本研究旨在運用特殊的演算法評估ATP網球選手的比賽績效，並且據以提出改善方案，以供受評選手參考。本研究所採用的研究方法具有二個特別之設計，其一為異於已發表有關網球選手績效評估之文獻，運用專家群的主觀評估方式；其二為運用簡易的線性代數方法－二維模糊語意演算法，使比賽績效的評估得以有效率地完成；就作者能力範圍內所能知，此演算法尚未在國內、外運動領域的研究文獻中被採用過。另外，本研究引用已發表文獻的九項評估指標，並以七位國內資深的教練/教授/教師組成專家群，其意見之整合乃採用德爾菲法。由評估指標的權重分析得知，第一發球成功率及第二發球勝球率的權重明顯高於其他七項評估指標；11位選手接受評估，以Nadal的比賽績效最好、盧彥勳最差；最後，本研究分別提出通盤性及個案性的改善建議方案供給受評選手參考。本研究所採用之簡易且有效率的績效評估流程值得被推廣至其他領域，而所得結果及改善建議方案可提供給選手及教練參考，期能轉化為實際的訓練計畫，進而提升比賽績效。

This study aimed at investigating the performances of ATP players by using special evaluation mode. Two special points existed in this evaluation model. One was the adoption of subjective evaluation method by experts, which was different from the published literatures. The other was the use of linear algebraic method- 2-tuple fuzzy linguistic computing(FLC)model to complete efficiently performance evaluation task. This study continued to use the nine evaluation measures of the published literature and had seven senior coaches/ teachers in the expert group. The weight analysis of evaluation measures revealed that the weights of 1st serve percentage and 2nd serve points won are significantly higher than those of the other seven. Among the 11 players evaluated, Nadal had the best performance, while Lu had the worst. Finally, this study proposed overall and individual improvement suggestions for players and their coaches. In this study, a simple and efficient performance evaluation procedure has been conducted successfully, and was worth to be extended to other areas. The research results and improvement proposals obtained must be translated into actual training actions for improving player performance in future.