本研究旨在暸解排球教練請求暫停因素與專業知識認知彼此間的典型相關及兩者之間適配的模式。研究對象為參加中華民國92 學年大專院校、高中及國民中學排球聯賽之275名教練，並以自編之『排球教練請求暫停因素與專業知識認知量表』為研究工具進行調查，所得資料以主成份分析法求得請求暫停因素之七個構面與專業知識認知之四個構面，繼續探討請求暫停因素與專業知識認知間的線性組合，最後再根據典型相關分析（Canonical Correlation Analysis）結果，建構一個請求暫停因素與專業知識認知間的過配結構方程棋式（Structural Equation Mode1ing）。結果發現： （一）專業知識對教練暫停因素的解釋量為23.0%，而大部分的解釋力來自第一對典型因素，而第二對典型因素的解釋力則較低。 （二）第一對與第二對典型相關，經找出典型加權、典型因素及典型相關係數結果，以公式表示如下： χ1=-0.512×基礎學科-0.740×技術理論-0.931×應用學科-0.456×實習 η1=-0.797×防守-0.740×情緒-0.681×攻擊-0.506×生理-0.785×臨場-0.618× 戰術-0.515×策略 χ2=0.841×基礎學科+0.165×技術理論+0.193×應用學科+0 244×實習 η2=0.115×防守+0.524×情緒-0.089×攻擊-0.054×生理-0.109×臨場-0 468×戰術-0.230×策略 （三）請求暫停各因素與專業知識認知之各因素，經LISREL 的適配模式統計結果，以模式一的配過程度最好，其χ2值比率為2.97、GFI為0.908、AGFI 為0.905、CFI 為0.994、RMR 為0.042。

　　The purpose of this study was to investigate the canonical correlation analysis and structural equation modeling between time out factors and professional knowledge of volleyball coaches. Subjects were 275 volleyball coaches who have coached in the 2003 national collegiate, senior high school and junior high school league competitions. The investigation procedure was carried out by a self-designed questionnaire for time out request factors and professional knowledge of volleyball coaches. Seven time out factors and four professional knowledge factors were obtained from principal component analysis and linear relationship between the time out factors and professional knowledge were further investigated. The structural equation modeling was established after the canonical correlation was used for final analysis. The results show: 1. The explain ratio for professional knowledge to time out factor is 23 %, and most of the explain ratio was coming from the first pair of the canonical correlation. 2. The first pair and the second pair of canonical correlation were expressed in the formula below after the finding of canonical weighting, canonical factor and canonical correlation coefficient. χl=-0.512×basic course-0.740×technological theories -0.931×application course-0.456×practical training η1 =-0.797×defend-0.740× mood-0.681×attack-0.506x physiology-0.785×real-time performance-0.618×tactics-0.515×strategy χ2=0.841×basic course +0.165×technological theories +0.193×application course+0.244×practical training η2=0.115×defend +0.524×mood -0.089×attack -0.054×physiology -0.109×real-time performance -0.468×tactics -0.230×strategy 3. After statistic calculation for LISREL's modeling for time out factor and professional knowledge factor, the finding was that model one is the better one withχ2value ratio of 2.97, GFI is 0.908, AGFI is 0.905, CFI is 0.994, RMR is 0.042.