Andrew Renfree

Application of Decision-Making Theory to the Regulation of Muscular Work Rate during Self-Paced Competitive Endurance Activity

Successful participation in competitive endurance activities requires continual regulation of muscular work rate in order to maximise physiological performance capacities, meaning that individuals must make numerous decisions with regards to the muscular work rate selected at any point in time. Decisions relating to the setting of appropriate goals and the overall strategic approach to be utilised are made prior to the commencement of an event, whereas tactical decisions are made during the event itself. This review examines current theories of decision-making in an attempt to explain the manner in which regulation of muscular work is achieved during athletic activity. We describe rational and heuristic theories, and relate these to current models of regulatory processes during self-paced exercise in an attempt to explain observations made in both laboratory and competitive environments. Additionally, we use rational and heuristic theories in an attempt to explain the influence of the presence of direct competitors on the quality of the decisions made during these activities. We hypothesise that although both rational and heuristic models can plausibly explain many observed behaviours in competitive endurance activities, the complexity of the environment in which such activities occur would imply that effective rational decision-making is unlikely. However, at present, many proposed models of the regulatory process share similarities with rational models. We suggest enhanced understanding of the decision-making process during self-paced activities is crucial in order to improve the ability to understand regulation of performance and performance outcomes during athletic activity.

Risk perception influences athletic pacing strategy

PURPOSE The objective of this study is to examine risk taking and risk perception associations with perceived exertion, pacing, and performance in athletes. METHODS Two experiments were conducted in which risk perception was assessed using the domain-specific risk taking (DOSPERT) scale in 20 novice cyclists (experiment 1) and 32 experienced ultramarathon runners (experiment 2). In experiment 1, participants predicted their pace and then performed a 5-km maximum effort cycling time trial on a calibrated Kingcycle mounted bicycle. Split times and perceived exertion were recorded every kilometer. In experiment 2, each participant predicted their split times before running a 100-km ultramarathon. Split times and perceived exertion were recorded at seven checkpoints. In both experiments, higher and lower risk perception groups were created using median split of DOSPERT scores. RESULTS In experiment 1, pace during the first kilometer was faster among lower risk perceivers compared with higher risk perceivers (t(18) = 2.0, P = 0.03) and faster among higher risk takers compared with lower risk takers (t(18) = 2.2, P = 0.02). Actual pace was slower than predicted pace during the first kilometer in both the higher risk perceivers (t(9) = -4.2, P = 0.001) and lower risk perceivers (t(9) = -1.8, P = 0.049). In experiment 2, pace during the first 36 km was faster among lower risk perceivers compared with higher risk perceivers (t(16) = 2.0, P = 0.03). Irrespective of risk perception group, actual pace was slower than predicted pace during the first 18 km (t(16) = 8.9, P < 0.001) and from 18 to 36 km (t(16) = 4.0, P < 0.001). In both experiments, there was no difference in performance between higher and lower risk perception groups. CONCLUSIONS Initial pace is associated with an individuals perception of risk, with low perceptions of risk being associated with a faster starting pace. Large differences between predicted and actual pace suggest that the performance template lacks accuracy, perhaps indicating greater reliance on momentary pacing decisions rather than preplanned strategy.

The influence of performance level, age and gender on pacing strategy during a 100-km ultramarathon

Abstract The aim of this study is to analyse the influence of performance level, age and gender on pacing during a 100-km ultramarathon. Results of a 100-km race incorporating the World Masters Championships were used to identify differences in relative speeds in each 10-km segment between participants finishing in the first, second, third and fourth quartiles of overall positions (Groups 1, 2, 3 and 4, respectively). Similar analyses were performed between the top and bottom 50% of finishers in each age category, as well as within male and female categories. Pacing varied between athletes achieving different absolute performance levels. Group 1 ran at significantly lower relative speeds than all other groups in the first three 10-km segments (all P < 0.01), and significantly higher relative speeds than Group 4 in the 6th and 10th (both P < 0.01), and Group 2 in the 8th (P = 0.04). Group 4 displayed significantly higher relative speeds than Group 2 and 3 in the first three segments (all P < 0.01). Overall strategies remained consistent across age categories, although a similar phenomenon was observed within each category whereby ‘top’ competitors displayed lower relative speeds than ‘bottom’ competitors in the early stages, but higher relative speeds in the later stages. Females showed lower relative starting speeds and higher finishing speeds than males. ‘Top’ and ‘bottom’ finishing males displayed differing strategies, but this was not the case within females. Although pacing remained consistent across age categories, it differed with level of performance within each, possibly suggesting strategies are anchored on direct competitors. Strategy differs between genders and differs depending on performance level achieved in males but not females.

Increased variability of lap speeds : differentiating medalists and nonmedalists in middle-distance running and swimming events

PURPOSE Previous literature has presented pacing data of groups of competition finalists. The aim of this study was to analyze the pacing patterns displayed by medalists and nonmedalists in international competitive 400-m swimming and 1500-m running finals. METHODS Split times were collected from 48 swimming finalists (four 100-m laps) and 60 running finalists (4 laps) in international competitions from 2004 to 2012. Using a cross-sectional design, lap speeds were normalized to whole-race speed and compared to identify variations of pace between groups of medalists and nonmedalists. Lap-speed variations relative to the gold medalist were compared for the whole field. RESULTS In 400-m swimming the medalist group demonstrated greater variation in speed than the nonmedalist group, being relatively faster in the final lap (P < .001; moderate effect) and slower in laps 1 (P = .03; moderate effect) and 2 (P > .001; moderate effect). There were also greater variations of pace in the 1500-m running medalist group than in the nonmedalist group, with a relatively faster final lap (P = .03; moderate effect) and slower second lap (P = .01; small effect). Swimming gold medalists were relatively faster than all other finalists in lap 4 (P = .04), and running gold medalists were relatively faster than the 5th- to 12th-placed athletes in the final lap (P = .02). CONCLUSIONS Athletes who win medals in 1500-m running and 400-m swimming competitions show different pacing patterns than nonmedalists. End-spurt-speed increases are greater with medalists, who demonstrate a slower relative speed in the early part of races but a faster speed during the final part of races than nonmedalists.

The Influence of Collective Behavior on Pacing in Endurance Competitions

A number of theoretical models have been proposed in recent years to explain pacing strategies observed in individual competitive endurance events. These have typically related to the internal regulatory processes that inform the making of decisions relating to muscular work rate. Despite a substantial body of research which has investigated the influence of collective group dynamics on individual behaviors in various animal species, this issue has not been comprehensively studied in individual athletic events. This is somewhat surprising given that athletes often directly compete in close proximity to one another, and that collective behavior has also been observed in other human environments including pedestrian interactions and financial market trading. Whilst the reasons for adopting collective behavior are not fully understood, collective behavior is thought to result from individual agents following simple local rules that result in seemingly complex large systems that act to confer some biological advantage to the collective as a whole. Although such collective behaviors may generally be beneficial, competitive endurance events are complicated by the fact that increasing levels of physiological disruption as activity progresses may compromise the ability of some individuals to continue to interact with other group members. This could result in early fatigue and relative underperformance due to suboptimal utilization of physiological resources by some athletes. Alternatively, engagement with a collective behavior may benefit all due to a reduction in the complexity of decisions to be made and a subsequent reduction in cognitive loading and mental fatigue. This paper seeks evidence for collective behavior in previously published analyses of pacing behavior and proposes mechanisms through which it could potentially be either beneficial, or detrimental to individual performance. It concludes with suggestions for future research to enhance understanding of this phenomenon.

Tactical considerations in the middle-distance running events at the 2012 Olympic Games: a case study.

PURPOSE To identify tactical factors associated with progression from preliminary rounds in middle-distance running events at an international championship. METHODS Results from the 2012 Olympic Games were used to access final and intermediate positions, finishing times, and season-best (SB) times for competitors in mens and womens 800-m and 1500-m events (fifteen 800-m races and ten 1500-m races). Finishing times were calculated as %SB, and Pearson product-moment correlations were used to assess relationships between intermediate and finishing positions. Probability (P) of qualification to the next round was calculated for athletes in each available intermediate position. RESULTS There were no significant differences in finishing times relative to SB between qualifiers and nonqualifiers. In the 800-m, correlation coefficients between intermediate and final positions were r = .61 and r = .84 at 400 m and 600 m, respectively, whereas in the 1500-m, correlations were r = .35, r = .43, r = .55, and r = .71 at 400 m, 800 m, 1000 m, and 1200 m, respectively. In both events, probability of qualification decreased with position at all intermediate distances. At all points, those already in qualifying positions were more likely to qualify for the next round. CONCLUSIONS The data demonstrate that tactical positioning at intermediate points in qualifying rounds of middle-distance races is a strong determinant of qualification. In 800-m races it is important to be in a qualifying position by 400 m. In the 1500-m event, although more changes in position are apparent, position at intermediate distances is still strongly related to successful qualification.

Editorial: Regulation of Endurance Performance: New Frontiers

Successful endurance performance requires the integration of multiple physiological and psychological systems, working together to regulate exercise intensity in a way that will reduce time taken or increase work done. The systems that ultimately limit performance of the task are hotly contested, and may depend on a variety of factors including the type of task, the environment, external influences, training status of the individual and a host of psychological constructs. These factors can be studied in isolation, or inclusively as a whole-body or integrative system. A reductionist approach has traditionally been favored, leading to a greater understanding and emphasis on muscle and cardiovascular physiology, but the role of the brain and how this integrates multiple systems is gaining momentum. However, these differing approaches may have led to false dichotomy, and now with better understanding of both fields, there is a need to bring these perspectives together.

Validity and Test –retest Reliability of the TIVRE-Basket® Test for the Determination of Aerobic Power in Elite Male Basketball Players

Abstract Vaquera, A, Villa, JG, Morante, JC, Thomas, G, Renfree, AJ, and Peters, DM. Validity and test-retest reliability of the TIVRE-Basket test for the determination of aerobic power in elite male basketball players. J Strength Cond Res 30(2): 584–587, 2016—The aims of this study were to (a) determine the relationship between performance on the court-based TIVRE-Basket test and peak aerobic power determined from a criterion laboratory-based incremental treadmill test and (b) to examine the test-retest reliability of the TIVRE-Basket test in elite male basketball players. To address aim 1, 36 elite male basketball players (age: 25.2 ± 4.7 years, weight: 94.1 ± 11.4 kg, height: 195.83 ± 9.6 cm) completed a graded treadmill exercise test and the TIVRE-Basket within 72 hours. The mean distance recorded during the TIVRE-Basket test was 4001.8 ± 176.4 m, and mean V[Combining Dot Above]O2 peak was 54.7 ± 2.8 ml·kg−1·min−1, and the correlation between the 2 parameters was r = 0.824 (p ⩽ 0.001). Linear regression analysis identified TIVRE-Basket distance (in meters) as the only unique predictor of V[Combining Dot Above]O2 peak in a single variable plus constant model: V[Combining Dot Above]O2 peak = 2.595 + (0.13 × TIVRE-Basket distance [in meters]). Performance on the TIVRE-Basket test accounted for 67.8% of the variance in V[Combining Dot Above]O2 peak (t = 8.466, p ⩽ 0.001, 95% confidence interval: 0.01–0.016, SEE: 1.61). To address aim 2, 20 male basketball players (age: 26.7 ± 4.2 years, height: 1.94 ± 0.92 cm, weight: 94.0 ± 9.1 kg) performed the TIVRE-Basket test on 2 occasions. There was no significant difference in total distance covered between trial 1 (4138.8 ± 677.3 m) and trial 2 (4188.0 ± 648.8 m; t = 0.5798, p = 0.5688). Mean difference between trials was 49.2 ± 399.5 m, with an intraclass correlation coefficient of 0.85 suggesting a moderate level of reliability. Standardized typical error of measurement was 0.88%, representing a moderate degree of trial-to-trial error, and the Coefficient of Variation (CV) was 6.3%. The TIVRE-Basket test therefore represents a valid and moderately reliable court-based sport-specific test of aerobic power for use with individuals and teams of elite-level male basketball players. Future research is required to ascertain its validity and reliability in other basketball populations, for example, across age groups, at different levels of competition, in females and in different forms of the game, for example, wheelchair basketball.

Regulation of Endurance Performance: New Frontiers

Successful endurance performance requires the integration of multiple physiological and psychological systems, working together to regulate exercise intensity in a way that will reduce time taken or increase work done. The systems that ultimately limit performance of the task are hotly contested, and may depend on a variety of factors including the type of task, the environment, external influences, training status of the individual and a host of psychological constructs. These factors can be studied in isolation, or inclusively as a whole-body or integrative system. A reductionist approach has traditionally been favoured, leading to a greater understanding and emphasis on muscle and cardiovascular physiology, but the role of the brain and how this integrates multiple systems is gaining momentum. However, these differing approaches may have led to false dichotomy, and now with better understanding of both fields, there is a need to bring these perspectives together.

A Computer Model of Drafting Effects on Collective Behavior in Elite 10,000-m Runners

PURPOSE Drafting in cycling influences collective behavior of pelotons. Although evidence for collective behavior in competitive running events exists, it is not clear if this results from energetic savings conferred by drafting. This study modeled the effects of drafting on behavior in elite 10,000-m runners. METHODS Using performance data from a mens elite 10,000-m track running event, computer simulations were constructed using Netlogo 5.1 to test the effects of 3 different drafting quantities on collective behavior: no drafting, drafting to 3 m behind with up to ~8% energy savings (a realistic running draft), and drafting up to 3 m behind with up to 38% energy savings (a realistic cycling draft). Three measures of collective behavior were analyzed in each condition: mean speed, mean group stretch (distance between first- and last-placed runner), and runner-convergence ratio (RCR), which represents the degree of drafting benefit obtained by the follower in a pair of coupled runners. RESULTS Mean speeds were 6.32 ± 0.28, 5.57 ± 0.18, and 5.51 ± 0.13 m/s in the cycling-draft, runner-draft, and no-draft conditions, respectively (all P < .001). RCR was lower in the cycling-draft condition but did not differ between the other 2. Mean stretch did not differ between conditions. CONCLUSIONS Collective behaviors observed in running events cannot be fully explained through energetic savings conferred by realistic drafting benefits. They may therefore result from other, possibly psychological, processes. The benefits or otherwise of engaging in such behavior are as yet unclear.