Traditional tennis rating systems, such as Elo, summarize overall player strength but do not isolate the independent value of serving. Using point-by-point data from Wimbledon and the U.S. Open, we develop serve-specific player metrics to isolate serving quality from overall performance. For each tournament and gender, we fit logistic mixed-effects models using serve speed, speed variability, and placement features, with crossed server and returner random intercepts capturing unobserved server and returner-strength effects. We use these models to estimate Server Quality Scores (SQS) that reflect players' serving ability. In out-of-sample tests, SQS shows stronger alignment with serve efficiency (measured as points won within three shots) than weighted Elo. Associations with overall serve win percentage are smaller and mixed across datasets, and neither SQS nor wElo consistently dominates on that outcome. These findings highlight that serve-specific metrics complement holistic ratings and provide actionable insight for coaching, forecasting, and player evaluation.

翻译：传统的网球评级系统（如Elo）虽能概括球员的整体实力，但未能独立衡量发球环节的独立价值。利用温网和美网的逐分数据，我们开发了专门针对发球的球员度量指标，以将发球质量从整体表现中分离出来。针对每项赛事和性别，我们使用发球速度、速度变异性和落点特征拟合了逻辑混合效应模型，并通过交叉的发球方与接发球方随机截距来捕捉未观测到的发球方与接发球方实力效应。基于这些模型，我们估算了反映球员发球能力的发球质量分数（SQS）。在样本外测试中，SQS与发球效率（以前三拍内得分衡量）的关联度高于加权Elo。与整体发球得分率的相关性较弱且在不同数据集间存在差异，且在该指标上SQS与加权Elo均未表现出稳定优势。这些发现表明，专门针对发球的度量指标可补充整体评级体系，并为教练指导、比赛预测和球员评估提供可操作的见解。