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Introduction: In distance running, pacing is characterized by changes in speed, leading to runners dropping off the leader's pace until a few remain to contest victory with a final sprint. Pacing behavior has been well studied over the last 30 years, but much remains unknown. It might be related to finishing position, finishing time, and dependent on critical speed (CS), a surrogate of physiologic capacity. We hypothesized a relationship between CS and the distance at which runners "fell behind" and "let go" from the leader or were "outsprinted" as contributors to performance. Methods: 100-m split times were obtained for athletes in the men's 10,000-m at the 2008 Olympics (N = 35). Split times were individually compared with the winner at the point of "falling behind" (successive split times progressively slower than the winner), "letting go" (large increase in time for distance compared with winner), or "outsprinted" (falling behind despite active acceleration) despite being with the leader with 400 m remaining. Results: Race times ranged between 26:55 and 29:23 (world record = 26:17). There were 3 groups who fell behind at ∼1000 (n = 11), ∼6000 (n = 16), and ∼9000 m (n = 2); let go at ∼4000 (n = 10), ∼7000 (n = 14), and ∼9500 m (n = 5); or were outkicked (n = 6). There was a moderate correlation between CS and finishing position (r =.82), individual mean pace (r =.79), "fell behind" distance (r =.77), and "let go" distance (r =.79). D′ balance was correlated with performance in the last 400 m (r =.87). Conclusions: Athletes displayed distinct patterns of falling behind and letting go. CS serves as a moderate predictor of performance and final placing. Final placing during the sprint is related to preservation of D′ balance. [ABSTRACT FROM AUTHOR]

Purpose: To investigate how cycling time-trial (TT) performance changes over a cycling season, both in a "fresh" state and in a "fatigued" state (durability). Additionally, the aim was to explore whether these changes are related to changes in underlying physiological factors such as gross efficiency, energy expenditure (EE), and substrate oxidation (fat oxidation [FatOx] and carbohydrate oxidation [CarbOx]). Methods: Sixteen male semiprofessional cyclists visited the laboratory on 3 occasions during a cycling season (PRE, START, and IN) and underwent a performance test in both fresh and fatigued states (after 38.1 [4.9] kJ/kg), containing a submaximal warm-up for the measurement of gross efficiency, EE, FatOx, and CarbOx and a maximal TT of 1 (TT1min) and 10 minutes (TT10min). Results were compared across states (fresh vs fatigued) and periods (PRE, START, and IN). Results: The average power output (PO) in TT1min decreased (P <.05) from fresh to fatigued state across all observed periods, whereas there was no change in the PO in TT10min. Over the course of the season, the PO in TT1min in the fatigued state improved more compared with the PO in TT1min in the fresh state. Furthermore, while EE did not significantly change, there was an increase in FatOx and a decrease in CarbOx toward the fatigued state. These changes diminished during the cycling season (IN), indicating a greater contribution of CarbOx in the fatigued state. Conclusions: TT1min performance is more sensitive to fatigue compared with TT10min. Also, during a cycling season, durability improves more when compared with fresh maximal POs, which is also observed in the changes in substrate oxidation. [ABSTRACT FROM AUTHOR]

Purpose: This study determined the evolution of performance and pacing for each winner of the men's Olympic 1500-m running track final from 1924 to 2020. Methods: Data were obtained from publicly available sources. When official splits were unavailable, times from sources such as YouTube were included and interpolated from video records. Final times, lap splits, and position in the peloton were included. The data are presented relative to 0 to 400 m, 400 to 800 m, 800 to 1200 m, and 1200 to 1500 m. Critical speed and D′ were calculated using athletes' season's best times. Results: Performance improved ∼25 seconds from 1924 to 2020, with most improvement (∼19 s) occurring in the first 10 finals. However, only 2 performances were world records, and only one runner won the event twice. Pacing evolved from a fast start–slow middle–fast finish pattern (reverse J-shaped) to a slower start with steady acceleration in the second half (J-shaped). The coefficient of variation for lap speeds ranged from 1.4% to 15.3%, consistent with a highly tactical pacing pattern. With few exceptions, the eventual winners were near the front throughout, although rarely in the leading position. There is evidence of a general increase in both critical speed and D′ that parallels performance. Conclusions: An evolution in the pacing pattern occurred across several "eras" in the history of Olympic 1500-m racing, consistent with better trained athletes and improved technology. There has been a consistent tactical approach of following opponents until the latter stages, and athletes should develop tactical flexibility, related to their critical speed and D′, in planning prerace strategy. [ABSTRACT FROM AUTHOR]

Purpose: To determine if workload and seasonal periods (preseason vs in season) are associated with the incidence of injuries and illnesses in female professional cyclists. Methods: Session rating of perceived exertion was used to quantify internal workload and was collected from 15 professional female cyclists, from 33 athlete seasons. One week (acute) workload, 4 weeks (chronic) workload, and 3 acute:chronic workload models were analyzed. Two workload models are based on moving averages of the ratios, the acute:chronic workload ratio (ACWR), and the ACWR uncoupled (ACWRuncoup). The difference between both is the chronic load; in ACWR, the acute load is part of the chronic load, and in ACWRuncoup, the acute and chronic load are uncoupled. The third workload model is based on exponentially weighted moving averages of the ratios. In addition, the athlete season is divided into the preseason and in season. Results: Generalized estimating equations analysis was used to assess the associations between the workload ratios and the occurrence of injuries and illnesses. High values of acute workload (P =.048), ACWR (P =.02), ACWRuncoup (P =.02), exponentially weighted moving averages of the ratios (P =.01), and the in season (P =.0001) are significantly associated with the occurrence of injury. No significant associations were found between the workload models, the seasonal periods, and the occurrence of illnesses. Conclusions: These findings suggest the importance of monitoring workload and workload ratios in female professional cyclists to lower the risk of injuries and therefore improve their performances. Furthermore, these results indicate that, in the preseason, additional stressors occur, which could lead to an increased risk of injuries. [ABSTRACT FROM AUTHOR]

The session rating of perceived exertion (sRPE) method was developed 25 years ago as a modification of the Borg concept of rating of perceived exertion (RPE), designed to estimate the intensity of an entire training session. It appears to be well accepted as a marker of the internal training load. Early studies demonstrated that sRPE correlated well with objective measures of internal training load, such as the percentage of heart rate reserve and blood lactate concentration. It has been shown to be useful in a wide variety of exercise activities ranging from aerobic to resistance to games. It has also been shown to be useful in populations ranging from patients to elite athletes. The sRPE is a reasonable measure of the average RPE acquired across an exercise session. Originally designed to be acquired ∼30 minutes after a training bout to prevent the terminal elements of an exercise session from unduly influencing the rating, sRPE has been shown to be temporally robust across periods ranging from 1 minute to 14 days following an exercise session. Within the training impulse concept, sRPE, or other indices derived from sRPE, has been shown to be able to account for both positive and negative training outcomes and has contributed to our understanding of how training is periodized to optimize training outcomes and to understand maladaptations such as overtraining syndrome. The sRPE as a method of monitoring training has the advantage of extreme simplicity. While it is not ideal for the precise recording of the details of the external training load, it has large advantages relative to evaluating the internal training load. [ABSTRACT FROM AUTHOR]

Background: Gross efficiency (GE) declines during high-intensity exercise. Increasing extracellular buffer capacity might diminish the decline in GE and thereby improve performance. Purpose: To examine if sodium bicarbonate (NaHCO3) supplementation diminishes the decline in GE during a 2000-m cycling time trial. Methods: Sixteen male cyclists and 16 female cyclists completed 4 testing sessions including a maximal incremental test, a familiarization trial, and two 2000-m GE tests. The 2000-m GE tests were performed after ingestion of either NaHCO3 supplements (0.3 g/kg body mass) or placebo supplements (amylum solani, magnesium stearate, and sunflower oil capsules). The GE tests were conducted using a double-blind, randomized, crossover design. Power output, gas exchange, and time to complete the 2000-m time trials were recorded. Capillary blood samples were analyzed for blood bicarbonate, pH, and lactate concentration. Data were analyzed using magnitude-based inference. Results: The decrement in GE found after the 2000-m time trial was possibly smaller in the male and female groups after NaHCO3 than with placebo ingestion, with the effect in both groups combined being unclear. The effect on performance was likely trivial for males (placebo 164.2 [5.0] s, NaHCO3 164.3 [5.0] s; Δ0.1; ±0.6%), unclear for females (placebo 178.6 [4.8] s, NaHCO3 178.0 [4.3] s; Δ−0.3; ±0.5%), and very likely trivial when effects were combined. Blood bicarbonate, pH, and lactate concentration were substantially elevated from rest to pretest after NaHCO3 ingestion. Conclusions: NaHCO3 supplementation results in an unclear effect on the decrease in GE during high-intensity exercise and in a very likely trivial effect on performance. [ABSTRACT FROM AUTHOR]

Background: Pacing studies suggest the distribution of effort for optimizing performance. Cross-sectional studies of 1-mile world records (WRs) suggest that WR progression includes a smaller coefficient of variation of velocity. Purpose: This study evaluates whether intraindividual pacing used by elite runners to break their own WR (1 mile, 5 km, and 10 km) is related to the evolution of pacing strategy. We provide supportive data from analysis in subelite runners. Methods: Men's WR performances (with 400-m or 1-km splits) in 1 mile, 5 km, and 10 km were retrieved from the IAAF database (from 1924 to present). Data were analyzed relative to pacing pattern when a runner improved their own WR. Similar analyses are presented for 10-km performance in subelite runners before and after intensified training. Results: WR performance was improved in 1 mile (mean [SD]: 3:59.4 [11.2] to 3:57.2 [8.6]), 5 km (13:27 [0:33] to 13:21 [0:33]), and 10 km (28:35 [1:27] to 28:21 [1:21]). The average coefficient of variation did not change in the 1 mile (3.4% [1.8%] to 3.6% [1.6%]), 5 km (2.4% [0.9%] to 2.2% [0.8%]), or 10 km (1.4% [0.1%] to 1.5% [0.6%]) with improved WR. When velocity was normalized to the percentage mean velocity for each race, the pacing pattern was almost identical. Very similar patterns were observed in subelite runners in the 10 km. When time improved from 49:20 (5:30) to 45:56 (4:58), normalized velocity was similar, terminal RPE increased (8.4 [1.6] to 9.1 [0.8]), coefficient of variation was unchanged (4.4% [1.1%] to 4.8% [2.1%]), and VO2max increased (49.8 [7.4] to 55.3 [8.8] mL·min−1·kg−1). Conclusion: The results suggest that when runners break their own best performances, they employ the same pacing pattern, which is different from when WRs are improved in cross-sectional data. [ABSTRACT FROM AUTHOR]

Purpose: A valid measure for training load (TL) is an important tool for cyclists, trainers, and sport scientists involved in professional cycling. The aim of this study was to explore the influence of exercise intensity on the association between kilojoules (kJ) spent and different measures of TL to arrive at valid measures of TL. Methods: Four years of field data were collected from 21 cyclists of a professional cycling team, including 11,716 training and race sessions. kJ spent was obtained from power output measurements, and others TLs were calculated based on the session rating of perceived exertion (sRPE), heart rate (Lucia training impulse [luTRIMP]), and power output (training stress score [TSS]). Exercise intensity was expressed by the intensity factor (IF). To study the effect of exercise intensity on the association between kJ spent and various other TLs (sRPE, luTRIMP, and TSS), data from low- and high-intensity sessions were subjected to regression analyses using generalized estimating equations. Results: This study shows that the IF is significantly different for training and race sessions (0.59 [0.03] vs 0.73 [0.03]). Significant regression coefficients show that kJ spent is a good predictor of sRPE, and luTRIMP, as well as TSS. However, IF does not influence the associations between kJ spent and sRPE and luTRIMP, while the association with TSS is different when sessions are done with low or high IF. Conclusion: It seems that the TSS reacts differently to exercise intensity than sRPE and luTRIMP. A possible explanation could be the quadratic relation between IF and TSS. [ABSTRACT FROM AUTHOR]

Purpose: The relationship between various training-load (TL) measures in professional cycling is not well explored. This study investigated the relationship between mechanical energy spent (in kilojoules), session rating of perceived exertion (sRPE), Lucia training impulse (LuTRIMP), and training stress score (TSS) in training, races, and time trials (TT). Methods: For 4 consecutive years, field data were collected from 21 professional cyclists and categorized as being collected in training, racing, or TTs. Kilojoules (kJ) spent, sRPE, LuTRIMP, and TSS were calculated, and the correlations between the various TLs were made. Results: 11,655 sessions were collected, from which 7596 sessions had heart-rate data and 5445 sessions had an RPE score available. The r between the various TLs during training was almost perfect. The r between the various TLs during racing was almost perfect or very large. The r between the various TLs during TTs was almost perfect or very large. For all relationships between TSS and 1 of the other measurements of TL (kJ spent, sRPE, and LuTRIMP), a significant different slope was found. Conclusion: kJ spent, sRPE, LuTRIMP, and TSS all have a large or almost perfect relationship with each other during training, racing, and TTs, but during racing, both sRPE and LuTRIMP have a weaker relationship with kJ spent and TSS. Furthermore, the significant different slope of TSS vs the other measurements of TL during training and racing has the effect that TSS collected in training and road races differs by 120%, whereas the other measurements of TL (kJ spent, sRPE, and LuTRIMP) differ by only 73%, 67%, and 68%, respectively. [ABSTRACT FROM AUTHOR]

Purpose: To provide a retrospective analysis of a large competition database describing the intensity and load demands of professional road-cycling races, highlighting the differences between men's and women's races. Methods: In total, 20 male and 10 female professional cyclists participated in this study. During 4 consecutive years, heart rate, rating of perceived exertion, and power-output data were collected during both men's (n = 3024) and women's (n = 667) professional races. Intensity distribution in 5 heart-rate zones was quantified. Competition load was calculated using different metrics, including Training Stress Score (TSS), training impulse (TRIMP), and session rating of perceived exertion. Standardized effect size is reported as Cohen d. Results:Large to very large higher values (d = 1.36–2.86) were observed for distance, duration, total work (in kilojoules), and mean power output in men's races. Time spent in high-intensity heart-rate zones (ie, zones 4 and 5) was largely higher in women's races (d = 1.38–1.55) than in men's races. Small higher loads were observed in men's races quantified using TSS (d = 0.53) and TRIMP (d = 0.23). However, load metrics expressed per kilometer were large to very largely higher in women's races for TSS·km–1 (d = 1.50) and TRIMP·km–1 (d = 2.31). Conclusions: Volume and absolute load are higher in men's races, whereas intensity and time spent in high-intensity zones is higher in women's races. Coaches and practitioners should consider these differences in demands in the preparation of professional road cyclists. [ABSTRACT FROM AUTHOR]

Background: Research has shown that gross efficiency (GE) declines during high-intensity exercise, but the time course of recovery of GE after high-intensity exercise has not yet been investigated. Purpose: To determine the time course of the recovery of GE after time trials (TTs) of different lengths. Methods: Nineteen trained male cyclists participated in this study. Before and after TTs of 2000 and 20,000 m, subjects performed submaximal exercise at 55% of the power output attained at maximal oxygen uptake (PVO2max). The postmeasurement continued until 30 min after the end of the TT, during which GE was determined over 3-min intervals. The magnitude-based-inferences approach was used for statistical analysis. Results: GE decreased substantially during the 2000-m and 20,000-m TTs (−11.8% [3.6%] and −6.2% [4.0%], respectively). A most likely and very likely recovery of GE was found during the first half of the submaximal exercise bout performed after the 2000-m, with only a possible increase in GE during the first part of the submaximal exercise bout performed after the 20,000-m. After both distances, GE did not fully recover to the initial pre-TT values, as the difference between the pre-TT value and average GE value of minutes 26–29 was still most likely negative for both the 2000- and 20,000-m (−6.1% [2.8%] and −7.0% [4.5%], respectively). Conclusions: It is impossible to fully recover GE after TTs of 2000- or 20,000-m during 30 min of submaximal cycling exercise performed at an intensity of 55% PVO2max. [ABSTRACT FROM AUTHOR]

This study aimed to investigate whether (semi-)professional cyclists' execution of a training programme differs from the coach's designed training programme. Also, the study sought to ascertain, in instances where the training sessions were indeed executed as designed by the coach, whether the perception of the cyclists differed from the intention of the coach. This study highlights the differences between the coach and the individual cyclist. In total, 747 training sessions were collected from 11 (semi-)professional cyclists. Rating of Perceived Exertion (RPE) and session Rating of Perceived Exertion (sRPE) were compared with intended RPE (iRPE) and intended sRPE (isRPE), planned by the coach. Pearson's correlation, regression coefficients and Typical Error of Estimate (TEE) were used to identify differences between the executed and planned training sessions. Moderate to large TEEs were noted between executed and intended sRPE, which indicates that cyclists do not always execute the training programme planned by the coach. Furthermore, when the training was executed as planned by the coach, very large correlations but moderate to very large TEEs were noted between cyclists' (s)RPE and the coach's i(s)RPE, with unique individual regression coefficients. This indicates that the relationship between RPE and iRPE is unique to each cyclist. Both the different execution and perception of the training programme by the individual cyclists could cause an impaired training adaptation. Therefore, the coach must pay attention to the perception of training sessions by the individual cyclist. Improved individual management of training load could result in the optimisation of the proposed training programme. [ABSTRACT FROM AUTHOR]

This study aims to investigate the presence of the relative age effect (RAE) in (semi-)professional cycling, especially within selecting cyclists for Continental (CT) development teams. Data were collected from (PCS). Cyclists out of the top-25 countries of the PCS ranking that were part of a CT team between 2005 and 2016 and born between January 1986 and December 1997 were included (n = 2854). Distributions of cyclists in different birth quarters (Q1, Q2, Q3 and Q4) as well as for different starting years at CT level (U23year1, U23year2, U23year3 and U23year4) and reaching professional level or not were investigated using the Chi-square goodness-of-fit test. A RAE was found for cyclists that did not reach professional level, which can be explained by cyclists starting at CT level U23year1 and U23year2 (19 and 20 years old). Meaning that for cyclists at 19 and 20 years old, there is a selection bias towards relatively older (Q1) cyclists at the expense of relatively younger (Q4) cyclists. Within the cyclists that reached professional level, no RAE was found, indicating that the RAE diminishes at professional level. This study provides insight into possible selection errors while selecting cyclists for CT development teams. [ABSTRACT FROM AUTHOR]

In the article, the authors discuss how sport-science researchers should deal with the paradox of the increases in the quality and quantity of studies on the effects of sports and exercise on the hormonal profile of female participants and their performances in their sports. Topics include the importance of collecting detailed data on the menstrual cycle history and hormonal contraceptive use of female athletes participating in research.

Wingate test scores are strongly associated with anaerobic capacity in athletes involved in speed-endurance sports. In speed skating Wingate results are known to predict performance cross-sectionally but have not been investigated relative to their ability to predict performance longitudinally. Purpose: To investigate whether Wingate tests performed during summer training are predictive of 1500-m speed-skating performance the subsequent winter in elite speed skaters. Methods: Wingate test results from the summer training periods and 1500-m performances during the subsequent winter were analyzed over a 3-y period in 5 female and 8 male elite (Olympic, World Championship, and World Cup medalists) speed skaters. Regression analyses using generalized estimating equations (GEE) were used to estimate the relationship between Wingate test variables and 1500-m speed-skating performance. Wingate peak power (PP) and mean power (MP) were used to predict 1500-m time and 400-m lap times. Results: Improvements of 1 W/kg on PP and MP in women predict improvements of -0.75 s and -2.05 s, respectively, on 1500-m time (World Record 110.85 s). In men, improvements in PP and MP were associated with performance improvements of -0.92 s and -2.32 s on 1500-m time per 1 W/kg (World Record 101.04 s). Conclusion: Wingate test results achieved during the summer training period are a good predictor of improvements in 1500-m speed-skating performance during the subsequent winter. For the smallest worthwhile improvement in 1500-m performance, a gain in PP and MP of 2.1% and 1.4%(0.38 and 0.14 W/kg) for females and 1.2% and 0.9% (0.29 and 0.12 W/kg) for males is needed. [ABSTRACT FROM AUTHOR]

Purpose: To investigate whether monitoring of easily measurable stressors and symptoms can be used to distinguish early between acute fatigue (AF) and functional overreaching (FOR). Methods: The study included 30 subjects (11 female, 19 male; age 40.8 ± 10.8 y, VO2max 51.8 ± 6.3 mL ⋅kg-1 ⋅min-1) who participated in an 8-d cycling event over 1300 km with 18,500 climbing meters. Performance was measured before and after the event using a maximal incremental test. Subjects with decreased performance after the event were classified as FOR, others as AF. Mental and physical well-being, internal training load, resting heart rate, temperature, and mood were measured daily during the event. Differences between AF and FOR were analyzed using mixed-model ANOVAs. Logistic regression was used to determine the best predictors of FOR after 3 and 6 d of cycling. Results: Fifteen subjects were classified as FOR and 14 as AF (1 excluded). Although total group changes were observed during the event, no differences between AF and FOR were found for individual monitoring parameters. The combination of questionnaire-based changes in fatigue and readiness to train after 3 d cycling correctly predicted 78% of the subjects as AF or FOR (sensitivity = 79%, specificity = 77%). Conclusions: Monitoring changes in fatigue and readiness to train, using simple visual analog scales, can be used to identify subjects likely to become FOR after only 3 d of cycling. Hence, we encourage athlete support staff to monitor not only fatigue but also the subjective integrated mental and physical readiness to perform. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Half the improvement in 1500-m speed-skating world records can be explained by technological innovations and the other half by athletic improvement. It is hypothesized that improved skating economy is accountable for much of the athletic improvement. Purpose: To determine skating economy in contemporary athletes and to evaluate the change in economy over the years. Methods: Contemporary skaters of the Dutch national junior team (n = 8) skated 3 bouts of 6 laps at submaximal velocity, from which skating economy was calculated (in mL O2 ⋅ kg-1 ⋅ km-1). A literature search provided historic data on skating velocity and submaximal ...O2 (in mL ⋅ kg-1 ⋅ min-1), from which skating economy was determined. The association between year and skating economy was determined using linear-regression analysis. Correcting the change in economy for technological innovations resulted in an estimate of the association between year and economy due to athletic improvement. Results: A mean (± SD) skating economy of 73.4 ± 6.4 mL O2 ⋅ kg-1 ⋅ km-1 was found in contemporary athletes. Skating economy improved significantly over the historical time frame (-0.57 mL O2 • kg-1 ⋅ km-1 ⋅ y-1, 95% confidence interval [-0.84, -0.31]). In the final regression model for the klapskate era, with altitude as confounder, skating economy improved with a nonsignificant -0.58 mL O2 ⋅ kg-1 ⋅ km-1 ⋅ y-1 ([-1.19, 0.035]). Conclusions: Skating economy was 73.4 ± 6.4 mL O2 • kg-1 • km-1 in contemporary athletes and improved over the past ~50 y. The association between year and skating economy due to athletic improvement, for the klapskate era, approached significance, suggesting a possible improvement in economy over these years. [ABSTRACT FROM AUTHOR]

The author reflects on his visit to the Kennedy Space Center after the American College of Sports Medicine (ACSM) 2019 Annual Meeting in Orlando, Florida. He talks about the memorabilia from the Apollo missions at the space center, students who co-authored his contributions to the journal, and the lesson he learned from his visit to the space center.

Purpose: The session rating of perceived exertion (sRPE) is a well-accepted method of monitoring training load in athletes in many different sports. It is based on the category-ratio (0-10) RPE scale (BORG-CR10) developed by Borg. There is no evidence how substitution of the Borg 6-20 RPE scale (BORG-RPE) might influence the sRPE in athletes. Methods: Systematically training, recreational-level athletes from a number of sport disciplines performed 6 randomly ordered, 30-min interval-training sessions, at intensities based on peak power output (PPO) and designed to be easy (50% PPO), moderate (75% PPO), or hard (85% PPO). Ratings of sRPE were obtained 30 min postexercise using either the BORG-CR10 or BORG-RPE and compared for matched exercise conditions. Results: The average percentage of heart-rate reserve was well correlated with sRPE from both BORG-CR10 (r = .76) and BORG-RPE (r=.69). The sRPE ratings from BORG-CR10 and BORG-RPE were very strongly correlated (r = .90) at matched limes. Conclusions: Although producing different absolute numbers, sRPE derived from either the BORG-CR10 or BORG-RPE provides essentially interchangeable estimates of perceived exercise training intensity. [ABSTRACT FROM AUTHOR]

Analysis of sport performance can provide effects of environmental and other venue-specific factors in addition to estimates of within-athlete variability between competitions, which determines smallest worthwhile effects. Purpose: To analyze elite long-track speed-skating events. Methods: Log-transformed performance times were analyzed with a mixed linear model that estimated percentage mean effects for altitude, barometric pressure, type of rink, and competition importance. In addition, coefficients of variation representing residual venue-related differences and within-athlete variability between races within clusters spanning ~8 d were determined. Effects and variability were assessed with magnitude-based inference. Results: A 1000-m increase in altitude resulted in very large mean performance improvements of 2.8% in juniors and 2.1% in seniors. An increase in barometric pressure of 100 hPa resulted in a moderate reduction in performance of 1.1% for juniors but an unclear effect for seniors. Only juniors competed at open rinks, resulting in a very large reduction in performance of 3.4%. Juniors and seniors showed small performance improvements (0.4% and 0.3%) at the more important competitions. After accounting for these effects, residual venue-related variability was still moderate to large. The within-athlete within-cluster race-to-race variability was 0.3-1.3%, with a small difference in variability between male (0.8%) and female juniors (1.0%) and no difference between male and female seniors (both 0.6%). Conclusion: The variability in performance times of skaters is similar to that of athletes in other sports in which air or water resistance limits speed. A performance enhancement of 0.1-0.4% by top-10 athletes is necessary to increase medal-winning chances by 10%. [ABSTRACT FROM AUTHOR]

Purpose: To reach top performance in cycling, optimizing distribution of energy resources is crucial. The purpose of this study was to investigate power output during 250-m, 500-m, and 1000-m cycling time trials and the characteristics of the adopted pacing strategy. Methods: Nine trained cyclists completed an incremental test and 3 time trials that they were instructed to finish as quickly as possible. Preceding the trials, peak power during short sprints (PPsprint) and gross efficiency (GE) were measured. During the trials, power output and oxygen consumption were measured to calculate the contribution of the aerobic and anaerobic energy sources. After the trial GE was measured again. Results: Peak power during all trials (PPTT) was lower than PPsprint. In the 250-m trial the PPTT was higher in the 1000-m trial (P = .008). The subjects performed a significantly longer time at high intensity in the 250-m than in the 1000-m (P = .029). GE declined significantly during all trials (P < .01). Total anaerobically attributable work was less in the 250-m than in the 500-m (P = .015) and 1000-m (P < .01) trials. Conclusion: The overall pacing pattern in the 250-m trial appears to follow an all-out strategy, although peak power is still lower than the potential maximal power output. This suggests that a true all-out pattern of power output may not be used in fixed-distance events. The 500-m and 1000-m had a more conservative pacing pattern and anaerobic power output reached a constant magnitude. [ABSTRACT FROM AUTHOR]

The official world records (WR) for the 1 -mile run for men (3:43.13) and for women (4:12.58) have improved 12.2% and 32.3%, respectively, since the first WR recognized by the International Association of Athletics Federations. Previous observations have suggested that the pacing pattern for successive laps is characteristically faster-slower-slowest-faster. However, modeling studies have suggested that uneven energy-output distribution, particularly a high velocity at the end of the race, is essentially wasted kinetic energy that could have been used to finish sooner. Here the authors report that further analysis of the pacing pattern in 32 men’s WR races is characterized by a progressive reduction in the within-lap variation of pace, suggesting that improving the WR in the 1-mile run is as much about how energetic resources are managed as about the capacity of the athletes performing the race. In the women’s WR races, the pattern of lap times has changed little, probably secondary to a lack of depth in the women’s fields. Contemporary WR performances have been achieved a coefficient of variation of lap times on the order of 1.5-3.0%. Reasonable projection suggests that the WR is overdue for improving and may require lap times with a coefficient of variation of ~1%. [ABSTRACT FROM AUTHOR]

During the last decade discussion about training-intensity distribution has been an important issue in sports science. Training-intensity distribution has not been adequately investigated in speed skating, a unique activity requiring both high power and high endurance. Purpose: To quantify the training-intensity distribution and training hours of successful Olympic speed skaters over 10 Olympiads. Methods: Olympic-medal-winning trainers/coaches and speed skaters were interviewed and their training programs were analyzed. Each program was qualified and quantified: workout type (specific and nonspecific) and training zones (zone 1 ≤2 mMol/L lactate, zone 2 2-4 mMol/L lactate, zone 3 lactate >4 mMol/L). Net training times were calculated. Results: The relation between total training hours and time (successive Olympiads) was not progressive (r = .51, P > .5). A strong positive linear relation (r = .96, P < .01) was found between training distribution in zone 1 and time. Zones 2 and 3 both showed a strong negative linear relation to time (r = -.94, P < .01 ; r = -.97, P < .01 ). No significant relation was found between speed skating hours and time (r = -. 11, P > .05). This was also the case for inline skating and time (r = -.86, P > .05). Conclusions: These data indicate that in speed skating there was a shift toward polarized training over the last 38 y. This shift seems to be the most important factor in the development of Olympic speed skaters. Surprisingly there was no relation found between training hours, skating hours, and time. [ABSTRACT FROM AUTHOR]

A meaningful association between changes (Δ) in push-off angle or effectiveness (e) and changes in skating velocity (v) has been found during 5000-m races, although no significant association was found between changes in knee (Θo) and trunk angle Θ1 and Δv. It might be that speed skating event, sex, and performance level influence these associations. Purpose: To study the effect of skating event, sex, and performance level on the association between Δe and Δv and between Δ Θ0 and Δ Θ0, and Θv. Methods: Video recordings were made from frontal (e) and sagittal views Θ0 and Θi) during 1500- and 5000-m men's and women's World Cup races. Radio-frequency identification tags provided data of v. Results: Skating event influenced the association between Δ e and Δv, which resulted in a significant association between Δe and Δv for the 5000-m (β = -0.069, 95% confidence interval [-0.11, -0.030]) but not for the 1500-m (β = -0.011 [-0.032, 0.010]). The association between ΔΘ0 and ΔΘ ;1 and Δv was not significantly influenced by skating event. Sex and performance level did not substantially affect the association between Δe and Δv and between ΔΘ0 and Δ0, and Δv. Conclusions: Skating event significantly influenced the association between Δe and Δv; a 10 change in e results in a 0.011-m/s decrease in v during the 1500-m and a 0.069-m/s decrease in v during the 5000-m. Thus, it seems especially important to maintain a small e during the 5000-m. [ABSTRACT FROM AUTHOR]

Anaerobic capacity/anaerobically attributable power is an important parameter for athletic performance, not only for short high-intensity activities but also for breakaway efforts and end spurts during endurance events. Unlike aerobic capacity, anaerobic capacity cannot be easily quantified. The 3 most commonly used methodologies to quantify anaerobic capacity are the maximal accumulated oxygen deficit method, the critical power concept, and the gross efficiency method. This review describes these methods, evaluates if they result in similar estimates of anaerobic capacity, and highlights how anaerobic capacity is used during sporting activities. All 3 methods have their own strengths and weaknesses and result in more or less similar estimates of anaerobic capacity but cannot be used interchangeably. The method of choice depends on the research question or practical goal. [ABSTRACT FROM AUTHOR]

Previous studies have found decreases in arterial oxygen saturation to be temporally linked to reductions in power output (PO) during time-trial (TT) exercise. The purpose of this study was to determine whether preexercise desaturation (estimated from pulse oximetry [SPO2]), via normobaric hypoxia, would change the pattern of PO during a TT. Purpose: The authors tested the hypothesis that the starting PO of a TT would be reduced in the EARLY trial secondary to a reduced SPO2 but would not be reduced in LATE until ~30 s after the start of the TT. Methods: Eight trained cyclists/triathletes (4 male, 4 female) performed 3 randomly ordered 3-km TTs while breathing either room air (CONTROL) or hypoxic air administered 3 min before the start of the TT (EARLY) or at the beginning of the TT (LATE). Results: There was no effect of hypoxia on PO during the first 0.3 km of either the EARLY or the LATE trial compared with CONTROL, although there was a significant decrease in pre-TT SPO2 in EARLY vs CONTROL and LATE. The time for PO to decrease was ~40 s after the start of the TT in both EARLY and LATE. Conclusions : The results support the strong effect of the preexercise template on the pattern of PO during simulated competition and suggest that reductions in SPO2 are not direct signals to decrease PO. [ABSTRACT FROM AUTHOR]

Purpose: The best way to apply precooling for endurance exercise in the heat is still unclear. The authors analyzed the effect of different preparation regimens on pacing during a 15-km cycling time trial in the heat. Methods: Ten male subjects completed four 15-km time trials (30°C), preceded by different preparation regimes: 10 min cycling (WARM-UP), 30 min scalp cooling of which 10 min was cycling (SC+WARM-UP), ice-slurry ingestion (ICE), and ice slurry ingestion + 30 min scalp cooling (SC+ICE). Results: No differences were observed in finish time and mean power output, although power output was lower for WARM-UP than for SC+ICE during km 13-14 (17 ± 16 and 19 ± 14 W, respectively) and for ICE during km 13(16± 16 W). Rectal temperature at the start of the time trial was lower for both ICE conditions (~36.7°C) than both WARM- UP conditions (~37.1°C) and remained lower during the first part of the trial. Skin temperature and thermal sensation were lower at the start for SC+ICE. Conclusions: The preparation regimen providing the lowest body-heat content and sensation of coolness at the start (SC+ICE) was most beneficial for pacing during the latter stages of the time trial, although overall performance did not differ. [ABSTRACT FROM AUTHOR]

Optimal pacing strategy was determined for breaking the world speed record on a human-powered vehicle (HPV) using an energy-flow model in which the rider's physical capacities, the vehicle's properties, and the environmental conditions were included. Power data from world-record attempts were compared with data from the model, and race protocols were adjusted to the results from the model. HPV performance can be improved by using an energy-flow model for optimizing race strategy. A biphased in-run followed by a sprint gave best results. [ABSTRACT FROM AUTHOR]

Speed skating posture, or technique, is characterized by the push-off angle or effectiveness (e), determined as the angle between the push-off leg and the ice; the preextension knee angle (&#952:o); and the trunk angle (&#952:1). Together with muscle-power output and environmental conditions, skating posture, or technique, determines velocity (v). Purpose: To gain insight into technical variables that are important to skate efficiently and perform well, e, &#952:o, &#952:1|, and skating v were determined every lap during a 5000-m World Cup. Second, the authors evaluated if changes (A) in e, &#952:o, and &#952:1 are associated with Av. Methods: One camera filmed the skaters from a frontal view, from which e was determined. Another camera filmed the skaters from a sagittal view, from which 0O and 0, were determined. Radio-frequency identification tags around the ankles of the skaters measured v. Results: During the race, e progressively increased and v progressively decreased, while &#952:o and &#952:1 showed a less consistent pattern of change. Generalized estimating equations showed that Ae is significantly associated with &Delata;v over the midsection of the race (β = -0.10, P < .001) and that A0o and A0, are not significantly associated with Δv. Conclusions: The decrease in skating v over the race is not due to increases in power losses to air friction, as knee and trunk angle were not significantly associated with changes in velocity. The decrease in velocity can be partly ascribed to the decrease in effectiveness, which reflects a decrease in power production associated with fatigue. [ABSTRACT FROM AUTHOR]

The quality of performance during international competitions such as the Olympic Games and various world championships is often judged by the number of world records attained. The simple fact that world records continue to improve is evidence that sports performance is progressing. Does this also mean that athletes are improving? Is the continual progression of world-record performances evidence that contemporary athletes are superior to the athletes who performed in the past? Technological developments may obscure insight into the athletic enhancement made by athletes over the years. This commentary tries to separate technological and athletic enhancement in the progression of world records by the use of a power balance model. [ABSTRACT FROM AUTHOR]

The author explains that he follows the Why-How-What-So what scheme for scientific publications. Under the Why scheme, he tries to comprehend the purpose of the study and if it would be of interest to the readership. He pays less attention to the How and What sections but full consideration is given to the So What part to decide whether the submission will proceed to the review process. He expresses gratitude to the journal's editorial team whom he worked with as editor-in-chief.

Music is widely used as an ergogenic aid in sport, but there is little evidence of its effectiveness during closed- loop athletic events. In order to determine the effectiveness of music as an ergogenic aid, well-trained and task-habituated cyclists performed 10-km cycle time trials either while listening to self-selected motivational music or with auditory input blocked. There were no statistically significant differences in performance time or physiological or psychological markers related to music (time-trial duration 17.75 ± 2.10 vs 17.81 ± 2.06 min, mean power output 222 ± 66 vs 220 ± 65 W, peak heart rate 184 ± 9 vs 183 ± 8 beats/min, peak blood Iactate 12.1 ± 2.6 vs 11.9 ± 2.1 mmol/L, and final rating of perceived exertion 8.4 ± 1.5 vs 8.5 ± 1.6). It is concluded that during exercise at competitive intensity, there is no meaningful effect of music on either performance or physiology. [ABSTRACT FROM AUTHOR]

The author reflects on the economic impact of the COVID-19 virus which is spreading around the world, as of May 2020. He discusses a speech by John F. Kennedy which used the two-character Chinese word wei-chi for crisis, the possibilities that will influence the "International Journal of Sports Physiology and Performance" and the way they disseminate their collective knowledge, and the author's hope that the COVID-19 crisis will not impact one's personal life too much.

Rowers need to combine high sprint and endurance capacities. Muscle morphology largely explains muscle power generating capacity, however, little is known on how muscle morphology relates to rowing performance measures. The aim was to determine how muscle morphology of the vastus lateralis relates to rowing ergometer performance, sprint and endurance capacity of Olympic rowers. Eighteen rowers (12♂, 6♀, who competed at 2016 Olympics) performed an incremental rowing test to obtain maximal oxygen consumption, reflecting endurance capacity. Sprint capacity was assessed by Wingate cycling peak power. M. vastus lateralis morphology (volume, physiological cross-sectional area, fascicle length and pennation angle) was derived from 3-dimensional ultrasound imaging. Thirteen rowers (7♂, 6♀) completed a 2000-m rowing ergometer time trial. Muscle volume largely explained variance in 2000-m rowing performance (R2 = 0.85), maximal oxygen consumption (R2 = 0.65), and Wingate peak power (R2 = 0.82). When normalized for differences in body size, maximal oxygen consumption and Wingate peak power were negatively related in males (r = −0.94). Fascicle length, not physiological cross-sectional area, attributed to normalized peak power. In conclusion, vastus lateralis volume largely explains variance in rowing ergometer performance, sprint and endurance capacity. For a high normalized sprint capacity, athletes may benefit from long fascicles rather than a large physiological cross-sectional area. [ABSTRACT FROM AUTHOR]

The authors discuss some issues for researchers to consider when submitting their work to the "International Journal of Sports Physiology and Performance" and wanting to use null hypothesis significance testing. Topics mentioned include the American Statistical Association statement on statistical significance and P values, uncertainty on the degree of transfer and generalizability of study findings, and requirements to fulfill when submitting reports with various types of statistical methods.

Despite some advances, it remains largely unknown how the millions of variations in the human genome influence athletic performance (especially in endurance events), and no single genetic test can really predict sports talent. However, there is experimental evidence from animal research that selecting for even a simple characteristic such as running ability can produce comparatively large and rapid changes in performance. That such selection has not been specifically documented in humans is more evidence of the limits of physiology-archeology than of the unlikelihood of selection for physical abilities. Here, the authors argue that top Olympians are likely genetically gifted individuals who in addition have numerous contributors to the "complex trait" of being an athletic champion that may not necessarily depend on defined genetic variations. [ABSTRACT FROM AUTHOR]

An editorial is presented in which the author discusses the work of sport scientists, with a focus on effective practices for training high-level athletes. Topics include ownership of failure when an athlete fails, the evaluation of physical training programs, and research on the signaling processes in response to athletic training.

Introduction: The aim of this study was to present the load, intensity, and performance characteristics of a general classification (GC) contender during multiple grand tours (GTs). This study also investigated which factors influence climbing performance. Methods: Power output (PO) data were collected from a GC contender from the Vuelta a España 2015, the Giro d'Italia 2017, the Giro d'Italia 2018, and the Tour de France 2018. Load (e.g., Training Stress Score and kJ spent) and intensity in five PO zones were quantified. One-way ANOVA was used to identify differences between the GTs. Furthermore, performance during the four GTs was quantified based on maximal mean PO (W·kg−1) over different durations and by the relative PO (W·kg−1) on the key mountains in the GTs. Stepwise multiple regression analysis was used to identify which factors influence relative PO on the key mountains. Results: No significant differences were found between load and intensity characteristics between the four GTs, with the exception that during the Giro d'Italia 2018, a significantly lower absolute time was spent in PO zone 5 (P = 0.005) compared with the other three GTs. The average relative PO on the key mountains (n = 33) was 5.9 ± 0.6 W·kg−1 and was negatively influenced by the duration of the climb and the total elevation gain before the key mountain, whereas the gradient of the mountain had a positive effect on relative PO. Conclusions: The physiological load imposed on a GC contender did not differ between multiple GTs. Climbing performance was influenced by short-term fatigue induced by previous altitude meters in the stage and the duration and gradient of the mountain. [ABSTRACT FROM AUTHOR]

PURPOSE: Performance in running events, such as 1-Mile World Records (WR), depends both on having and effectively using energetic resources. Although often understood in terms of physiological capacity based on the Joyner model, the Critical Speed/D' model is an alternative method of accounting for energetic capacity and use, based on prior performances rather than measured physiological capacity. One would hypothesize that lap-by-lap running speed during a WR would be based on CS + a fraction of D' used during each lap, and that D' would be very close to zero at the end of the WR. METHODS: Data were retrieved from the IAAF database for individual best performances between 800m-5km (at least 3 distances per athlete, not including the WR) to allow calculation of CS/D'. Lap times from the WR races were also retrieved. Observed speed per lab with CS subtracted, was used to compute the %D' used during each lap to account for the amount of D' remaining at the end. The data sample included 23 Males (29 WR races, 223.1-254.4s) and 6 Females (8 WR races,252.6-279.2s). If a given athlete achieved more than one WR, their data was treated independently. RESULTS: The average) (+sd) 1-mle WR was 238.7+13.7 s. Average CS was 5.698+0.556 m/s, the average D' was 197.0+32.6 m, the average %D' remaining after 1, 2, 3 & 4 laps was 69+7, 46+7 23+9, and -7.8% of D'. At the finish D' was -15.4+16.8 m. There was a week relationship between WR time and D' remaining at the conclusion of the event (r=0.37) suggesting little temporal change in the use of D'. CONCLUSIONS: The results suggest that the CS/D' model is effective at accounting for 1-mile WR performance with an error of <8%, despite considerable differences in the pacing pattern. These results support the CS/D' model for the analysis of running performance. [ABSTRACT FROM AUTHOR]