Demarcation of Intensity From 3 to 5 Zones Aids in Understanding Physiological Performance Progression in Highly Trained Under-23 Rowing Athletes.

ABSTRACT: Watts, SP, Binnie, MJ, Goods, PSR, Hewlett, J, Fahey-Gilmour, J, and Peeling, P. Demarcation of intensity from 3 to 5 zones aids in understanding physiological performance progression in highly trained under-23 rowing athletes. J Strength Cond Res 37(11): e593-e600, 2023-The purpose of this investigation was to compare 2 training intensity distribution models (3 and 5 zone) in 15 highly trained rowing athletes ( n = 8 male; n = 7 female; 19.4 ± 1.1 years) to determine the impact on primary (2,000-m single-scull race) and secondary (2,000-m ergometer time trial, peak oxygen consumption [V̇O 2 peak], lactate threshold 2 [LT2 power]) performance variables. Performance was assessed before and after 4 months training, which was monitored through a smart watch (Garmin Ltd, Olathe, KS) and chest-strap heart rate (HR) monitor (Wahoo Fitness, Atlanta, GA). Two training intensity distribution models were quantified and compared: a 3-zone model (Z1: between 50% V̇O 2 peak and lactate threshold 1 (LT1); Z2: between LT1 and 95% LT2; Z3: >95% LT2) and a 5-zone model (T1-T5), where Z1 and Z3 were split into 2 additional zones. There was significant improvement in LT2 power for both male (4.08% ± 1.83, p < 0.01) and female (3.52% ± 3.38, p = 0.02) athletes, with male athletes also demonstrating significant improvement in 2,000-m ergometer time trial (2.3% ± 1.92, p = 0.01). Changes in V̇O 2 peak significantly correlated with high-quality aerobic training (percent time in T2 zone; r = 0.602, p = 0.02), whereas changes in LT2 power significantly correlated with "threshold" training (percent time in T4 zone; r = 0.529, p = 0.04). These correlations were not evident when examining intensity distribution through the 3-zone model. Accordingly, a 5-zone intensity model may aid in understanding the progression of secondary performance metrics in rowing athletes; however, primary (on-water) performance remains complex to quantify.

Concurrent validity of the CORE wearable sensor with BodyCap temperature pill to assess core body temperature during an elite women's field hockey heat training camp.

Wearable temperature sensors offer the potential to overcome several limitations associated with current laboratory- and field-based methods for core temperature assessment; however, their ability to provide accurate data at elevated core temperatures (Tc) has been questioned. Therefore, this investigation aimed to determine the concurrent validity of a wearable temperature sensor (CORE) compared to a reference telemetric temperature pill (BodyCAP) during a team-sport heat training camp prior to the 2020 Olympic Games. Female field hockey players (n = 19) in the Australian national squad completed 4 sessions in hot conditions where their temperature was monitored via CORE and BodyCAP. Concurrent validity of the wearable CORE device was determined with reference to the ingested BodyCAP pill. Lin's Concordance Correlation Coefficients determined there was "poor" agreement between devices during all sessions. Mean bias demonstrated that CORE underestimated Tc in all sessions (-0.06°C to -0.34°C), with wide mean 95% confidence intervals (±0.35°C to ±0.56°C). Locally estimated scatterplot smoothing regression lines illustrated a non-linearity of error, with greater underestimation of Tc by the CORE device, as Tc increased. The two devices disagreed more than ±0.3°C for 41-60% of all data samples in each session. Our findings do not support the use of the CORE device as a valid alternative to telemetric temperature pills for Tc assessment, particularly during exercise in hot conditions where elevated Tc are expected.

The CORE wearable sensor is not a valid alternative to telemetric temperature pills for Tc assessment, particularly during exercise in hot conditions where elevated Tc are expected.Compared to reference Tc data provided by a validated, ingestible telemetric temperature pill, the CORE device demonstrated "poor" agreement between devices during all sessions in this investigation.There was a non-linear bias which tended to underestimate Tc to a greater extent as Tc increased (but with wide confidence intervals), with 41-60% of all data exceeding a threshold error of ±0.3°C.

Post-game recovery of isometric hamstring strength in a high-risk hamstring strain injury group throughout an Australian Football League season.

This study sought to investigate post-game hamstring strength recovery of 26 Australian Football League (AFL) players with a previous hamstring strain injury (HSI) across an AFL season. Maximal unilateral isometric knee flexion strength was assessed using an externally fixed dynamometer, and inter-session reliability was measured during the pre-season period. Linear mixed effects models investigated the influence of numerous variables on post-game hamstring strength decrement (relative change between initial weekly test and individual baseline) and individual within-week strength change following gameplay. The test demonstrated good inter-tester reliability (ICC = 0.81-0.88; CV = 6.73-7.33), and an acceptable level of error (MAE = 5.77-7.14%). Player as a random effect strongly influenced post-game strength decrement and within-week strength change (marginal R2 = 0.185-0.407; conditional R2 = 0.455-0.654). Within-week hamstring strength change was strongly determined by post-game strength decrement alone (estimate = 0.51, 95% CI = -0.66- -0.36 ; η2 = 0.32; P=<0.001) and in interaction with number of days post-game (estimate = 0.43, 95% CI = 0.20-0.66; η2 = 0.096; P=<0.001). This study shows the importance of early individual assessment of post-game hamstring strength in players with prior hamstring injury and could be valuable to inform post-game hamstring recovery in future applications.

Subsequent Injury Risk Is Elevated Above Baseline After Return to Play: A 5-Year Prospective Study in Elite Australian Football.

BACKGROUND: The risk of sustaining a subsequent injury is elevated in the weeks after return to play (RTP) from an index injury. However, little is known about the magnitude, duration, and nature by which subsequent injury risk is increased. PURPOSE: To quantify and describe the risk of injury in a 12-week period after RTP from an index injury in Australian football players. STUDY DESIGN: Cohort study; Level of evidence, 2. METHODS: Injury data were collected from 79 players over 5 years at 1 Australian Football League club. Injuries were classified with the Orchard Sports Injury Classification System and by side of the body. Furthermore, injury severity was classified as time loss (resulting in ≥1 matches being missed) or non-time loss (no matches missed). Subsequent injury was categorized with the SIC-2.0 model and applied to the data set via an automated script. The probability of a time loss subsequent injury was calculated for in-season index injuries for each week of a 12-week period after RTP via a mixed effect logistic regression model. RESULTS: Subsequent injury risk was found to be highest in the week of RTP for both time loss injuries (9.4%) and non-time loss injuries (6.9%). Risk decreased with each week survived after RTP; however, it did not return to baseline risk of participation (3.6%). CONCLUSION: These findings demonstrate that athletes returning to play are at an increased risk of injury for a number of weeks, thus indicating the requirement for tertiary prevention strategies to ensure that they survive this period.