Training monitoring is about keeping track of what athletes accomplish in training, for the purpose of improving the interaction between coach and athlete. Over history there have been several basic schemes of training monitoring. In the earliest days training monitoring was about observing the athlete during standard workouts. However, difficulty in standardizing the conditions of training made this process unreliable. With the advent of interval training, monitoring became more systematic. However, imprecision in the measurement of heart rate (HR) evolved interval training toward index workouts, where the main monitored parameter was average time required to complete index workouts. These measures of training load focused on the external training load, what the athlete could actually do. With the advent of interest from the scientific community, the development of the concept of metabolic thresholds and the possibility of trackside measurement of HR, lactate, VO₂, and power output, there was greater interest in the internal training load, allowing better titration of training loads in athletes of differing ability. These methods show much promise but often require laboratory testing for calibration and tend to produce too much information, in too slow a time frame, to be optimally useful to coaches. The advent of the TRIMP concept by Banister suggested a strategy to combine intensity and duration elements of training into a single index concept, training load. Although the original TRIMP concept was mathematically complex, the development of the session RPE and similar low-tech methods has demonstrated a way to evaluate training load, along with derived variables, in a simple, responsive way. Recently, there has been interest in using wearable sensors to provide high-resolution data of the external training load. These methods are promising, but problems relative to information overload and turnaround time to coaches remain to be solved.

The aims of this study were to measure the aerodynamic drag in professional cyclists, to obtain aerodynamic drag reference values in static and effort positions, to improve the cyclists' aerodynamic drag by modifying their position and cycle equipment, and to evaluate the advantages and disadvantages of these modifications. The study was performed in a wind tunnel with five professional cyclists. Four positions were assessed with a time-trial bike and one position with a standard racing bike. In all positions, aerodynamic drag and kinematic variables were recorded. The drag area for the time-trial bike was 31% higher in the effort than static position, and lower than for the standard racing bike. Changes in the cyclists' position decreased the aerodynamic drag by 14%. The aero-helmet was not favourable for all cyclists. The reliability of aerodynamic drag measures in the wind tunnel was high (r > 0.96, coefficient of variation < 2%). In conclusion, we measured and improved the aerodynamic drag in professional cyclists. Our results were better than those of other researchers who did not assess aerodynamic drag during effort at race pace and who employed different wheels. The efficiency of the aero-helmet, and the validity, reliability, and sensitivity of the wind tunnel and aerodynamic field testing were addressed.

R foot strike pattern: rearfoot (RF, n = 10) and midfoot (MF, n = 10) strikers. Anthropometric characteristics were measured (height, body mass, body mass index, skinfolds, circumferences, and lengths); physiological (V˙O2max, anaerobic threshold, and running economy) and biomechanical characteristics (contact and flight times, step rate, and step length) were registered during both incremental and submaximal tests on a treadmill. Results There were no significant intergroup differences in anthropometrics, V˙O2max, or anaerobic threshold measures. RF strikers were 5.4%, 9.3%, and 5.0% more economical than MF at submaximal speeds (11, 13, and 15 km·h−1 respectively, although the difference was not significant at 15 km·h−1, P = 0.07). Step rate and step length were not different between groups, but RF showed longer contact time (P < 0.01) and shorter flight time (P < 0.01) than MF at all running speeds. Conclusions The present study showed that habitually rearfoot striking runners are more economical than midfoot strikers. Foot strike pattern affected both contact and flight times, which may explain the differences in running economy....