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Øystein Sylta, Espen Tønnessen and Stephen Seiler

Purpose:

The authors directly compared 3 frequently used methods of heart-rate-based training-intensity-distribution (TID) quantification in a large sample of training sessions performed by elite endurance athletes.

Methods:

Twenty-nine elite cross-country skiers (16 male, 13 female; 25 ± 4 y; 70 ± 11 kg; 76 ± 7 mL · min−1 · kg−1 VO2max) conducted 570 training sessions during a ~14-d altitude-training camp. Three analysis methods were used: time in zone (TIZ), session goal (SG), and a hybrid session-goal/time-in-zone (SG/TIZ) approach. The proportion of training in zone 1, zone 2, and zone 3 was quantified using total training time or frequency of sessions, and simple conversion factors across different methods were calculated.

Results:

Comparing the TIZ and SG/TIZ methods, 96.1% and 95.5%, respectively, of total training time was spent in zone 1 (P < .001), with 2.9%/3.6% and 1.1%/0.8% in zones 2/3 (P < .001). Using SG, this corresponded to 86.6% zone 1 and 11.1%/2.4% zone 2/3 sessions. Estimated conversion factors from TIZ or SG/TIZ to SG and vice versa were 0.9/1.1, respectively, in the low-intensity training range (zone 1) and 3.0/0.33 in the high-intensity training range (zones 2 and 3).

Conclusions:

This study provides a direct comparison and practical conversion factors across studies employing different methods of TID quantification associated with the most common heart-rate-based analysis methods.

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Tom W. Macpherson and Matthew Weston

Purpose:

To examine the effect of low-volume sprint interval training (SIT) on the development (part 1) and subsequent maintenance (part 2) of aerobic fitness in soccer players.

Methods:

In part 1, 23 players from the same semiprofessional team participated in a 2-wk SIT intervention (SIT, n = 14, age 25 ± 4 y, weight 77 ± 8 kg; control, n = 9, age 27 ± 6 y, weight 72 ± 10 kg). The SIT group performed 6 training sessions of 4–6 maximal 30-s sprints, in replacement of regular aerobic training. The control group continued with their regular training. After this 2-wk intervention, the SIT group was allocated to either intervention (n = 7, 1 SIT session/wk as replacement of regular aerobic training) or control (n = 7, regular aerobic training with no SIT sessions) for a 5-wk period (part 2). Pre and post measures were the YoYo Intermittent Recovery Test Level 1 (YYIRL1) and maximal oxygen uptake (VO2max).

Results:

In part 1, the 2-week SIT intervention had a small beneficial effect on YYIRL1 (17%; 90% confidence limits ±11%), and VO2max (3.1%; ±5.0%) compared with control. In part 2, 1 SIT session/wk for 5 wk had a small beneficial effect on VO2max (4.2%; ±3.0%), with an unclear effect on YYIRL1 (8%; ±16%).

Conclusion:

Two weeks of SIT elicits small improvements in soccer players’ high-intensity intermittent-running performance and VO2max, therefore representing a worthwhile replacement of regular aerobic training. The effectiveness of SIT for maintaining SIT-induced improvements in high-intensity intermittent running requires further research.

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Mark Booth, Stephen Cobley and Rhonda Orr

(eg, injury characteristics and/or performance measures). Population search terms were the sport of rugby league and associated terms (“rugby*,” OR “rugby league,” OR “rugby league player*”). Intervention terms were all associated with training quantification and included “training load,” OR “training

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Iñigo Mujika

Training quantification is basic to evaluate an endurance athlete’s responses to training loads, ensure adequate stress/recovery balance, and determine the relationship between training and performance. Quantifying both external and internal workload is important, because external workload does not measure the biological stress imposed by the exercise sessions. Generally used quantification methods include retrospective questionnaires, diaries, direct observation, and physiological monitoring, often based on the measurement of oxygen uptake, heart rate, and blood lactate concentration. Other methods in use in endurance sports include speed measurement and the measurement of power output, made possible by recent technological advances such as power meters in cycling and triathlon. Among subjective methods of quantification, rating of perceived exertion stands out because of its wide use. Concurrent assessments of the various quantification methods allow researchers and practitioners to evaluate stress/recovery balance, adjust individual training programs, and determine the relationships between external load, internal load, and athletes’ performance. This brief review summarizes the most relevant external- and internal-workload-quantification methods in endurance sports and provides practical examples of their implementation to adjust the training programs of elite athletes in accordance with their individualized stress/recovery balance.

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Andrew J. Carnes and Sara E. Mahoney

, MID, and POST), in accordance with laboratory measured values. Training Quantification Training load and distribution were quantified using the modified training impulse (TRIMP) score pioneered by Lucía et al. 22 Running duration, intensity (HR), and distance (km) for each running session were

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Bent R. Rønnestad and Joar Hansen

10.1016/S1440-2440(00)80008-0 8. Verkhoshansky YV . Organization of the training process . New Stud Athl . 1998 ; 13 , 21 – 31 . 9. Sylta O , Tønnessen E , Seiler S . From heart-rate data to training quantification: a comparison of 3 methods of training-intensity analysis . Int J

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Ed Maunder, Andrew E. Kilding, Christopher J. Stevens and Daniel J. Plews

, Tonnessen E , Seiler S . From heart-rate data to training quantification: a comparison of 3 methods of training-intensity analysis . Int J Sports Physiol Perform . 2014 ; 9 ( 1 ): 100 – 107 . doi:10.1123/IJSPP.2013-0298 10.1123/ijspp.2013-0298 24408353 6. Plews DJ , Laursen PB , Kilding AE

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Roberto Baldassarre, Marco Bonifazi, Romain Meeusen and Maria Francesca Piacentini

.2014-0410 10.1123/ijspp.2014-0410 25671844 16. Sylta O , Tønnessen E , Seiler S . From heart-rate data to training quantification: a comparison of 3 methods of training-intensity analysis . Int J Sports Physiol Perform . 2014 ; 9 ( 1 ): 100 – 107 . PubMed ID: 24408353 doi:10.1123/ijspp

Open access

Amelia J. Carr, Philo U. Saunders, Laura A. Garvican-Lewis and Brent S. Vallance

25983592 14. Sharma A , Saunders P , Garvican-Lewis L , et al . Training quantification and periodization during live high train high at 2100 m in elite runners: an observational cohort case study . J Sports Sci Med . 2018 ; 17 : 607 – 616 . PubMed ID: 30479529 30479529 15. McLean B

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Bent R. Rønnestad, Tue Rømer and Joar Hansen

, Seiler S . From heart-rate data to training quantification: a comparison of 3 methods of training-intensity analysis . Int J Sports Physiol Perform . 2014 ; 9 ( 1 ): 100 – 107 . PubMed ID: 24408353 doi:10.1123/ijspp.2013-0298 21. Sandbakk Ø , Holmberg HC , Leirdahl S , Ettema G