Pace Versus Prediction: Is the Age of the Runner Associated With Marathon Success?

INTRODUCTION: During closed-loop exercise, such as marathon running, the athlete adopts a pacing strategy to optimise performance. Exercise intensity (speed) is modulated in response to afferent signals from biological and psychological systems, which relay the responses of the exercise to the brain where efferent, homeostatic-orientated responses are issued. Thus a conscious perception of effort is continuously compared to a sub-conscious template which is derived from previous exposure to the sensations of pain and fatigue and expected exercise duration. The purpose of this study was to explore the association between pacing strategy/race outcome and biological age of the athlete. METHODS: Following local institutional ethical approval n = 777 runners who were competing in the 2015 London Marathon volunteered and agreed to participate. Age, gender and experience of the participants were ascertained using an online survey and opportunistic questionnaire surveying at the pre-marathon registration event. Age was stratified according to the following classifications: 18-39 yrs, 40-49 yrs, 50-59 yrs and >60 yrs. Additionally, participants were asked to predict their marathon finish time (PT) serving as a proxy for end-point and compared to actual finish time (FT). All participating runners 5km splits and FT were downloaded from the race website, converted to speed and then normalised (%) to the final split time/speed (m∙s-1). RESULTS: Significant differences were observed for all age groups (p 60 yrs (p = 0.153). Non-significant differences observed between age groups across all 5km splits (p > 0.05), but within group differences observed between 10-15km for all age groups (p 60yrs at 30-35km (ES = 0.53). CONCLUSIONS: These data suggest that the biological age of the athlete is associated with the implementation of a successful pacing strategy and may be a function of the accrued training volume and/or emotional-event development. Athletes are encouraged to pace themselves with older (>60yrs) athletes with similar PT’

Pace Versus Prediction: Is the Experience of the Runner Associated With Marathon Success?

PURPOSE: Pacing strategies during exercise are attributed to optimising the balance between the artefacts of fatigue and regulation of substrate metabolism. Pace judgement is set within a continuum of information from the ability to anticipate metabolic demands and select an appropriate strategy through to the accumulation of prior experience for completion of such a task that has a known end-point. Therefore the purpose of this study was to evaluate the importance of athlete experience to successfully regulate pace and attain a predicted end time during a marathon. METHOD: Following local institutional ethical approval n= 777 runners competing in the 2015 London Marathon agreed to participate. Using an on-line survey and opportunistic questionnaire at a pre-marathon event participants were asked to predict their race time. Athlete experience (EXP) was established based on the number of previously completed marathons using a Likert scale from 0 to greater than 10 with increments of 1 race. Athlete age was also recorded. All race data was downloaded from the race website generating 5Km split times, then converted to speed and normalised (%) to the final split time/speed (m.s-1). Prediction time (PT) was used a proxy for end-point and compared to finish time (FT). RESULTS: FT for whole group (WG) was 15479 ±3311s compared to the group PT 15003 ±2972s a significant difference of 476s (P= 0.0001). An R2of 0.863 observed for WG compared to 0.799 (EXP-0) and 0.852 (EXP-5) when comparing FT to PT. Significant differences observed between PT and FT for all EXP groups apart from EXP-5 (P= 0.0001). EXP-0 showed significant difference across all split times apart from 35-40 km (P=0.0001) with a decrease in normalised speed from 5km (109.0 ±7.6) –40km (89.9 ±7.4%). The EXP-5 group showed significant changes in pace between 25-30 km (P= 0.001) (ES= 0.35) and 30-35 km (P= 0.0001) (ES= 0.44), decrease in pace from 5km (105.0 ±5.7%) to 40km (93.7 ±5.6%). CONCLUSIONS: These data suggest that successful marathon pacing is dependent on the experience of the athlete reflecting the development of the pacing template. Additionally experience is associated with better attainment of prediction time suggesting that less experienced runners should run with more experienced athletes with similar end-point targets

Marathon Pacing Ability: Training Characteristics and Previous Experience

Even pacing within the marathon has been associated with faster marathon performance times, however, little literature has investigated the association between pacing ability during a marathon and a recreational marathoner's training characteristics and previous experiences. N = 139 participants completed an online questionnaire concerning training history in relation to a 2017 marathon and previous long-distance running experiences. Online databases were used to collect split times of the participants after successfully completing a 2017 marathon, identifying the percentage slowdown in pace between the first half and second half of the marathon, used for correlational analyses. The strongest correlates for pacing ability were marathon finishing time and previous distance race personal best finishing times (i.e. marathon, half-marathon, 10 km and 5 km). There were many weaker, however significant correlates for training history characteristics and previous long-distance running experience. The current findings demonstrate that greater accrued long-distance running experiences and higher weekly training volumes are strongly associated smaller declines in pace during the second half of the marathon in comparison to the first half and less variability in pace during the marathon

Pace Versus Prediction: Is the Sex of the Runner Associated With Marathon Success?

PURPOSE: The ability to regulate effort (pace) is ascribed to the ability to make prospective judgments regarding the metabolic demands of the exercise challenge against personal metabolic capacity. Thus pace modulations which are dependent on knowing an exercise end-point are a function of biologically and cognitively orchestrated afferent signals and the homeostatically orientated efferent responses are manifest to prevent a depletion of the finite anaerobic capacity and onset of fatigue. The purpose of this study was to examine the pacing strategies adopted during a marathon and to explore whether there was a difference in outcome between males and females. METHOD: Following local institutional ethical approval n= 777 runners competing in the 2015 London Marathon volunteered and agreed to participate of which n= 393 were females and n= 384 were males. Using an online survey, available for 12 weeks up to the marathon and opportunistic sampling at the pre-marathon registration, participants were also asked to predict race time. Additional information regarding age and experience (number of marathons) were also obtained. Prediction time (PT) served as a proxy of end target time. For each participant 5km splits and finish time (FT) were converted to speed and then normalised (%) to the final split time/speed (m.s-1). RESULTS: A significant difference (P= 0.0001) of 476s was observed between PT and FT for the whole group compared to differences of 531 s (p= 0.000) and 419s (P= 0.000) for the males and females respectively. Both males (P= 0.0001) and females (P= 0.0001) showed significant differences between PT and FT. Males exhibited differences in pace for all 5km splits (P= 0.0001) except 5-10km (P= 0.483), large ES between 25-30km (r= 0.319) and 30-35km (r= 0.426), pace decreased from 107.4 ± 7.8% (5km) to 91.2 ± 7.1% (40km), compared to 109.1 ± 8.6% (5km) to 93.2 ± 6.5% (40km) for females. Females exhibited differences across all 5km splits (P= 0.0001) except between 35-40km (P= 1.000) with medium ES for 20-25km (r= 0.243) and 30-35km (r= 0.313). CONCLUSIONS: There is no difference between male and female marathon pacing strategies suggesting that the pacing template is not sex specific. Furthermore these data lend support to the notion that there is not an unfair advantage for females to be paced or race with males

Pace versus prediction: Implications of age, experience and sex on marathon race performance

PURPOSE: Pacing strategies during exercise are attributed to optimising the balance between the artefacts of fatigue and regulation of substrate metabolism. Pace judgement is set within a continuum of information from the ability to anticipate metabolic demands and select an appropriate strategy through to the accumulation of prior experience for completion of such a task that has a known end-point. Therefore the purpose of this study was evaluate the factors which contribute to successfully regulating pace and attaining a predicted end time during a marathon. METHOD: Following local institutional ethical approval n= 777 runners competing in the 2015 London Marathon of which n= 393 were females and n= 384 were males participated. Using an on-line survey and opportunistic questionnaires at a pre-marathon event participants were asked to predict their race time. Athlete experience (EXP) was established based on the number of previously completed marathons using a Likert scale from 0 to greater than 10 with increments of 1 race. Age was stratified according to those adopted by the marathon organisers: 18-39yrs, 40-49yrs, 50-59yrs and >60yrs. 5Km split times were converted to speed and normalised (%) to the final split time/speed (m.s-1). Prediction time (PT) was used a proxy for end-point and compared to finish time (FT). RESULTS: FT for whole group (WG) was 15479 ± 3311s compared to the group PT 15003 ± 2972s a significant difference of 476s (P= 0.0001). An R2 of 0.863 observed for WG compared to 0.799 (0-EXP) and 0.852 (EXP-5) when comparing FT to PT. 0-EXP showed significant difference across all split times apart from 35-40 km (P=0.0001) with a decrease in normalised speed from 5km (109.0 ± 7.6) – 40km (89.9 ± 7.4%). The 5-EXP group showed significant changes in pace between 25-30 km (P= 0.001) (ES =0.35), 30-35 km (P= 0.0001) (ES= 0.44) and 35-40 km (P= 0.0001), decrease in pace from 5km (105.0 ± 5.7%) to 40km (93.7 ± 5.6%). Large effect sizes (ES) observed for 18-39yrs at 30-35km (r= 0.370), 40-49yrs at 30-35km (r= 0.337), 50-59yrs at 25-30km (r= 0.368) and 30-35km (r= 0.418) and >60yrs at 30-35km (r= 0.527). A significant difference (P= 0.0001) of 476s was observed between PT and FT for the whole group compared to differences of 531 s (p= 0.000) and 419s (P= 0.000) for the males and females respectively. CONCLUSIONS: These data suggest that successful marathon pacing is dependent on the experience of the athlete reflecting the development of the pacing template. Additionally experience is associated with better attainment of prediction time suggesting that less experienced runners should run with more experienced athletes with similar end-point targets