Anaerobic Speed Reserve: A Key Component of Elite Male 800m Running

Abstract

Purpose::
In recent years (2011-2016), men's 800m championship running performances have required greater speed than previous eras (2000-2009). The "Anaerobic speed reserve" (ASR) may be a key differentiator of this performance, but profiles of elite 800m runners and its relationship to performance time have yet to be determined.

Methods::
The ASR - determined as the difference between maximal sprint speed (MSS) and predicted maximal aerobic speed (MAS) - of 19 elite 800m and 1500m runners was assessed using 50m sprint and 1500m race performance times. Profiles of three athlete sub-groups were examined using cluster analysis and the speed reserve ratio (SRR), defined as MSS/MAS.

Results::
For the same MAS, MSS and ASR showed very large negative (both r=-0.74±0.30, ±90% confidence limits; very likely) relationships with 800m performance time. In contrast, for the same MSS, ASR and MAS had small negative relationships (both r=-0.16±0.54), possibly) with 800m performance. ASR, 800m personal best, and SRR best defined the three sub-groups along a continuum of 800m runners, with SRR values as follows: 400-800m ≥1.58, 800m ≤1.57 to ≥1.47, and 800-1500m as ≤1.47 to ≥ 1.36.

Conclusions::
MSS had the strongest relationship with 800m performance, whereby for the same MSS, MAS and ASR showed only small relationships to differences in 800m time. Further, our findings support coaching observation of three 800m sub-groups, with the SRR potentially representing a useful and practical tool for identifying an athlete's 800m profile. Future investigations should consider the SRR framework and its application for individualised training approaches in this event.

Full text

Anaerobic Speed Reserve: A Key Component
of Elite Male 800-m Running
Gareth N. Sandford, Sian V. Allen, Andrew E. Kilding, Angus Ross, and Paul B. Laursen
Purpose:In recent years (2011–2016), men’s 800-m championship running performances have required greater speed than
previous eras (2000–2009). The “anaerobic speed reserve”(ASR) may be a key differentiator of this performance, but profiles of
elite 800-m runners and their relationship to performance time have yet to be determined. Methods:The ASR—determined as the
difference between maximal sprint speed (MSS) and predicted maximal aerobic speed (MAS)—of 19 elite 800- and 1500-m
runners was assessed using 50-m sprint and 1500-m race performance times. Profiles of 3 athlete subgroups were examined using
cluster analysis and the speed reserve ratio (SRR), defined as MSS/MAS. Results:For the same MAS, MSS and ASR showed
very large negative (both r=−.74 ± .30, ±90% confidence limits; very likely) relationships with 800-m performance time. In
contrast, for the same MSS, ASR and MAS had small negative relationships (both r=−.16 ± .54; possibly) with 800-m
performance. ASR, 800-m personal best, and SRR best defined the 3 subgroups along a continuum of 800-m runners, with SRR
values as follows: 400–800 m ≥1.58, 800 m ≤1.57 to ≥1.48, and 800–1500 m ≤1.47 to ≥1.36. Conclusion:MSS had the
strongest relationship with 800-m performance, whereby for the same MSS, MAS and ASR showed only small relationships to
differences in 800-m time. Furthermore, the findings support the coaching observation of three 800-m subgroups, with the SRR
potentially representing a useful and practical tool for identifying an athlete’s 800-m profile. Future investigations should
consider the SRR framework and its application for individualized training approaches in this event.
Keywords:middle distance running, training science, maximal sprint speed, maximal aerobic speed
Preparation for 800-m running represents a unique challenge
to the middle-distance coach. With close interplay required
between aerobic and anaerobic/neuromuscular physiology, ath-
letes with distinctly different profiles have an opportunity for
success in the event. Recently, a “changing of the guard”in the
men’s championship 800-m event was revealed, whereby from
2011 onwards World and Olympic medalists were shown to run
predominantly a “gun-to-tape”type race tactic in the final,
1
requiring 100-m sectors that are 0.5 m/s faster than in 2000–
2009. This raises important questions pertaining to the mechani-
cal speed range required in top athletes relative to their aerobic
capabilities.
Previous studies of national and international caliber 800-
and 1500-m runners reveal opposing findings regarding the phys-
iological requirements of 800-m running. For example, Ingham
et al
2
reported that VO
2
max and running economy explained
95.9% of running performance in 800- and 1500-m runners;
however, no speed and power measures were collected. In contrast,
Bachero-Mena et al
3
showed very large relationships between
800-m performance and sprints over 20 m (r=.72) and 200 m
(r=.84), yet aerobic markers were not reported. Several reasons
may explain these contrasting outcomes. First, athletes with diverse
physiological profiles may be competing in the same event. For
example, Schumacher and Muller
4
showed in Olympic gold medal-
winning team pursuit cyclists that the first and second position
riders presented with markedly different anaerobic and aerobic
physiological profiles, yet produced similar individual pursuit
performance times (4:18 vs 4:19). Accordingly, it is possible
that more aerobic-based 800-m runners demonstrate stronger
relationships between aerobic-measured variables and perfor-
mance, whereas more sprint-based 800-m athletes present stronger
correlations with anaerobic and neuromuscular qualities, depend-
ing on the random phenotype predominance of the sample. Second,
it is possible that a cultural endurance-focused training approach
bias has contributed to a production of studies from the more
endurance-based 800-m running subgroup. Third, although the 800
and 1500 m have historically been considered as “similar events,”
2
this belief may require reassessment in light of recent tactical
evolution.
1
Indeed, heterogeneity of performance standard within
“elite”samples may be misleading when it comes to differentiating
elite athlete makeup. For example, conclusions are often drawn on
elite performance when samples may contain only 1 or 2 truly elite
runners (800-m performance ≤1:46).
3,5
Middle-distance coaches have long spoken of 3 subgroups
of middle-distance runners. These include: (1) speed types (400- to
800-m specialists), (2) 800-m specialists, and (3) endurance types
(800- to 1500-m specialists).
6,7
Understanding the athlete subgroup
has substantial influence on the coach’s plan, training program, and
coaching approach. In contrast, the sport science literature has
traditionally treated the 800-m cohort as a single athlete type,
without assessing individual characteristics that might form a
coach’s subgroup. Although a minimum level of both aerobic and
neuromuscular qualities would be required for success in any elite
800-m runner, a deficiency in either component is likely balanced
by a strength in the other to achieve a 2-lap performance.
8
How-
ever, without information defining this variability, clarity of train-
ing methods for this event group cannot be established to the degree
that they have been with runners training for the 1500- to 10,000-m
events.
9
Sandford, Allen, Kilding, and Laursen are with the Sport Performance Research
Inst New Zealand (SPRINZ), Auckland University of Technology, Auckland,
New Zealand. Sandford and Ross are with High Performance Sport New Zealand
and Athletics New Zealand, Auckland, New Zealand. Sandford is also with the
Millennium Inst of Sport & Health in Auckland. Sandford (gareth.sandford@hpsnz.
org.nz) is corresponding author.
501
International Journal of Sports Physiology and Performance, 2019, 14, 501-508
https://doi.org/10.1123/ijspp.2018-0163
© 2019 Human Kinetics, Inc. ORIGINAL INVESTIGATION

Sanders et al
10
recently showed the usefulness of the anaero-
bic power reserve construct for predicting sustainable power
performance across 4 professional road cyclists with largely
diverse peak power profiles (range =1036–1525 W). Therefore,
the anaerobic speed reserve (ASR), defined as the speed range an
athlete possesses between velocity at VO
2
max (vVO
2
max) in the
laboratory (or maximal aerobic speed [MAS] in the field
11
) and
maximal sprint speed (MSS),
12
may likewise prove a useful tool to
better understand the apparent diversity of mechanical profiles
across the 800-m event group. In addition, ASR may provide the
coach and sport scientist a profile for assessing an athlete’s
mechanical limits supported by their metabolic systems (aerobic
and anaerobic) as well as for tracking progress in training.
13
Therefore, the aims of the present study were to (1) determine
MSS and ASR and their relationship with 800-m performance in an
elite middle-distance cohort and (2) using the ASR construct,
investigate the athlete profiles within the event and offer possible
solutions for coaches and scientists to be able to better categorize
800-m athletes.
Methods
Study Overview
To perform this study, the primary researcher traveled to locations
around the world to test participants at their local training venue
during the late precompetition/competition phase of the 2017
athletics season. At each training location, athletes were tested
for their MSS. Within 6 weeks of the MSS assessment, an
outdoor 1500-m race used to estimate MAS, was performed in
competition.
Participants
A total of 19 elite 800- and 1500-m specialists representing 5
different continents (Africa, Europe, North America, Oceania, and
South America) participated in this study (Table 1). The study
inclusion criteria included an 800-m personal best (PB) of
≤1:47.50, and/or a 1500-m PB of ≤3:40, as guided by USA track
and field World Championship trial standards (2017). Season’s
bests (SB) were used throughout the analysis to better reflect an
athletes’current shape (eg, PB could be up to 3 years prior). Each
athlete provided written informed consent to participate in the
study, which was approved by the Auckland University of Tech-
nology Ethics Committee.
Performance Testing
Maximal Aerobic Speed. For MAS assessment, a “gun-to-tape”
1500-m race performed within 6 weeks of MSS assessment was
reflective of an athlete’s absolute time-trial capacity and current
aerobic fitness. In line with the periodization phase described,
data collection aligned well with the period where athletes were
targeting qualifying times and “gun-to-tape”style races led by a
pacemaker to 1000 to 1200 m; an aspect that would also have
likely enhanced the reliability of 1500-m times. From these times,
MAS was predicted using the 1500-m race performance equation
of Bellenger et al
11
:
MAS =TTsð0.766 þ0.117 ½TTdÞ
where TT
s
was the athlete’s average 1500-m speed (in kilometer
per hour) and TT
d
was 1.5 km.
Maximal Sprint Speed. Upon arrival at the track, participants
were informed of the rationale for the 50-m MSS assessment and
maximal nature of the testing protocol. Athlete performance was
measured using a sports radar device (Stalker ATS II System; Radar
Sales, Richardson, TX) over a 50-m sector on the track straight. The
device was placed in the middle of 2 lanes, 2 m behind the start
line, and on a tripod resting 1.5 m from the ground. For live capture
of the athlete’s acceleration trace, the radar was operated remotely
from a laptop to remove the possibility of manual use variability,
using a method that has been shown to be highly reliable (CV =
1.1%) against gold-standard force plates.
14
Instantaneous radar was
used to extract MSS (in meter per second) and split time (in seconds)
from each effort, sampling at 46.9 Hz. Custom-built software
(Goldmine, HPSNZ, NZ), was used to remove postprocessing error
of the acceleration trace from manual inspection of erroneous data
points. Previous investigations have shown the reliability limitation
of postprocessing with “LabVIEW”(Build version: 11.0, National
Instruments Corp, Austin, TX) software.
15
Owing to the experienced status of the athletes, and cultural
differences in warm-up, a semistructured framework was used to
provide consistency across sites. Here, instructions were to take 10
to 15 minutes to prepare for a maximal effort, incorporating
individual needs to feel ready to go. Athletes were familiarized
with the standing start position and instructed to place 1 foot in
front of the other (athlete’s preference), with no backward oscilla-
tion, though a forward lean into the movement was permitted into
the first forward step.
Boundaries for the warm-up includedsome pulse-raisingactivity
(jogging), some drills (A skips, B skips, etc), time for any other
exercises athletes required and 2 to 3 progressive strides in flats,
before transitioning into race spikes, where athletes were asked to
rehearse the standing start in 1 to 2 maximal efforts to 30 m. Athletes
performed the assessment in spikes (n =17)orraceflats (n =2).
Once ready to go, an instruction of “on you”was provided for
the athlete to accelerate in their own time maximally through to the
end of the cones, along with the line at the center of the 2 lanes.
Athletes performed 2 to 3 maximal efforts with ∼3 minutes rest on
rotation at the end of the athlete testing line. The primary variable of
interest taken from the radar for analysis was the MSS, representing
the ceiling of the athlete’s ASR. MSS assessments were conducted
where possible in an indoor location, but where not possible
(6 sites), a wind gauge (Kestrel 5100; Nielsen-Kellerman Com-
pany, Boothwyn, PA) was used to measure wind speed. All MSS
assessments outdoors were captured with 0.5 ± 0.3 m/s tailwind.
Environmental conditions indoors (25.2°C ± 3.5°C, 51.4 ± 10.7%
RH) and outdoors (26.2°C ± 5.0°C, 42.7 ± 22.8%RH) were similar.
One site was at 580-m altitude with all others at sea level.
Speed Reserve Ratio
The speed reserve ratio (SRR) was developed from the ASR
construct as a potentially practical tool for coaches to display
individual athlete profiles in 1 variable, as used in team sports.
16
Whereby:
SRR =MSS ðkm=hÞ=MAS ðkm=hÞ
Data Analysis
Data are presented as mean ± 90% confidence limits (CL) unless
otherwise stated. The relationships between 800-m SB perfor-
mance and MSS, MAS, and ASR (n =10) were determined
from partial correlations using SAS 9.4 (SAS Institute, Cary,
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Table 1 Description of the Participants in the Study
Category of athlete Regions represented Highest competition representation Other details
800-m PB, mm:ss.ms
(mean [SD])
1500-m PB, mm:ss.ms
(mean [SD])
International, n =8 Europe, North America,
South America, and Oceania
Olympic Games/World Championships, n =6
World Indoor Championships, n =1
World Relay Championships, n =1
Includes 1 ×world-record
holder, 2 ×national-record
holders
1:45.55 (1.18) 3:46.69 (8.20)
European, n =3 Europe European U23 Cross Country
European U23 Outdoor Championships
European U20 Outdoor Championships
1×medalist 1:47.07 (0.15) 3:39.93 (3.53)
National, n =2 Oceania National Championship 5 ×national champion
1×national medalist
1:47.80 (1.13) 3:42.34 (5.04)
Collegiate, n =6 Africa, Europe, and North America World University Games, n =3
NCAA Outdoor Championship, n =3
World University Games
2×medalist
Includes African
championship finalist
1:47.90 (1.84) 3:41.40 (3.04)
Abbreviation: PB, personal best; NCAA, National Collegiate Athletic Association.
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NC) and described by magnitude-based inferences.
17
As alluded to
in the introduction, the merging of elite and subelite athlete data
into the same analysis
2,3
may explain disparate outcomes reported
previously. Therefore, two 1500-m specialists who did not have an
800-m SB on record were removed from this part of the analysis.
Five athletes with a SB of >1:47.50 for 800 m were also removed
with times outside cutoffs for elite status.
Ak-means cluster analysis was performed using SAS 9.4 to
investigate the variation in physiological and performance char-
acteristics of world-class 800-m runners. Athletes excluded from
partial-correlation analysis (due to the 800-m focus) were included
for subgroup clustering (n =19). Instruction was given to fit the
collected variables into 3 clusters, as per the aforementioned coach
observations. MAS, MSS, ASR, SRR, body mass, 800-m PB and
SB, 1500-m PB and SB obtained through testing, questionnaire, or
competition data collection were standardized and run through the
cluster analysis to understand which best explained any differences
between groups.
Variables were excluded based on their ability to explain
variation between clusters, with the strongest relationships (highest
R
2
value) used for final subgroup determination. Differences
between clusters were determined using magnitude-based infer-
ences. The following threshold values used for effect size statistics
were ≥0.2 (small), ≥0.6 (moderate), ≥1.2 (large), and ≥2.0 (very
large). The smallest worthwhile change for maximum velocity was
determined as the SD of all 19 athletes’MSS, multiplied by the
effect size.
17
Moderate thresholds were applied across all variables
to acknowledge variability in the MAS equation.
11
To explore the individual variation specifically in the 800 m,
the SRR was used. For this analysis, 10 athletes with SB ≤1:47.50,
who also had a MAS marker within the 6-week window were
assessed. 800-m SB times of these participants ranged from 1:44.50
to 1:47.36.
Results
ASR and 800-m Performance Relationships
Participant details are described in Table 1. MSS and ASR
showed very large negative (both r=−.74 ± .30; very likely)
relationships with 800-m performance time for the same MAS.
In contrast, ASR and MAS had small negative relationships (both
r=−.16 ± .54, possibly) with 800 m when MSS was constant
(Figures 1A–1C).
800-m Subgroup Variation
The ASR, SRR, and 800-m PB accounted for the greatest variation
between the 3 clusters of 800-m athletes (R
2
=.87; very large).
Subgroup performance characteristics are shown in Table 2.
The MSS of 400- to 800-m athletes was faster than the 800-m
specialists (1.8 ± 0.6 km/h, moderate, very likely), and 800- to
1500-m athletes (4.0 ± 0.4 km/h, very large, very likely). The 800-
m specialists had faster MSS than 800- to 1500-m athletes (2.2 ±
1.5 km/h, large, likely). MAS in 400- to 800-m athletes was slower
than both 800-m specialists (−0.5 ± 0.5 km/h, moderate, likely) and
800- to 1500-m athletes (−0.8 ± 0.4, large, very likely). MAS of
800-m specialists was slower than 800- to 1500-m athletes (−0.3 ±
0.3, moderate, possibly). ASR of 400- to 800-m athletes was larger
than 800-m specialists (2.3 ± 0.7 km/h, large, very likely) and
800- to 1500-m athletes (4.3 ± 1.2 km/h, very large, most likely).
ASR of 800 specialists was larger than 800- to 1500-m athletes
(2.0 ± 1.2 km/h, moderate, likely).
The SRR had a large relationship with 800-m performance
(r=.53 ± .43, likely) whereby faster 800-m athletes had a higher
ratio. In addition, body mass showed a large relationship with SRR
(r=.62 ± .34, very likely). 400- to 800-m athletes were heavier
than 800-m specialists (6.4 ± 7.8 kg, moderate, possibly) and 800-
to 1500-m athletes (5.8 ± 11.2 kg, moderate, possibly), with trivial
differences between 800-m specialists and 800- to 1500-m athletes
(−0.6 ± 11.1 kg, possibly).
Discussion
In the present study, we examined for the first time, the role of the
ASR in elite male 800-m running performance, in an era where
faster top speed appears to be a critical performance requirement.
1
Our findings confirm this observation, with a greater MSS (and
therefore ASR) strongly correlated with a faster 800 m. Impor-
tantly, for the same MSS, having a greater MAS or ASR was not
strongly related to changes in 800-m time. These results support the
notion that at an elite level, faster 800-m runners have a larger ASR,
which is related to a higher MSS (Figures 1A and 1C), along with
an already established minimum level of estimated MAS. In
addition, in agreement with longstanding coaching observations,
6,7
we reveal the profiles of three 800-m athlete subgroups, described
along a continuum herein as 400 to 800 m (speed types), 800 m
(specialists), and 800 to 1500 m (endurance types; Table 1).
Finally, we present the SRR construct (Figure 2) as a practical
and easily implemented tool to support a coach’s identification of
the 800-m athlete subgroup, which may aid training approaches
and event specialization.
The unique nature of the global elite study sample (Table 1)
represents a critical addition to the middle-distance literature, with
high relevance to coaches, athletes, scientists, and sports federa-
tions. Importantly, we confirm the role of ASR (through the
function of larger MSS) as a key performance indicator of elite
male 800-m running. Indeed, for the same MSS, having a greater
MAS or ASR was not strongly related to changes in 800-m time.
The paradigm offered by our analysis should consider that once a
certain aerobic standard is reached, MSS becomes a differentiating
factor in elite 800-m runners. In agreement with Bachero-Mena
et al,
3
we found a very large relationship between MSS and 800-m
running performance (Figure 1A). The small relationship with
MAS contrasts the study by Ingham et al,
2
who studied athletes
with slower performance times (1:48.9 ± 2.4), where perhaps the
aerobic component may be a more important differentiator of
slower (≥1:47.50) performance times. As we have shown, in an
elite 800-m running cohort, the strong relationships between 800-m
performance times and MSS (Figure 1A) and ASR (Figure 1B)
demonstrate the importance of possessing advanced speed char-
acteristics alongside an already well-developed aerobic capability.
It appears that to be competitive in the modern-day elite 800 m
era, an MSS of ∼10 m/s is required to cope with the high-speed
demands in the first 200 m of the race (Table 2).
1
Notwithstanding,
the complex phenomenon of any middle-distance performance,
18
amid tactics, trips, mistimed training, injury, illness, and other
uncertainties that occur,
19,20
our data suggest that at the elite level, a
baseline level of MSS/MAS characteristics are required to handle
surging in slow, fast, or moderate paced 800-m events. Critically,
considering the energetic demands of the men’s 800-m (66%
aerobic),
21
neither aerobic nor anaerobic/neuromuscular compo-
nents of training can be neglected.
Historically, the most common coaching approaches for dif-
ferentiating 800-m athletes into subgroups involves using 400-m
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Figure 1 —Relationship between (A) MSS and (B) ASR with 800-m season’s-best race performance in 10 elite-class male 800-m
runners. (C) Partial correlation magnitudes with 90% confidence limits; gray area represents trivial relationship. Change *possibly
substantial, **likely substantial, and ***very likely substantial. ASR indicates anaerobic speed reserve; MAS, maximal aerobic
speed; MSS, maximal sprint speed.
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and 1500-m PB times to segregate an athlete into 400- to 800-m or
800- to 1500-m subgroups.
6,7
The present investigation offers the
SRR as an additional tool for classifying athletes into subgroups
(Table 2; Figure 2). MAS differences between 400 to 800 m and
800-m specialists, and 800-m and 800- to 1500-m subgroups were
moderate, whereas they were large between 400- to 800-m and
800- to 1500-m athletes. However, the differences in MSS were
much greater between subgroups (Table 2). Therefore, SRR may be
the most effective metric for easily identifying an athlete’s sub-
group, as evidenced by the cluster analysis, which revealed that
ASR, SRR, and 800-m PB accounted for the greatest amount of
subgroup variation. Further studies investigating middle distance
running should consider stating the distribution of athlete sub-
groups in the methodology sections and perform data analysis per
subgroup to provide readership with outcomes of interventions
(eg, training or nutritional) on specific subgroups with similar
profiles (Table 2).
Many questions remain across 800-m subgroup characteriza-
tion, in terms of how mechanical and metabolic components may
explain these results. The critical speed describes the divide
between steady state and nonsteady state exercise, with the finite
work capacity above critical speed termed Dprime (D′).
22
D′is our
current best estimate of an athlete’s so-called anaerobic capacity, a
measurement that has challenged physiologists for years.
23
Previ-
ously,
24
it was shown that Finnish national 800- and 1500-m
distance runners and US 400-m athletes (PB range: 44–52.5 s)
had superior anaerobic work capacity (as defined from the maximal
anaerobic running test) compared with long-distance runners and
control (sprinters and jumpers) groups. The 400-m athletes had
superior anaerobic work capacity and the highest MSS in compari-
son to the national Finnish 800- and 1500-m athletes; however,
individual event comparisons were not provided. A fast MSS
determines the proportion of ASR an athlete can work at and
may relate to high-intensity training tolerance.
25
Body mass showed a large positive relationship with SRR
(r=.62), which may be explained by the underlying ground force
characteristics, with MSS ultimately limited by the impulse an
athlete can produce.
26
Van Der Swaard
27
showed that fast-twitch
muscle fiber composition and vastus lateralis muscle volume
explained 65% of the normalized peak power output in cycling.
Therefore, greater muscle mass differences (inferred from body
mass measurement) between subgroups may explain part of their
different MSS capability (Table 2). Furthermore, muscle composi-
tion differences between the subgroups have implications for VO
2
kinetics, with slower oxygen flux through type IIa and IIx fibers,
28
as well as smaller capillary density and electron transport chain
enzymes versus type I fibers.
29
Differences in metabolic efficiency
(lower efficiency in type II fibers) may have implications for
metabolic perturbation during exercise intensities above critical
speed,
30
such as in 800-m racing, therefore, reiterating the need to
characterize D′(alongside MSS) in 800-m subgroups. We postu-
late that perhaps 800-m specialist athletes are event experts, in part
due to a predominance of IIa fiber types, which provide the unique
blend of higher force generation characteristics than type I fibers,
Table 2 Performance (mm:ss.ms) and Profile Characteristics of the 800-m Subgroups (N =19), Mean (SD)
400- to 800-m athletes (n =10) 800-m specialist (n =6) 800- to 1500-m athletes (n =3)
800-m personal best 1:46.21 (1.16) 1:46.37 (1.43) 1:49.53 (1.28)
1500-m personal best 3:44.05 (4.33) 3:42.13 (3.87) 3:38.89 (0.87)
Body mass, kg 72.2 (8.3) 65.8 (8.3)
a
66.4 (6.9)
a,e
MSS, km/h 35.48 (0.30)
g
33.68 (0.63)
c
31.49 (0.99)
c,f
MAS, km/h 22.41 (0.62 22.76 (0.50)
b
23.21 (0.06)
c,e
ASR, km/h 14.46 (1.00)
g
12.12 (0.61)
c
10.13 (0.76)
d,f
SRR ≥1.58 ≤1.57 to ≥1.48 ≤1.47 to ≥1.36
Abbreviations: ASR, anaerobic speed reserve; MAS, maximal aerobic speed; MSS, maximal sprint speed; SRR, speed reserve ratio.
a
Possibly substantial difference from 400–800 m.
b
Likely substantial difference from 400–800 m.
c
Very likely substantial difference from 400–800 m.
d
Most likely
substantial difference from 400–800 m.
e
Possibly substantial difference from 800-m specialist.
f
Likely substantial difference from 800-m specialist.
g
Very likely
substantial difference from 800-m specialist.
Figure 2 —Speed reserve ratio (maximum sprint speed [km/h]/maximal aerobic speed [km/h]) of 10 elite male 800-m runners. Lines depict 800-m
subgroups from cluster analysis.
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and greater metabolic efficiency than type IIx, though this warrants
confirmation using noninvasive muscle fiber-type estimation
alongside SRR.
31
Limitations
Our current methods used a 1500-m race for MAS prediction,
potentially creating bias toward a better MAS prediction in 800 m
rather than 1500-m specialists. With the current methods and
logistics of the study collection, a race (that was already in
most athlete’s calendars), was deemed as the most practical
method for capturing the MAS estimate in this elite sample during
competition. However, specialization in competition today means
that some 800-m athletes rarely, if ever, perform 1500-m races.
The present sample also represents a distribution that unintention-
ally reflects clustering around the qualifying mark for nationals
(1:47.50), similar to the Bannister 4-minute mile phenomenon,
32
in addition to the difficulty of capturing World-Class participants
for a research study. As such, this should be kept in mind with
study interpretation.
The unique nature of this investigation into the speed char-
acteristics of elite athletes in their various locations meant that
laboratory assessment of vVO
2
max was not practically possible, so
a sound prediction method was a necessity. In this regard, it is also
important to highlight that the variability of elite middle-distance
racing is only ∼1%,
33
far less than typical metabolic cart measure-
ments (coefficient of variation VO
2
,∼4.7%
34
). In addition, athletes
may not always produce “true maximum”results in laboratory
settings.
17
Although unique, we believe our methodology provides
a robust level of ecological validity and practicality for athletes and
coaches.
35
Furthermore, the scientific literature has a comprehen-
sive understanding of the aerobic determinants of elite middle-
distance running, but data are scarce with respect to the MSS
characteristics of elite 800-m runners.
Practical Application
An athlete’s ASR and SRR showed the greatest variation between
the 3 subgroups of elite male 800-m runners, and these variables,
therefore, represent practical markers that coaches can easily
measure to categorize their athletes’subgroup profiles. Impor-
tantly, many training studies show large individual variation in
response to a given intervention, with the “responder and nonre-
sponder concept”often attributed to the outcome.
36
Another
explanation may be that for some athlete profiles, the stimulus
provided could be inappropriate. For example, it is unlikely an
anaerobic/neuromuscular-based athlete would respond to high
densities of continuous aerobic work. The SRR framework
(Table 2; Figure 2) could advance the profiling of athletes into
subgroups based on their ASR characteristics, which may allow
precise selection of more favorable training content. Such an
approach has been successfully used in team sports,
37
and thus
provides a fruitful opportunity for further understanding the indi-
vidual training response required for different 800-m subgroups.
Conclusion
A larger ASR through the function of a faster MSS had the strongest
relationship with elite 800-m performance. When MSS was held
constant, MAS and ASR had only small relationships to differences
in 800-m time. In addition, the SRR, defined as the MSS/MAS, may
represent a useful tool to identify an athlete’s 800-m subgroup.
Future investigations should consider the SRR framework and its
application for individualized training approaches in this event.
Acknowledgments
The authors thank the athletes, coaches, and scientists who participated in
the project. We are also grateful to the funding partners—High Perfor-
mance Sport New Zealand, Athletics New Zealand, and Sport Performance
Research Institute–AUT University.
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