The warm-up is considered beneficial for increasing body temperature, stimulating the neuromuscular system and overall preparing the athletes for the demands of training sessions and competitions. Even when warm-up–derived benefits are slight and transient, they may still benefit preparedness for subsequent efforts. However, sports training and competition performance are highly affected by contextual factors (e.g., how is the opponent acting?), and it is not always clear what should be the preferred warm-up modalities, structure and load for each athlete and context. Further, we propose that the warm-up can also be used as a pedagogical and training moment. The warm-up may serve several different (albeit complementary) goals (e.g., rising body temperature, neuromuscular activation, attentional focus) and be performed under a plethora of different structures, modalities, and loads. The current commentary highlights the warm-up period as an opportunity to teach or improve certain skills or physical capacities, and not only as a preparation for the subsequent efforts. Moreover, the (justified) call for individualized warm-ups would benefit from educating athletes about exploring different warm-up tasks and loads, providing a broad foundation for future individualization of the warm-up and for more active, engaged, and well-informed participation of the athletes in deciding their own warm-up practices.

This study compared acceleration and deceleration demands between different training drills (compensation, rondos, small-sided games, technical) and matches, and between playing positions. Nineteen professional players were monitored during four microcycles. Efforts intensities were classified as low (25–50%), moderate (50–75%), and high (> 75%); starting speed was assessed in bandwidths (< 5 km h ⁻¹ , 5–10 km h ⁻¹ , 10–15 km h ⁻¹ , 15–20 km h ⁻¹ , 20–25 km h ⁻¹ , and > 25 km h ⁻¹ ). Paired mean differences compared activities, and independent groups contrasts compared playing positions, with 90% confidence intervals. Match elicited more high-intensity accelerations than technical drills (effect size [ES]: 1.75 [1.40, 2.28]), rondos (ES: 1.47 [0.92, 2.17]), compensation drills (ES: 1.28 [0.66, 2.09]), and small-sided games (ES: 0.64 [0.11, 1.25]), and more high-intensity decelerations than technical drills (ES: 0.74 [0.24, 1.32]) and rondos (ES: 0.53 [0.04, 1.06]). Compensation drills elicited more decelerations starting > 25 km h ⁻¹ than small-sided games (ES: 2.90 [2.18, 3.98]), technical drills (ES: 2.88 [2.11, 4.02]), and matches (ES: 2.06 [1.35, 3.08]). Fullbacks performed more high-intensity accelerations than central midfielders during small-sided games (ES: 0.10 [0.01, 0.20]), wide midfielders performed more high-intensity accelerations than central defenders during technical drills (ES: 0.05 [0.02, 0.08]), and wide midfielders performed more decelerations starting > 25 km h ⁻¹ than central defenders (ES: 0.10 [0.01, 0.20]) and central midfielders (ES: 0.12 [0.04, 0.20]) during matches. Match imposed higher demands to players than any drill, and merging compensation drills with small-sided games can be a good strategy to compensate competition acceleration and deceleration demands. Rondos drills should be carefully used due to the high deceleration demands.

Purpose: To investigate the effect of different resistance training protocols with equated volume load on acute mechanical and metabolic responses. Methods: In a randomized order, 18 men performed 8 different training protocols in the bench press exercise consisting of (sets, repetitions, intensity, and interset recoveries) 3 × 16, 40% 1-repetition maximum (1RM), 2 and 5 minutes; 6 × 8, 40% 1RM, 2 and 5 minutes; 3 × 8, 80% 1RM, 2 and 5 minutes; and 6 × 4, 80% 1RM, 2 and 5 minutes. Volume load was equalized between protocols (1920 arbitrary units). Velocity loss and effort index were calculated during the session. Movement velocity against the 60% 1RM and blood lactate concentration pre–post exercise were used to assess the mechanical and metabolic responses, respectively. Results: Resistance training protocols performed with heavy load (80% 1RM) resulted in a lower (P < .05) total number of repetitions (effect size = −2.44) and volume load (effect size = −1.79) than the scheduled ones when longer set configurations and shorter rest periods were used in the same protocol (ie, higher-training-density protocols). Protocols including a higher number of repetitions per set and shorter rest times induced higher velocity loss, effort index, and lactate concentrations than the rest of the protocols. Conclusions: Our results suggest that resistance training protocols with similar volume load but different training variables (ie, intensity, number of sets and repetitions, rest between sets) produce different responses. Implementing a lower number of repetitions per set and longer rest intervals is recommended to reduce the intrasession and postsession fatigue.

Purpose : To explore and compare physical performance across different match scheduling types, including noncongested, congested, and playoffs and considering contextual factors such as match outcomes, location, and player position of a Liga MX football club over a 4-season follow-up. Method : Thirty-seven players participated. Physical-performance metrics included total and relative distance, maximal velocity, maximal acceleration and deceleration, high-intensity break distance, explosive distance, high-speed running (HSR), number and distance of HSR actions, and number and distance of sprints. Linear mixed-model analysis was applied to compare interactions between variables using fixed factors and random factors. Results : Players showed a physical decrement during the playoffs compared with noncongested fixtures in total distance (Δ = −497 m, P = .007), relative distance (Δ = 9.10 m/min, P < .001), peak velocity (Δ = 0.54 km/h, P = .003), high-intensity break distance (Δ = 14 m, P < .001), explosive distance (Δ = 58 m, P < .001), HSR distance (Δ = 43 m, P < .001), number of HSR actions (Δ = 1.86, P < .001), sprint distance (Δ = 29 m, P < .001), and number of sprints (Δ = 1.17, P < .001). Furthermore, physical performance tended to decline during playoff matches that resulted in a loss, and this was more pronounced in winger player positions than in players with other roles such as center backs and forwards ( P ≤ .001). Conclusion : These findings highlight a physical-performance decrease during the playoffs, which can be a key determinant of match outcomes.

This study examined whether barbell velocity can accurately predict relative load during a free-weight parallel squat performed with a deliberate pause between the eccentric and concentric phases in elite Portuguese rugby players. A repeated-measures design was used, in which 25 athletes completed an incremental loading protocol up to their one-repetition maximum (1-RM) on two occasions separated by four weeks. The relationship between mean propulsive velocity (MPV) and %1-RM was analyzed using polynomial regression, and a second-order prediction equation was developed. The model showed a very strong association between MPV and %1-RM (R² = 0.95) with a standard error of estimate of 6.27 %1-RM, indicating good practical accuracy. Test–retest analyses demonstrated high stability of the load–velocity relationship (mean velocity difference: −0.01 ± 0.02 m·s⁻¹). Compared with values reported in other athletic populations, first-division rugby players displayed distinct load–velocity profiles across the full loading spectrum, underscoring the influence of execution technique and population characteristics on load–velocity behavior. These findings support the use of individualized velocity-based prescriptions rather than generalized equations. In conclusion, this study provides a technique- and population-specific prediction equation for the paused parallel back squat, offering a novel and practical tool for regulating training intensity in elite rugby players.