使用谷歌趋势测量足球运动员的受欢迎程度
Pilar Malagón-Selma1, Ana Debón1, Josep Domenech2
1Centro de Gestión de la Calidad y del Cambio, Universitat Politècnica de València, Valencia, Spain.
PloS one
|August 16, 2023
概括
这项研究引入了来自谷歌趋势的新人气指标,以预测足球运动员的市场价值. 这种新的方法在各种机器学习模型中提高了预测准确性,而低利息时期的玩家人气最具影响力.
科学领域:
- 运动分析 运动分析
- 数据科学数据科学数据科学
- 计算社会科学 计算社会科学
背景情况:
- 谷歌趋势是体育分析中未充分利用的资源,用于评估球员的受欢迎程度.
- 现有的球员估值方法往往忽视了人气指标.
- 准确的球员市场价值预测对于体育组织至关重要.
研究的目的:
- 开发和验证使用谷歌趋势来预测足球运动员市场价值的新型人气指标.
- 在不同的机器学习模型中比较这些指标的预测能力.
- 确定市场价值评估中最有影响力的受欢迎度指标.
主要方法:
- 利用谷歌趋势数据计算了六个不同的玩家受欢迎度指标.
- 开发了一种使用"人气层"来比较不平等人气的球员的方法.
- 应用累积转换因子来重新调整指标以获得统一的尺度.
- 将这些指标集成到多重线性回归,随机森林和梯度增强机器模型中.
主要成果:
- 提出的受欢迎度指标显著提高了对球员市场价值的预测.
- 将这些指标纳入所有测试的机器学习模型中减少了预测错误.
- 人气指标"Min",反映了玩家兴趣较低的时期,对市场价值产生了最实质性的影响.
结论:
- 来自谷歌趋势的新型人气指标对于预测玩家市场价值非常有价值.
- "Min"指标特别重要,突出了持续,即使较低,受欢迎程度的重要性.
- 该方法为体育分析和任何受欢迎程度影响价值的领域提供了实际应用.
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