Lazarus Brendan H, Hopkins William G, Stewart Andrew M, Aughey Robert J
Int J Sports Physiol Perform. 2018 Feb 1;13(2):140-144. doi: 10.1123/ijspp.2016-0450. Epub 2018 Feb 13.
Effects of fixture and team characteristics on match outcome in elite Australian football were quantified using data accessed at AFLtables.com for 5109 matches for seasons 2000 to 2013. Aspects of each match included number of days' break between matches (≤7 d vs ≥8 d), location (home vs away), travel status (travel vs no travel), and differences between opposing teams' mean age, body mass, and height (expressed as quintiles). A logistic-regression version of the generalized mixed linear model estimated each effect, which was assessed with magnitude-based inference using 1 extra win or loss in every 10 matches as the smallest important change. For every 10 matches played, the effects were days' break, 0.1 ± 0.3 (90% CL) wins; playing away, 1.5 ± 0.6 losses; traveling, 0.7 ± 0.6 losses; and being in the oldest, heaviest, or shortest, quintile, 1.9 ± 0.4, 1.3 ± 0.4, and 0.4 ± 0.4 wins, respectively. The effects of age and body-mass difference were not reduced substantially when adjusted for each other. All effects were clear, mostly at the 99% level. The effects of playing away, travel, and age difference were not unexpected, but the trivial effect of days' break and the advantage of a heavier team will challenge current notions about balancing training with recovery and about team selection.
利用AFLtables.com网站获取的2000年至2013年赛季5109场比赛的数据,对澳大利亚精英足球比赛中固定装置和球队特征对比赛结果的影响进行了量化。每场比赛的相关方面包括比赛之间的休息天数(≤7天与≥8天)、比赛地点(主场与客场)、旅行状态(旅行与不旅行)以及对阵双方球队平均年龄、体重和身高的差异(以五分位数表示)。广义混合线性模型的逻辑回归版本估计了每种影响,并使用基于量级的推断进行评估,将每10场比赛中多赢或多输1场作为最小的重要变化。每进行10场比赛,影响如下:休息天数,赢0.1±0.3场(90%置信区间);客场比赛,输1.5±0.6场;旅行,输0.7±0.6场;处于年龄最大、体重最重或身高最矮的五分位数,分别赢1.9±0.4场、1.3±0.4场和0.4±0.4场。年龄和体重差异的影响在相互调整后并没有大幅降低。所有影响都很明显,大多在99%的水平。客场比赛、旅行和年龄差异的影响并不意外,但休息天数的微小影响和较重球队的优势将挑战当前关于平衡训练与恢复以及球队选拔的观念。