近年來，針對籃球的實務與研究均發現單純依靠攻守紀錄表上的數據無法完整呈現與解釋籃球場上的攻擊方與防守方的互動，尤其是防守的過程中產生的事件在傳統紀錄上時常被忽略。因此美國國家籃球協會 (National Basketball Association, NBA) 在2015-16年季後賽開始統計每場比賽的拚搏數據 (Hustle stats)，包含出手干擾 (Contested shots)、擾斷 (Deflections)、進攻犯規製造 (Charges Drawn)、無主球取得 (Loose ball recovery)、掩護助攻 (screen assists) 等，但相關數據是否反映對進攻方限制的成效以及其適用範圍，則仍有待檢驗。本研究以標記分析的方式，記錄2016年里約奧運男子籃球賽共38場的比賽中，兩項具代表性的拚搏數據:出手干擾及擾斷，分別檢驗前者與對手在不同的出手位置、出手方式、出手所剩秒數下的的出手數與命中率的關聯性，以及後者與對手得分效率、失誤率間的關聯。結果發現出手干擾在三分球及跳投的情境下發生的比例較低，而在進攻剩下5秒以內的出手干擾比例較高；至於對於命中率的影響，每種情境下有出手干擾的出手命中率都比無出手干擾低，甚至會改變原先各種情境下出手命中率的趨勢。擾斷則除了發生次數較少的情境下，擾斷次數越多，越能阻擾對手進攻的流暢性，降低對手得分效率並提高對手失誤率。綜上所述，本研究發現拚搏數據確實能夠呈現籃球防守方對進攻方造成的影響，值得實務上更多的紀錄與運用，而對於數據紀錄上更精確的定義與其適用的比賽層級，仍需後續的研究探討。

Recently, applied and research field of basketball have both found that the defensive stats in traditional box scores are not sufficient for explaining the interactions of offense and defense on court. NBA therefore recorded “hustle stats” including contested shots and deflections in the 2015-16 playoff games. These performance indicators have not been systematically studied within international games, however. As a result, in this study we used notational analysis to record two vital hustle stats─contested shots and deflections─in 2016 men’s Olympic basketball games in Rio. We examined the relationship between contested shots and opponent’s field goal attempts and percentage under shot conditions such as shot location, shot type, and shot clock left. In addition, the relationship between deflections and opponent’s offensive efficiency (OE) and turnover percentage (TOV%) were also explored. Our results indicated that under conditions of three point shots and jump shots, the rate of shot contests was lower. In contrast, when shot was taken under 5 seconds, the rate was higher. In terms of field goal percentage, contested shots in all circumstances were lower than uncontested shots. This impact also made the original trend of percentage in regards to different shot conditions insignificant. Lastly, our result showed that the more deflection one team made, the lower OE and higher TOV% the other team had. In conclusion, this study was able to find the defensive impact due to hustle stats on offense in basketball, and the indicators are worth further discussion.

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