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Mathieu Lacome, Ben M. Simpson, Yannick Cholley, Philippe Lambert and Martin Buchheit

Purpose: To compare the peak intensity of typical small-sided games (SSGs) with those of official matches in terms of running demands and mechanical work (MechW) over different rolling average durations and playing positions. Methods: Data were collected in 21 players (25 [5] y, 181 [7] cm, and 77 [7] kg) belonging to an elite French football team. SSG data were collected over 2 seasons during typical training sessions (249 files, 12 [4] per player) and official matches (n = 12). Players’ locomotor activity was recorded using 5-Hz Global Positioning System. Total distance (m), high-speed distance (HS, distance above 14.4 km·h−1, m), and MechW (a.u.) were analyzed during different rolling average periods (1–15 min). The SSGs examined were 4v4+goalkeepers (GKs), 6v6+GKs, 8v8+GKs, and 10v10+GKs. Results: Peak total distance and HS during 4v4, 6v6, and 8v8 were likely-to-most likely lower than during matches (effect size: −0.59 [±0.38] to −7.36 [±1.20]). MechW during 4v4 was likely-to-most likely higher than during matches (1–4 min; 0.61 [±0.77] to 2.30 [±0.64]). Relative to their match demands, central defenders performed more HS than other positions (0.63 [±0.81] to 1.61 [±0.52]) during 6v6. Similarly, central midfielders performed less MechW than the other positions during 6v6 (0.68 [±0.72] to 1.34 [±0.99]) and 8v8 (0.73 [±0.50] to 1.39 [±0.32]). Conclusion: Peak locomotor intensity can be modulated during SSGs of various formats and durations to either overload or underload match demands, with 4v4 placing the greatest and the least emphasis on MechW and HS, respectively. Additionally, in relation to match demands central defenders and central midfielders tend to be the most and least overloaded during SSGs, respectively.

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Amanda J. Visek, Erin A. Olson and Loretta DiPietro

Background:

Little is known about factors affecting adherence to highly-structured and supervised exercise programs in older people.

Methods:

Healthy, inactive older (≥65 y) women (N = 30) were randomized into a 1) higher- (ATH—80% VO2peak); 2) moderate- (ATM—65% VO2peak) intensity aerobic; or 3) lower-intensity resistance (RTL; 50% VO2peak) group. All 3 groups exercised 4 days·week-1 for an average of 45 to 70 min·session-1 over 9 months. Adherence (%) was defined as the proportion of prescribed sessions (N = 144) in which subjects achieved their 1) prescribed heart rate (intensity adherence) and 2) their prescribed duration (duration adherence). Primary determinants of adherence included prescribed intensity (METs) and prescribed duration (min), as well as age, body composition, VO2peak, and exercise self-efficacy score.

Results:

Intensity adherence was nearly 100% for all 3 groups, while duration adherence was 95%, 91%, and 85% in the RTL, ATH, and ATM groups, respectively. Prescribed exercise duration was the strongest determinant of duration adherence (r = −0.72; P < .0001), independent of prescribed METs, age, VO2peak, and body composition.

Conclusions:

Due to competing lifestyle demands, exercise intensity may be less of a factor in adherence among older women than is exercise duration.

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Tatiane Piucco, Rogério Soares, Fernando Diefenthaeler, Guillaume Y. Millet and Juan M. Murias

kinetics responses. We hypothesized that (1) given the similarities previously reported for treadmill and slide board skating at submaximal and peak intensities of exercise, 10 the V ˙ O 2 kinetics response would be similar in both conditions and (2) well-trained speed skaters would have a fast (∼20 s

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Heidi R. Thornton, André R. Nelson, Jace A. Delaney, Fabio R. Serpiello and Grant M. Duthie

include removing unwanted algorithms, adding additional algorithms, including new metrics, 7 or for retrospective analysis of peak intensities of matches using rolling periods. 13 , 14 Independently processing GPS data may improve the quality of the data, and the reliability of various measures may be

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Natalie Frost, Michael Weinborn, Gilles E. Gignac, Shaun Markovic, Stephanie R. Rainey-Smith, Hamid R. Sohrabi, Ralph N. Martins, Jeremiah J. Peiffer and Belinda M. Brown

; 95%). VO 2 peak, intensity, and all other cognitive test data (one-back, Flanker, phonemic and semantic fluency, and Groton Maze errors) were normally distributed ( Mallery & George, 2016 ). For tests where a lower score denotes better performance (Trail Making Test-Part B, time in seconds; Groton

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Theofanis Tzatzakis, Konstantinos Papanikolaou, Dimitrios Draganidis, Panagiotis Tsimeas, Savvas Kritikos, Athanasios Poulios, Vasiliki C. Laschou, Chariklia K. Deli, Athanasios Chatzinikolaou, Alexios Batrakoulis, Georgios Basdekis, Magni Mohr, Peter Krustrup, Athanasios Z. Jamurtas and Ioannis G. Fatouros

difference from baseline in SEPT/1:5. b Significant difference from baseline in SEPT/1:8. c Significant difference between SEPT/1:5 and SEPT/1:8 within time point. Table 3 Peak Intensity During the 2 Protocols Expressed as Peak Speed Responses (Percentage Relative to 30-m-Sprint Speed Testing at Baseline