Monitoring Acute Effects on Athletic Performance with Mixed Linear Modeling TOM J. VANDENBOGAERDE and WILL G. HOPKINS Sport Performance Research Institute New Zealand, AUT University, Auckland, NEW ZEALAND ABSTRACT VANDENBOGAERDE, T. J. and W. G. HOPKINS. Monitoring Acute Effects on Athletic Performance with Mixed Linear Modeling. Med. Sci. Sports Exerc., Vol. 42, No. 7, pp. 1339–1344, 2010. There is a need for a sophisticated approach to track athletic performance and to quantify factors affecting it in practical settings. Purpose: To demonstrate the application of mixed linear modeling for monitoring athletic performance. Methods: Elite sprint and middle-distance swimmers (three females and six males; aged 21–26 yr) performed 6–13 time trials in training and competition in the 9 wk before and including Olympic-qualifying trials, all in their specialty event. We included a double-blind, randomized, diet-controlled crossover intervention, in which the swimmers consumed caffeine (5 mgIkg j1 body mass) or placebo. The swimmers also knowingly consumed varying doses of caffeine in some time trials. We used mixed linear modeling of log-transformed swim time to quantify effects on performance in training versus competition, in morning versus evening swims, and with use of caffeine. Predictor variables were coded as 0 or 1 to represent absence or presence, respectively, of each condition and were included as fixed effects. The date of each performance test was included as a continuous linear fixed effect and interacted with the random effect for the athlete to represent individual differences in linear trends in performance. Results: Most effects were clear, owing to the high reliability of performance times in training and competition (typical errors of 0.9% and 0.8%, respectively). Performance time improved linearly by 0.8% per 4 wk. The swimmers performed substantially better in evenings versus mornings and in competition versus training. A 100-mg dose of caffeine enhanced performance in training and competition by È1.3%. There were substantial but unclear individual responses to training and caffeine (SD of 0.3% and 0.8%, respectively). Conclusions: Mixed linear modeling can be applied successfully to monitor factors affecting performance in a squad of elite athletes. Key Words: ELITE ATHLETES, CAFFEINE, METHOD, TRAINING T he primary aim of sport scientists working with elite athletes is to assess the effects of training and nutri- tional or other treatments on performance. Several mathematical models have been suggested for analyzing effects of treatments on performance (2,4,11,17,28,29). Repeated-measures ANOVA is a commonly used method, but it can lead to loss of power when there are missing values in a series of repeated measurements: either the en- tire trial with a missing value has to be deleted or the entire series of values of each subject with a missing value has to be deleted. A better approach is mixed modeling, which overcomes the missing value problem and, in addition, allows specification and estimation of different sources of variation or error (30). For example, in tracking perfor- mance using training and competition time trials, perfor- mance could be more variable in training. In this article, we report an analysis with mixed modeling in which we have devised a novel coding method to account for various factors that could affect performance. We monitored performance in a squad of elite swimmers pre- paring for Olympic-qualifying trials and assessed changes in performance arising from training versus competition, morning versus evening swims, and with use of caffeine or placebo. METHODS Subject characteristics. Nine highly trained swim- mers (age range = 21–26 yr) competing at the international level and specializing in 400-m freestyle (n = 1), 100-m backstroke (n = 1), 200-m backstroke (n = 2), 100-m but- terfly (n = 1), 200-m butterfly (n = 2), 100-m breaststroke (n = 1), or 400-m individual medley (n = 1) took part in this study. Subjects’ characteristics are shown in Table 1. The swimmers were performing a similar training program consisting of two 2-h swim sessions each day, except for Wednesday and Saturday (morning session only) and Sun- day (no session). Sessions started at 6:30 a.m. and 4 p.m. All subjects gave written informed consent as required by the AUT University Ethics Committee, which approved this study. Study design. The swimmers performed 2–8 time trials in training and 2–7 in competition in the 9 wk before and Address for correspondence: Tom J. Vandenbogaerde, Division of Sport and Recreation, AUT University, Private Bag 92006, Auckland 0627, New Zealand; E-mail: tvdb34@hotmail.com. Submitted for publication September 2009. Accepted for publication December 2009. 0195-9131/10/4207-1339/0 MEDICINE & SCIENCE IN SPORTS & EXERCISE Ò Copyright Ó 2010 by the American College of Sports Medicine DOI: 10.1249/MSS.0b013e3181cf7f3f 1339 APPLIED SCIENCES Copyright © 2010 by the American College of Sports Medicine. Unauthorized reproduction of this article is prohibited.