目前在台灣的體育風氣日漸興盛，不管是棒球、籃球，甚至於排球，每次的大型比賽總是吸引許多球迷的注意力。以排球為例，亞洲四強挑戰賽已舉行數年，而國內大專院校及企業聯賽也行之有年，在這些比賽中，教練對選手的選擇及調度幾乎都以主觀的認知來決定，鮮少以較科學的分析方法來選擇選手，以至於常選用了所謂的明星選手但結果表現不佳的狀況。
本研究目的在於建立一個最佳團隊選手組成決策系統，以位置為組成基礎，利用選手技術能力對隊伍的貢獻度，組成得分最大、勝率最高的最佳團隊。根據實際比賽資料，將收集到的資料分成三部份進行分析，第一部分為選手能力分析，分析選手過去比賽之技術資料，評估選手貢獻度；第二部份為位置關鍵技術能力，藉由位置所需的攻防技術集合，配合選手貢獻度，決定位置最佳選手；最後為隊伍整體分析，以隊伍為單位，援用本研究所建立之比賽時序性，分析關鍵得失分技術、選手組合的技術相關性，以及選手技術的落點位置預測，支援教練組成最佳團隊，並以選手技術組合作為戰術運用的參考。本研究以年度實際排球比賽資料進行驗證最佳化組合的表現。
在最佳選手組成的部份，由本研究所提出的選手技術貢獻度配合位置技術權重所推薦之組合經由教練認定，可以有效整合選手在特定位置的技術，組成勝率最大之組合，教練可依此進行選手的調度。在整體隊伍技術的部份，實驗結果顯示將關鍵得失分技術的門檻值降低，將可以幫助教練獲得更多有效的資訊；利用隊伍內技術相關性，比較選手相互配合的成功率，推薦教練選手間的戰術使用；由選手技術落點表現進行預測，獲得選手技術表現傾向。本研究建置之系統透過過去比賽資料，客觀的反應選手及隊伍的表現，做為未來訓練的基準，利用決賽資料做驗證，顯示本研究多可達到80%的預測準確度，幫助教練對比賽進行即時的掌控，使隊伍能有最好的表現。

In recent years, sports in Taiwan have received more and more attentions, especially baseball, basketball and volleyball. Every large-scale match attracts many audiences. In those competitions, the coaches decide the team line-up by their subjective perception; rarely use science analyses for dispatch. It may cause the result that choosing the star players but they do not have the anticipated representation.
In this research, we focus on establishing an optimized member selection decision support system. Base on the position, we use the contribution of every player’s skill to recommend a line-up that has the highest winning rate. According to the reality matches, we divide the data into three parts. In the first part, we estimate the player’s contribution by analyzing the skill represent in the passing competitions. And second part, we find a key skill set of each position, and combine the player’s contribution to product an optimized member line-up. Finally, we use the ‘time sequence’ that our system built to analyze the whole team. Our research uses the First Level Volleyball League competitions to test and verify.
Using our digital record system, the optimized member line-up of CHNA and PCCU can match and revise the coach perception; the coach is willing to arrange the player by our recommendation. In the whole team skill analysis, the result shows that we may lower the threshold to get more key skill that the coach interested. In the interrelatedness between the skills, we compare the successful rate to recommend the strategies of player in the field. And last, our research provides a prediction of player’ skill placement, helping the coach to take corrective attack and effective defense to win the competition.

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