为转会费预测器的一个特征。该模型可以帮助俱乐部识别被低估并能够盈利出售的球员，也可以帮助俱乐部避免为球员支付过高的费用。我们相信我们的模型可以成为足球俱乐部的有价值工具，帮助他们在球员招募和转会方面做出更好的决策。

基于性能洞察力的人工智能驱动足球转会费预测