Vol.:(0123456789)
Sports Medicine (2023) 53:1595–1607 
https://doi.org/10.1007/s40279-023-01850-z
SYSTEMATIC REVIEW
Long‑Term Development of Training Characteristics 
and Performance‑Determining Factors in Elite/International 
and World‑Class Endurance Athletes: A Scoping Review
Hanne C. Staff1  · Guro Strøm Solli1,2 · John O. Osborne1  · Øyvind Sandbakk1,3
Accepted: 31 March 2023 / Published online: 13 May 2023 
© The Author(s) 2023
Abstract
Objective In this scoping review, we aimed to 1) identify and evaluate existing research that describes the long-term develop-
ment of training characteristics and performance-determining factors in male and female endurance athletes reaching an elite/
international (Tier 4) or world-class level (Tier 5), 2) summarize the available evidence and 3) point out existing knowledge 
gaps and provide methodological guidelines for future research in this field.
Methods This review was conducted following the Joanna Briggs Institute methodology for scoping reviews.
Results Out of 16772 screened items across a 22-year period (1990-2022), a total of 17 peer-reviewed journal articles met the 
inclusion criteria and were considered for further analysis. These 17 studies described athletes from seven different sports and 
seven different countries, with 11 (69%) of the studies being published during the last decade. Of the 109 athletes included 
in this scoping review, one quarter were women (27%), and three quarters were men (73%). Ten studies included information 
about the long-term development of training volume and training intensity distribution. A non-linear, year-to-year increase 
in training volume was found for most athletes, resulting in a subsequent plateau. Furthermore, 11 studies described the 
development of performance determining factors. Here, most of the studies showed improvements in submaximal variables 
(e.g., lactate/anaerobic threshold and work economy/efficiency) and maximal performance-indices (e.g., peak speed/watt 
during performance testing). Conversely, the development of VO2max was inconsistent across studies. No evidence was found 
regarding possible sex differences in development of training or performance-determining factors among endurance athletes.
Conclusion Overall, a low number of studies describing the long-term development of training and performance-determining 
factors is available. This suggests that existing talent development practices in endurance sports are built upon limited sci-
entific evidence. Overall, there is an urgent need for additional long-term studies based on systematic monitoring of athletes 
from a young age utilizing high-precision, reproducible measurements of training and performance-determining factors.
 * Hanne C. Staff 
 
hanne.c.staff@uit.no
 
Guro Strøm Solli 
 
guro.s.solli@nord.no
 
John O. Osborne 
 
john.osborne@uqconnect.edu.au
 
Øyvind Sandbakk 
 
oyvind.sandbakk@ntnu.no
1 
School of Sport Sciences, UiT The Arctic University 
of Norway, Campus Tromsø, Hansine Hansens veg 18, 
9019 Tromsø, Norway
2 
Department of Sports Science and Physical Education, Nord 
University, Bodø, Norway
3 
Department of Neuromedicine and Movement Science, 
Centre for Elite Sports Research, Norwegian University 
of Science and Technology, Trondheim, Norway
1596
 
H. C. Staff et al.
Key Points 
Only 17 studies described the long-term development 
of training characteristics and performance-determining 
factors of elite/international and world-class athletes, 
with 16 studies using a retrospective study design, 11 
studies being case studies, and the majority of partici-
pants being male.
A non-linear year-to-year increase in training volume, 
mainly driven by increases in low-intensity training until 
reaching a subsequent plateau at elite/international and 
world-class level was found for most of the included 
endurance athletes.
Consistent improvement in maximal performance tests 
and submaximal performance indices were found for 
most athletes, while the developments in maximal oxy-
gen uptake were inconsistent across studies.
This scoping review highlights an urgent need for addi-
tional long-term studies based on systematic monitoring 
of athletes and suggests that a common framework is 
required for comparing results across different long-term 
studies in endurance sports.
1 Introduction
Long-term performance development in endurance sports is 
determined by a multifaceted interaction of manifold vari-
ables. Extensive sport-specific practice, including optimal 
progression of training volume, frequency, and intensity 
distribution, is required to stimulate sport-specific adap-
tive responses. This process normally requires a relatively 
long period (10–15 years) of dedicated training, although 
recent studies report considerable variation within and 
across sports in the amount of training and the time needed 
to reach elite and super-elite levels [1–4]. In addition to the 
obvious role of the genetic potential, the realization of ath-
letes’ potential is also influenced by motivation, skillset and 
experience of the athlete and coach, training peers, support-
ing staff, training environment and facilities, well-being, and 
life balance [5, 6].
The training characteristics among elite/international and 
world-class athletes in endurance sports have been widely 
described in retrospective studies [7–10]. The outcomes 
from this research have emphasized the importance of high-
endurance training volumes (TV) with sport-specific dif-
ferences owing to variations in muscular loads and injury 
risks across exercise modalities [10]. Furthermore, there 
is an established consensus that a relatively long period of 
dedicated training is required to tolerate these TV and reach 
an elite level [4, 11–13]. Accordingly, gradual progression 
in TV is required to tolerate and respond positively to the 
overall training load. However, training load can also be 
manipulated by changing the intensity and/or frequency of 
training, although limited evidence exists on how the pro-
gressive increase in these factors interacts to provide the 
best possible training stimulus and to avoid setbacks, thereby 
ensuring continuity to optimize the development of physi-
ological factors and performance [9, 14].
Describing and comparing the intensity distribution of 
endurance training (TID) across different studies and ath-
letes necessitates a standardized intensity scale. Here, a 
three-zone model is often used, with the zones referred to 
as: low-intensity training (LIT), moderate-intensity train-
ing (MIT), and high-intensity training (HIT). Although both 
conceptual and practical challenges are associated with the 
division of intensity zones, the separation of each zone using 
reproducible blood lactate anchor points, combined with 
corresponding heart rate and ratings of perceived exertion, is 
arguably the most effective available method [9, 15]. Other 
methods that are used to determine intensity zones include 
ventilatory thresholds or critical power [16, 17]. Although 
there are differences in the methods for quantifying training 
intensity, there seems to be similarities in the basic TID pat-
terns selected by successful endurance athletes [9]. Previous 
studies report that the training of successful endurance ath-
letes include 70–90% LIT, with the remaining 10–30% per-
formed as MIT and HIT [9, 18, 19]. This variation in TID is 
likely caused by differences in the demands of the examined 
sports, individual development areas, and the methodology 
used to determine LIT, MIT, and HIT [10, 20, 21]. Still, it 
is unclear if the same TID should be employed in all stages 
of the development process in an endurance athlete’s career.
Successful endurance performance is characterized by 
high levels of maximal oxygen uptake (VO2max), anaerobic 
threshold or lactate threshold, and work economy or effi-
ciency [22]. However, the long-term development of these 
performance-determining factors is influenced by vari-
ous aspects such as training, psychophysiological matura-
tion, and sex, resulting in different developmental patterns 
throughout an athlete’s career [23]. Therefore, an overview 
of the studies including information about the long-term 
development of training characteristics and performance-
determining factors of elite/international and world-class 
athletes would provide a starting point for better under-
standing the long-term development process of endurance 
athletes.
Accordingly, this scoping review aimed to (1) iden-
tify and evaluate existing research that has focused on 
the long-term development of training characteristics and 
1597
Long-Term Development of Training Characteristics and Performance-Determining Factors
performance-determining factors in male and female endur-
ance athletes reaching an elite/international or world-class 
level, (2) summarize the available evidence, and (3) point 
out existing knowledge gaps and provide methodological 
guidelines for future research in this field.
2  Methods
This scoping review was conducted following the Joanna 
Briggs Institute methodology for scoping reviews [24]. The 
review protocol and search results for each step of the review 
are available on the Open Science Framework (https:// osf. 
io/ b3fwu/). The Preferred Reporting Items for Systematic 
reviews and Meta-Analyses extension for Scoping Reviews 
Checklist (PRISMA-ScR) was followed step by step [25].
An initial limited search of PubMed was undertaken to 
identify potentially relevant articles. The words contained 
in the titles and abstracts of relevant articles, and the index 
terms used to describe the articles, were then utilized to 
develop a full search strategy. Broad inclusion criteria were 
initially employed to increase the probability of mapping 
the existing literature of interest and obtaining a compre-
hensive list of articles. The search strategy (Table 1), includ-
ing all identified keywords and index terms, was adapted 
for use across four major databases: PubMed, PsychINFO, 
SPORTDiscus, and Web of Science. Boolean search terms 
were used to link nested concepts.
Once the search strategy was completed, search results 
were collated and exported to EndNote referencing soft-
ware (version X9.3.3; Clarivate Analytics, Philadelphia, 
PA, USA). Duplicates were removed using the duplication 
detection tool of the Endnote software, before all remaining 
unique records were made available to reviewers for further 
processing (i.e., study screening and selection). In addition 
to the systematic search of the four primary databases, an 
additional search was performed using Google Scholar, with 
the first 200 results exported for further screening. The ini-
tial database search output can be viewed at https:// osf. io/ 
b3fwu/.
The types of publications included in the first stage of the 
literature review were: peer-reviewed journal papers (pub-
lished between the period 1 January, 1990 and 8 December, 
2022, written in English and involving human participants), 
reviews, and meta-analyses; while non-peer reviewed arti-
cles published in magazines, unpublished doctoral disser-
tations, and masters’ theses were excluded. Both quantita-
tive, qualitative, and mixed-method studies were included 
to consider different aspects of the development process. 
To chart data related to long-term development, the stud-
ies were included if training or physiological characteristics 
were reported for ≥ 2 years. The participant classification 
Table 1  Search strategy, 
including all identified 
keywords and index terms
MeSH Medical Subject Headings, RPE ratings of perceived exhaustion
An asterisk (*) indicates a Boolean operator for truncation searching from the word stem, while a question 
mark (?) represents a wild card replacement of a single letter
MeSH terms
Concept 1
Concept 2
Concept 3
Concept 4
Athletic level
Population
Sex differences
Training characteristics
Athletes
Sports
Elite
Professional
Medalist
Olympic
“High performance”
“World class”
“World champion”
“Highly trained”
Endurance
Aerobic
Cycli*
Skier*
“Cross country”
Skiing
Runn*
Triat*
Biath*
Swim*
Rowing
Rower
Orienteer*
“Long distance”
Marathon
Athletics
Skating
Biking
Female
Woman/Women
Girl
Male
Man/Men
Boy
Sex
Gender
Training
Endurance
Load
TRIMP
Intensity
Speed
Velocity
Frequency
Volume
Distance
Distribution
Time
RPE
Mode
Modality
Movement
Activity
Terrain
Periodi?ation
Tapering
Peaking
Altitude
Progression
Longitudinal
1598
 
H. C. Staff et al.
framework of McKay et al. [26] was used and only stud-
ies with participants classified as Tier 4 (elite/international 
level) or Tier 5 (world-class level) were included.
The review process consisted of three levels of screening: 
(1) an initial title screening; (2) an abstract review; and (3) 
a full-text review. Two investigators (HS and JOO) inde-
pendently screened all articles against the forementioned 
inclusion and exclusion criteria and then compared results. 
Where consensus was not reached, it was resolved by means 
of consolidation with a third independent researcher (GSS). 
Reasons for the exclusion of any full-text source are reported 
in the scoping review report. The search results are presented 
in a PRISMA flow diagram (Fig. 1) [27, 28]. Following the 
final full-text review screening step, an expert panel (n = 6) 
of experienced academics in exercise physiology and athlete 
development was assembled to review the included stud-
ies and suggest any additional relevant articles that could 
be considered for inclusion. Snowball searching was also 
employed on the reference lists of the included studies, to 
identify any other relevant sources.
A data extraction form was developed and key infor-
mation on the selected articles, population, concept, and 
context was collected. This form was reviewed and tested 
by all research team members before implementation, to 
ensure that the form accurately captured the necessary data. 
Extracted study variables included: primary author, year of 
publication, athletes’ country, study aim/purpose, sample 
description and size, participant details, study methodology, 
body composition, training characteristics (TV, TID), physi-
ological characteristics (VO2max, submaximal responses, per-
formance indicators), and performance. The charting process 
was an iterative process with three researchers (HS, JOO, 
and GSS) extracting the data.
3  Results
3.1  Study Characteristics
A total of 17 peer-reviewed journal articles were included. 
Sixteen of these studies used a retrospective study design, 
with a mean duration of ~ 7 years (range 2–17 years). Out of 
the 17 studies, ten included men exclusively, five included 
only women, and two included a mix of men and women. 
Cumulatively, the studies included a total of 109 partici-
pants, with approximately a quarter (n = 29; 27%) being 
women. The two studies that included both sexes represented 
two-thirds (n = 73; 67%) of the total participants, with a total 
of 24 women and 49 men. The five women-only studies were 
all individual case studies, accounting for just 5% of the 109 
Records identified from 
databases (n = 16,772)
• 
PubMed (n = 2,728)
• 
SPORTDiscus (n = 5,653)
• 
Web of Science (n = 7,656) 
•
PsycInfo (n = 735) 
Duplicates removed before screening
(n = 4,411)
Records title screened
(n = 12,361)
Records excluded at title screening
(n = 11,390)
Full-text articles assessed for 
eligibility (n = 132)
• 
Databases (n = 121) 
• 
Google Scholar (n = 11) 
Full-text articles excluded:
• 
Intervention duration too short (n = 33) 
• 
Out of scope (n = 26) 
• 
Not elite-level athletes (n = 24) 
• 
Review paper (n = 18) 
• 
Age (n = 10) 
• 
Not endurance exercise (n = 4) 
• 
No development (n = 2) 
• 
Not English language (n = 1) 
•
Cannot access full-text (n = 1)
Records identified from 
Google Scholar (n = 200)
Additional records identified from:
• 
Expert reference group (n = 6) 
• 
Citation searching (n = 6) 
Full-text articles excluded:
• 
Previous excluded (n = 1) 
• 
Out of scope (n = 2) 
• 
Not elite-level athletes (n = 3) 
• 
Not endurance exercise (n = 2) 
Studies included (n = 17) 
• 
Database (n = 13) 
• 
Alternative sources (n = 4) 
Identification of studies via databases 
Identification of studies via other methods
Identification
Screening
Included
Records removed before screening 
(n = 78)
• 
Duplicate records (n = 7) 
•
Duplicate to database search (n = 71)
Records abstract screened
(n = 122)
Records excluded at abstract 
screening (n = 111)
Records abstract screened
(n = 971)
Records excluded at abstract 
screening (n = 850) 
Eligibility
Fig. 1  Preferred Reporting Items for Systematic reviews and Meta-
Analyses (PRISMA) flow diagram showing the flow of informa-
tion through the review process [28]. From Page MJ, McKenzie 
JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The 
PRISMA 2020 statement: an updated guideline for reporting system-
atic reviews. BMJ 2021;372:n71. https:// doi. org/ 10. 1136/ bmj. n71
1599
Long-Term Development of Training Characteristics and Performance-Determining Factors
total participants, while men-only studies represented 28% 
(n = 31). A total of 11 different studies were individual case 
reports. Athletes from seven Olympic endurance sports were 
represented in the study, middle- and long-distance run-
ning (n = 41); swimming (n = 41); cycling (n = 13); rowing 
(n = 6); triathlon (n = 6); biathlon (n = 1); and cross-country 
skiing (n = 1), while only one athlete represented the Para-
lympic disciplines (swimming). The majority of included 
studies (n = 11; 65%) were published after 2010. Athletes 
from seven countries were included, with the majority of 
athletes (85%) from Spain (n = 52) and Australia (n = 40), 
and the remaining from Norway (n = 7), Croatia (n = 4), UK 
(n = 3), France (n = 2), and Belgium (n = 1).
3.2  Training Characteristics
The ten studies that provided information about the long-
term development of training characteristics are presented in 
Table 2. Nine of the studies were individual case studies that 
were conducted on athletes in cross-country skiing, biathlon, 
running, cycling, rowing, and para-swimming. Six studies 
described training data that ranged from 6 to 17 years dura-
tion. No information about training before a junior age was 
reported by any of the studies. Table 2 includes a summary 
of TV and TID from the included studies. Other important 
training characteristics such as training frequency, strength, 
speed, and altitude training were rarely described and are 
not included in Table 2. Specifically, four studies included 
information about training frequency [29–32], three stud-
ies reported strength and speed training [30, 33, 34], and 
four studies included information about the use of altitude 
training.[30, 33–35]. One study had a detailed description 
of the altitude training during the 5 most successful years 
(30–35 years of age) but no information about altitude train-
ing from earlier years was presented [30]. The other studies 
only briefly described that altitude training was employed, 
without providing any detailed data.
3.2.1  Training Volume
In total, eight studies reported a progressive non-linear 
increase in TV [29, 30, 32–37]. Two female world-class 
athletes, from cross-country skiing and marathon running, 
had relatively low TV at a junior age, and increased their 
TV by 80–500% over a 10- to 12-year period, from 18 to 
20 years of age until the age of peak performance [30, 35]. 
A similar pattern was seen in two male athletes, from row-
ing and cycling, with a 50–80% increase in TV from the age 
of 18–23 years [29, 36], in one female para-swimmer with 
an almost 70% increase in TV from the age of 23–26 years 
[34] and in two male middle-distance runners from the age 
of 17–21 years with TV increases of approximately 50% and 
66% [32]. In contrast, a much lower increase in TV (30%) 
was reported in a world-class male biathlete from the age 
of 21–31 years [33]. Three studies reported a plateau in TV 
(500–900 h·year−1) between the ages of 26–30 years [30, 
31, 33]. Particularly large increases in TV were observed to 
occur relatively early in the development process, such as a 
60% increase in TV from the age of 20–24 years in a world-
class female cross-country skier and a 60% TV increase from 
the age of 18–20 years for a male Spanish cyclist [30, 36].
3.2.2  Training Intensity Distribution
Training intensity distribution was described in six indi-
vidual case studies [29, 30, 33, 34, 37, 38]. One of these 
studies reported increased LIT and MIT, and an associ-
ated decrease in the amount of HIT, at a later stage in the 
career of a female world-class cross-country skier [30]. Two 
studies showed a change towards a higher volume of both 
LIT and HIT, but reduced volume in MIT, for male rowers 
(number of kilometers rowed per week) and long-distance 
runners (relative distribution) [29, 38]. In contrast, a middle-
distance runner reported an increase in the number of kilo-
meters run per week at both LIT, MIT, and HIT from the 
age of 17–22 years [37]. Finally, a relatively stable TID was 
reported over 10 years in a world-class male biathlete and 
over 4 years in a world-class para-swimmer [33, 34].
3.3  Performance‑Determining Factors
The 11 studies that describe the development of physiologi-
cal parameters are presented in Table 2. Five of the studies 
were individual case studies and described world-class ath-
letes in cross-country skiing, rowing, and running. Only two 
studies included both male and female athletes.
An increase in VO2max was reported in four studies [29, 
38–40]. The relative (i.e., body mass normalized) VO2max 
of a male rower increased by 4% from the age of 25 years 
until he retired at 32 years [39]. Two other studies on male 
rowers found a 29% absolute to 26% relative increase in 
VO2max from 16 to 20 years [29, 40]. In one of these stud-
ies, a further 13% increase was observed from the age of 
20–27 years, before stabilizing at 28 years [29]. An 11% 
increase in relative VO2max was also reported in a male mid-
dle-distance runner who altered his TID by increasing the 
proportion of LIT and HIT, but decreasing MIT, over two 
consecutive seasons [38].
Five studies found no change in relative values of VO2max 
of elite/international and world-class level athletes in long-
distance running, triathlon, cycling, and cross-country skiing 
[30, 35, 41–43]. Six studies described improvements in sub-
maximal performance-determining variables (e.g., lactate/
anaerobic threshold and/or economy/efficiency) [29, 30, 35, 
38, 40, 44] and six studies showed improvements in per-
formance indicators (e.g., maximal speed, maximal power 
1600
 
H. C. Staff et al.
Table 2  Overview of the development of training characteristics and physiological-determining factors
References
Participants 
Nation and sport 
n (sex)
Age (y)
Time 
period (y)
Training characteristics 
TV development
TID development
Performance-determining factors 
VO2max 
Submaximal responses
Maximal performance indicators
Female population
 [30]
Norwegian XC skier;
Tier 5;
(♀ = 1);
18–35 y
17
Age 20–35 y.:
↑TV 522–940 h·y−1 (+ 80%)
↑LIT ~ 430 to ~ 800 h·y−1
Age 20–23 and 29–35 y: 
MIT + HIT ~ 60 h·y−1
Age 23–28 y: MIT + HIT ~ 80 h·y−1
Age 20–27 y: LIT/MIT/
HIT ~ 88/2/10%
Age 28–35 y: LIT/MIT/HIT ~ 92/3/5%
Age 30–35 y (five most successful 
seasons):
 ↔ VO2max = 67.7 ± 1.7 mL·kg−1·min−1
 ↔ vAT = 10.7 ± 0.4 km·h−1 (running 
@10.5% inclination)
 ↔ AT =  ~ 89% of VO2max
 [35]
British marathon runner;
Tier 5;
(♀ = 1);
19–30 y
12
Age 18–29 y:
↑TV from 25–30 miles·wk−1 to 
120–160 miles·wk−1 (380–433%)
↑TV from 40–48 km·wk−1 to 
193–258 km·wk−1 (382–438%)
Age 18–29 y:
VO2max =  ~ 70 mL·kg−1·min−1 (range 
65–80 mL·kg−1·min−1)
↑vVO2max = 20.5–23.5 km·h−1 (+ 15%)
↓VO2 @16 km·h−1 = 205–
175 mL·kg−1·km−1 (− 15%)
↑LT =  ~ 15.5 km·h−1 to ~ 17.5–
18.5 km·h−1 (+ 13–19%)
 [44]
British marathon runner;
Tier 5;
(♀ = 1);
18–22 y
5
Age 18–22 y:
↓VO2max = 72.8–66.7 mL·kg−1·min−1 
(− 8%)
↑LT = 15–18 km·h−1 (+ 20%)
↑vVO2max = 19.5–22 km·h−1 (+ 13%)
↓VO2@16 km·h−1 = 53–48 mL·kg−1·m
in−1 (+ 9%)
 [34]
Norwegian Paralympic swimmer;
Tier 5;
(♀ = 1);
23–26 y
4
Age 23–26 y:
↑TV 388–656 h·y−1 (+ 69%), 1126–
1993 km·y−1 (+ 77%)
 ↔ LIT/MIT/HIT ˃90/2–4/3–6% (of 
total training)
 [31]
Norwegian marathon runner;
Tier 5;
(♀ = 1);
25–26 and 29–30 y
2
Age 25–26 y (track focus):
TV = 123 km·wk−1 (119–
132 km·week−1)
Age 29–30 y (marathon focus):
TV = 121 km·wk−1 (first 26 weeks of 
the year)
↓TV than current marathon runners
Similar TV when changing from track 
races to marathon races
Male population
 [29]
Belgium rower;
Tier 5;
(♂ = 1);
16–30 y
15
From junior (18 y) to senior (23 y):
↑TV 4372–6091 km·y−1 (+ 39%), 
11.3–17.2 h·wk−1 (+ 52%)
↑LIT = 4021–5664 km·y−1 (+ 40%)
↓MIT = 218–121 km·y−1 (-44%)
↑HIT = 87–280 km·y−1 (+ 221%)
Age 16–20 y: ↑VO2max = 4.1–5.3 
L·min−1 (+ 29%)
Age 20–27 y: ↑VO2max = 5.3–6.0 
L·min−1 (+ 13%)
Age 27–30 y: ↔  VO2max = 6.0 L·min−1
Age 16–27 y: ↑POLa4 = 200–404 W 
(+ 101%)
Age 27–30 y: ↔  POLa4 = 396 W
Age 16–25 y: ↑POmax = 330–536 W 
(+ 62%)
Age 25–30 y: ↔  POmax = 536 W
1601
Long-Term Development of Training Characteristics and Performance-Determining Factors
Table 2  (continued)
References
Participants 
Nation and sport 
n (sex)
Age (y)
Time 
period (y)
Training characteristics 
TV development
TID development
Performance-determining factors 
VO2max 
Submaximal responses
Maximal performance indicators
 [33]
French biathlete;
Tier 5;
(♂ = 1);
19–31 y
11
Age 19–31 y:
↑TV =  ~ 530–700 h·y−1 (+ 32%)
Age 19–30 y:
 ↔ LIT/MIT/HIT ~ 86/3/4% (of total 
training)
Age 30–31 y:
↑MIT = 7.4% (of total training)
 [39]
French rower;
Tier 5;
(♂ = 1);
26–36 y
10
Age 26–32 y:
↑VO2max = 67.6–70.7 mL·kg−1·min−1 
(+ 5%)
↑POmax = 455–461 W (+ 1%)
 [40]
Croatian rowers;
Tier 5;
(♂ = 4);
16–21 y
6
Age 16–20 y: ↑VO2max = 61.5–
69.7 ml·kg−1·min−1 (+ 26%)
Age 20–21 y: ↔ VO2max = 69.7 mL·kg
−1·min−1
Age 16–21 y:
↑POAT = 297–359 W (+ 21%)
↑POVO2max = 400–481 W (+ 20%)
 [36]
Spanish
cyclist;
Tier 4;
(♂ = 1);
18–23 y
6
Age 18–23 y:
↑TV = 526–943 h·y−1 (+ 79.2%), 
14.733–29.383 km·y−1 (+ 100%)
Large increase (60–62%) before 
becoming professional, but smaller 
increases afterwards
 [32]
Norwegian MD runners;
Tier 5;
(♂ = 3; HI, FI, and JI);
17–28 y
6
HI age 17–21 y: ↑TV = 100–110 to 
156 km·wk−1 (~ + 50%)
FI age 17–20 y: ↑TV = 70–80 to 
120–130 km·wk−1 (~ + 66%)
JI age 17–18 y: TV = 130–
140 km·wk−1
All had a similar TV = 150–
160 km·wk−1 in the 2019 preparation 
period (HI 28 y, FI 26 y, JI 19 y)
 [37]
Norwegian MD runner;
Tier 5;
(♂ = 1);
17–21 y
5
Age 17–21 y:
↑TV = 100–110 to 145–160 km·wk−1 
(~ + 50%)
↑LIT =  ~ 80 to ~ 110 km·wk−1 
(~ + 37%)
↑MIT =  ~ 10 to ~ 20 km·wk−1 
(~ + 100%)
↑HIT =  ~ 2 to ~ 3 km·wk−1 (~ + 50%)
Training recorded 10 weeks. January-
March
 [43]
Spanish cyclists;
Tier 5;
(♂ = 12);
22–27 y
5
Age 22–27 y:
 ↔ VO2max = range 75.5–
77.3 mL·kg−1·min−1
↑DE = 24–27%
 [42]
Spanish triathletes;
Tier 4;
(♂ = 6);
24–25 y
2
Age 24–25 y:
 ↔ VO2max = range 77.8–
77.4 mL·kg−1·min−1
 ↔  POmax = range 5.7–5.9 W·kg−1)
3-km TT (as running and running after 
cycling) did not change
1602
 
H. C. Staff et al.
output, and speed at VO2max) [29, 35, 38–40, 44] over dura-
tions of 2–17 years in world-class runners, cross-country 
skiers, and rowers.
4  Discussion
This scoping review aimed to (1) identify and evaluate exist-
ing research that has focused on the long-term development 
of training characteristics and performance-determining fac-
tors in male and female endurance athletes reaching an elite/
international or world-class level, (2) summarize the avail-
able evidence, and (3) point out existing knowledge gaps 
and provide methodological guidelines for future research 
in this field.
In total, 17 studies were included in the review, with all 
but one using a retrospective study design and the major-
ity of participants being male. A non-linear year-to-year 
increase in TV was reported for most athletes, resulting in 
a plateau at the elite/international and world-class levels. 
Only six case studies reported details about the development 
of TID, with all showing an increased volume of LIT while 
the long-term changes in MIT and HIT distribution varied 
across studies. Improvements in submaximal performance-
determining factors (e.g., lactate/anaerobic threshold and 
work economy/efficiency) and various performance indices 
(e.g., peak speed/watt during performance testing) were 
reported for seven of the studies, with inconsistent find-
ings in the ten studies reporting long-term development of 
VO2max. No evidence regarding possible sex differences in 
the development of training or performance-determining 
variables among endurance athletes reaching an elite/inter-
national or world-class level was described for any of the 
included studies.
4.1  Study Characteristics
Only studies with elite/international or world-class level 
athletes (i.e., performance level Tier 4 and 5) as classi-
fied according to the definition by McKay et al. [26] were 
included in the review. Accordingly, this criterion decreased 
the pool of potentially relevant research, and of the included 
studies, the majority had small sample sizes (n < 5). A pos-
sible explanation for the limited number of relevant stud-
ies is the lack of systematic monitoring of elite/world-class 
athletes and/or restrictions on publishing unique data from 
such individuals. It is understandable that athletes may wish 
minimal distractions during their sporting careers, and that 
national federations likely want to maintain secrecy to gain 
a competitive advantage in the short-term perspective. How-
ever, we believe that systematic monitoring and publishing 
of long-term athletic data would benefit the sporting com-
munity at large, by contributing to the body of literature 
regarding elite-level training and athletic development.
The majority of the included research in this scoping 
review were case studies, which are considered the weakest 
form of scientific evidence and limit the possibility for gen-
eralization of the findings. Still, the case studies provide rich 
Table 2  (continued)
References
Participants 
Nation and sport 
n (sex)
Age (y)
Time 
period (y)
Training characteristics 
TV development
TID development
Performance-determining factors 
VO2max 
Submaximal responses
Maximal performance indicators
 [38]
British MD runner;
Tier 5;
(♂ = 1);
26–27 y
2
Age 26–27 y:
 ↔ TV = range 112–114 km·wk−1
↑LIT, ↓MIT, ↑HIT (absolute numbers 
not reported)
Age 26–27 y:
↑ VO2max 70.5–78.,5 mL·kg−1·min−1 
(+ 11%)
↑LT = 16–18 km·h−1 (+ 13%)
↑vVO2max = 10.4–23.1 km·h−1 (+ 13%)
Mixed population
 [45]
Australian
swimmers;
Tier 4;
(♀ = 16, ♂ = 24);
19–25 y (♂);
18–24 y (♀)
6
Age 19–25 y (♂) and 18–24 (♀) y:
↑LT = 1.2% annual increase (♀)
↑maximal speed = 0.6–1.0% annual 
increase (♂/♀)
 [41]
Spanish MD and LD runners;
Tier 4;
(♀ = 8, ♂ = 25);
23–26 y (♂);
26–29 y (♀)
3
Age 23–26 (♂) and 26–29 (♀) y:
 ↔ VO2max = ♂ ~ 76 mL·kg−1·min−1 and 
♀ ~ 70 mL·kg−1·min−1
Running performance (800-mara-
thon): + 1.8% (♂) and + 0.7% (♀)
AT anaerobic threshold, DE delta efficiency, HIT high-intensity training, LD long-distance, LIT low-intensity training, LT lactate threshold, MD 
middle-distance, MIT moderate-intensity training, PO power output, TID training intensity distribution, TT time trial, TV training volume, v 
velocity, VO2max maximal oxygen uptake, XC cross-country, y years, ↑ increase, ↓ decrease, ↔ stabilized, ♀ female, ♂ male
1603
Long-Term Development of Training Characteristics and Performance-Determining Factors
in-depth material on unique world-class level athletes such 
as Grete Waitz, Paula Radcliffe, Marit Bjørgen, Martin Four-
cade, Henrik, Filip, and Jacob Ingebrigtsen, Tim Maeyens, 
Sarah Louise Rung, and Mo Farah. While studies including 
more athletes would improve the ability to generalize find-
ings, another possibility would be merging data from several 
individual case studies of world-class athletes, to produce 
stronger evidence. However, such assimilation would require 
a common framework for the reporting of high-quality long-
term training data in elite athletes. Overall, implementation 
of such a policy would require collaboration between sports 
federations and research institutions, resulting in national 
and international projects with a concurrent focus on helping 
today’s athletes optimize their abilities, while the long-term 
data would enhance the performance of future generations of 
athletes. Furthermore, the finding that no information about 
training before a junior age was reported by any of the stud-
ies in this review demonstrates the importance of systemati-
cally monitoring athletes from a younger age.
Over the past decade, there has been a burgeoning aware-
ness and discussion regarding the lack of female-specific 
sports science research [46]. The present systematic scoping 
review highlights that female participants are considerably 
under-represented, and these findings align with other recent 
studies that emphasize the continued paucity of research on 
women in sport [47]. Out of the 17 studies included in this 
review, only 5% of the participants were from female-only 
studies. Similarly, Cowley et al. [47] reported that only 6% 
of randomly sampled sport and exercise studies, published 
between 2014 and 2020, were on women. Furthermore, 
the data in this review showed an under-representation of 
female participants and Paralympic athletes, a small num-
ber of unique sports, and a clear predominance of athletes 
from Western Europe. This restricts the generalizability of 
the existing scientific evidence and limits the possibility to 
inform sport practices and policies [48].
4.2  Training Characteristics
Although scientific evidence is lacking, long-term dedi-
cated training is crucial for reaching a world-class level in 
endurance sports. In our results, only seven of the studies 
included detailed information about the long-term progres-
sion in training; from a junior age or beginning of a sen-
ior age (18–20 years), until reaching elite/international or 
world-class level (i.e., 23–29 years). Interestingly, none of 
these studies included information about training before the 
age of 18 years, which could be a topic to investigate in 
future studies.
The studies demonstrate a non-linear increase in TV, 
varying from 30 to 500% over periods that range from 2 
to 17 years. Such large overall increases in TV required a 
considerable elevation in TV for specific years. However, 
more information is needed to understand the observed 
increases in TV, and if larger increases are associated with 
a more rapid performance and physiological development, 
or conversely, a greater risk of stagnation.
Three studies documented a plateau in TV occur-
ring close to peak performance, from ~ 650 to 900 h·yr−1 
depending on the type of endurance sport and individual 
needs. This is not unexpected for the long-term develop-
ment process, as a TV plateau is often observed around 
the same time an athlete reaches their peak performance 
level. However, we observed a decrease in TV, although 
performance level was maintained in the final years of 
a world-class female cross-country skier [30]. The find-
ings of a gradual TV increase prior to reaching a plateau 
support the guidelines provided by sporting bodies, but 
additional research on how training progression can be 
further optimized is required.
The effectiveness of utilizing TID concepts to maxi-
mize endurance adaptations and performance is a “hot 
topic” in the scientific literature [19, 20, 49]. However, 
little research has investigated the long-term development 
of TID in elite/international or world-class endurance 
athletes. In this scoping review, six case studies detailed 
athletic TID development, with all studies reporting an 
increased LIT volume. Two of the studies showed a stable 
portion of MIT and HIT over time [33, 34]; one study 
observed a change towards a higher volume for both MIT 
and HIT [37], while another study showed a small rela-
tive increase in MIT and a corresponding decrease in HIT 
[30]. The remaining two studies described a reduction in 
MIT and increased HIT [29, 38]. It is therefore difficult to 
draw any conclusions from this summary. In addition, six 
studies used different methodologies to determine TID, 
included athletes from different sports, and detailed dif-
ferent timespans. For example, one study compared only 
2 years of training [38], while another study described 
training changes over 12 years [30]. In addition, the differ-
ent methodology for logging intensity zones [21] and the 
complexity of the long-term development process, make it 
challenging to form generalizations about TID. However, 
increased LIT was associated with progression in the train-
ing load for all studies, and as such, this factor appears 
to be a critical cornerstone of any successful endurance 
training program. Accordingly, the proportion or volume 
of MIT and HIT is a crux of the training debate that has 
been previously described [20]. Still, an optimal endur-
ance training program should provide the necessary total 
TV, whilst balancing the appropriate proportion of MIT 
and HIT for each individual athlete. The current scientific 
understanding of how TID should be divided over a long 
duration is limited and more information regarding the 
long-term development of TID during different stages of 
an athlete’s career is needed.
1604
 
H. C. Staff et al.
4.3  Performance‑Determining Factors
The description of a world-class athlete implies a positive 
performance development across multiple years, and seven 
of the included studies also reported positive developments 
of performance and/or maximal performance indicators 
[29, 35, 38, 40, 44, 45, 50]. However, a compilation of the 
results is challenging because of testing in different periods 
of the season, and the fact that these performance determi-
nants appear particularly sensitive to seasonal variations in 
training.
While high VO2max values have been measured in world-
class athletes for most endurance sports [51], less data are 
available on the long-term development of VO2max. In this 
scoping review, VO2max was reported in ten studies [29, 30, 
35, 38–44], and suggests a considerable individual varia-
tion in the development of VO2max of elite athletes during 
their athletic careers. These cumulative data indicate that for 
some athletes, VO2max may develop and become optimized 
in the early stages of their career, while other performance-
determining factors then drive subsequent improvements. 
In contrast, other athletes were able to further develop their 
VO2max at later stages in their careers. The causative rea-
son behind this divergent response may be due to training 
pattern changes that stress complementary VO2max-limiting 
factors during this period. However, this theory should be 
considered speculative and additional research is required 
to further investigate this concept. For example, changes in 
body mass or body composition could change the relative 
VO2max values.
While VO2max showed different development patterns in 
world-class athletes, performance-determining factors that 
were based on submaximal responses demonstrated consid-
erably more consistent developments, both with and without 
improvements in VO2max [29, 30, 35, 38, 40, 44, 50]. This 
result provides further support for the concept that endur-
ance performance improvements after the age of 18–20 years 
are primarily related to other factors than  VO2max, such as 
improved fractional utilization of VO2max and work econ-
omy/efficiency. This is exemplified in the studies of Paula 
Radcliff [35, 44] who already reached a high value of VO2max 
at the age of 18 years, while improvements in running econ-
omy and running performance continued to develop gradu-
ally over years.
4.4  Existing Knowledge Gaps
The low number of peer-reviewed articles that have pre-
sented data on the long-term development of athletes reach-
ing elite/international or world-class level, in combination 
with varying data quality and lack of important details, high-
lights the urgent need for more long-term studies to support 
evidence-based talent development in sport. As more than 
half of the included studies were case studies, and most of 
the data were collected retrospectively, prospective studies 
would be of particularly interest. The low number of studies 
in women also confirms their current under-representation 
in the scientific literature.
Although participation and professionalization in Para-
lympic sports are increasing, it is problematic that only one 
study with Paralympic athletes met the inclusion criteria in 
this systematic scoping review. The same applies for the 
small number of unique sports and the clear predominance 
of athletes from Western Europe, which highlights the need 
for further examinations of different sports, cultures, and 
ethnicities.
Finally, only four of the 17 studies reported concurrent 
data of training and performance-determining variables, lim-
iting the ability to identify potential associations between 
relevant variables of interest. In this context, future long-
term development studies should follow a common frame-
work, enabling the possibility to compare data across studies 
and the performance of future meta-analyses.
4.5  Methodological Guidelines for Future Research
The findings in this scoping review demonstrate that a com-
mon methodological framework to permit a detailed com-
parison between different studies is needed. Based on the 
findings in this study, we have devised the following guide-
lines regarding the type of information to include, and the 
standardization required, for all future studies that wish to 
report on long-term training development and performance-
determining factors in endurance sports (see Table 3). We 
hope that these guidelines can assist future studies to stand-
ardize the collection and presentation of training data, and 
we encourage other researchers to further develop and vali-
date this proposed framework.
5  Conclusions
The current review found that only a handful of previous 
studies have reported the long-term development of train-
ing characteristics and performance-determining factors in 
male and female endurance athletes reaching an elite/inter-
national or world-class level. There are particularly limited 
data on women, and athletes aged younger than 18 years. No 
evidence was found for possible sex differences. Although 
17 studies were included in this systematic scoping review, 
athletes from only a small number of countries and sports 
are described. Accordingly, current long-term talent devel-
opment practices in endurance sports have insufficient sci-
entific evidence.
The training characteristics described a non-linear year-
to-year increase in TV for most world-class endurance 
1605
Long-Term Development of Training Characteristics and Performance-Determining Factors
athletes, subsequently resulting in a plateau. However, the 
progression of TID showed individual patterns. While it is 
likely that a gradual progression in TV, with most of the 
increase stemming from more LIT, is required to reach a 
high level in endurance sports, no pattern was identified for 
the optimal development of MIT and HIT. The few stud-
ies reporting the development of performance-determining 
variables indicated a consistent improvement in maximal 
performance tests and submaximal performance indicators 
for most athletes. Conversely, VO2max development was 
observed to be inconsistent.
Overall, there is an urgent need for additional research 
that describes the long-term development of world-class 
athletes. Specifically, the implementation of systematic 
monitoring of athletes from a young age, employing high-
precision reproducible measurements of training and per-
formance-determining variables would enable prospective 
and high-quality retrospective study designs of considerable 
Table 3  Methodological guidelines for future research focusing on the long-term development of endurance athletes
AT anaerobic threshold, CP critical power, HIT high-intensity training, HR heart rate, LIT low-intensity training, LT lactate threshold, max maxi-
mum, MIT moderate-intensity training, PO power output, TID training intensity distribution, TV training volume, VE minute ventilation, VO 
oxygen uptake, VO2max maximal oxygen uptake, VT ventilatory threshold
Topics
Information and standardization
Time frame
Years without using training diary/logs: qualitatively describe the training/activity background until the start of 
systematically logging
Years with the use of training diary/logs: record daily/weekly training from the year they started logging training 
until the end of their career
Performance development
Logging of all competitions (type, duration)
Logging of results from major events (national and international championship and World Cup as junior and senior)
Training characteristics
Training volume
Training frequency
Training form (endurance, strength, and speed)
Exercise mode (modality)
TID 3-zone model (LIT, MIT, HIT)
Session design (continuous or interval and choice of terrain)
Mobility
Qualitative descriptions of methodology used to record TID, TV, and pauses between intermitted training methods 
(interval training)
Recovery parameters
Rest days
Sleeping time and quality
Nutrition
Qualitative registrations of other loading factors:
 Work/school or other cognitive stress
 Traveling (including time-zone changes)
 Environmental (heat, cold, humidity, altitude)
 Traumatic challenging emotional events/situations
Health parameters
Illness and injury days
Menstrual or hormonal contraceptive cycle
Periodization phases
Annual
General preparation
Specific preparation
Competition period
Altitude
Tapering
Anthropometric and physi-
ological parameters
Body height (cm)
Body mass (kg)
Lean body mass (kg)
Total body fat (%)
Systematic measurements of
 VO2max (L·min−1, mL·kg−1·min−1)
   speed@VO2max,  HR@VO2max,  VE@VO2max
 Performance indices (peak/average speed and power)
  Peak/max HR
 Threshold concepts (LT, VT, CP)
   speed@AT,  watt@AT,  HR@AT,  lactat@AT,  VO@AT,  PO@AT
 Work economy or efficiency
 Relevant speed and strength measurements if possible
1606
 
H. C. Staff et al.
scientific and practical value. In addition, the use of a com-
mon methodological framework is also necessary to permit 
a detailed comparison between different studies and allow 
for future meta-analyses.
Acknowledgements The authors thank Tromsø Research Foundation 
and the FENDURA project team for their enthusiasm and contribution 
in this study.
Declarations 
Funding This study was funded by the Tromsø Research Foundation 
(Project-ID: 19_FENDURA_BW) and UiT The Arctic University of 
Norway. Open access funding provided by UiT The Arctic University 
of Norway (incl University Hospital of North Norway).
Conflicts of Interest/Competing Interests Hanne Staff, Guro Strøm 
Solli, John O. Osborne, and Øyvind Sandbakk have no conflicts of 
interest that are directly relevant to the content of this article.
Ethics Approval Not applicable.
Consent to Participate Not applicable.
Consent for Publication Not applicable.
Availability of Data and Material Not applicable.
Code Availability Not applicable.
Authors’ Contributions HS, GS, JOO, and ØS designed the study; JOO 
performed the database search; HS, GS, and JOO performed the screen-
ing process; HS, GS, JOO, and ØS contributed to interpretation of the 
results; HS, GS, and ØS wrote the draft manuscript; and HS, GS, JOO, 
and ØS contributed to the final manuscript.
Open Access This article is licensed under a Creative Commons Attri-
bution 4.0 International License, which permits use, sharing, adapta-
tion, distribution and reproduction in any medium or format, as long 
as you give appropriate credit to the original author(s) and the source, 
provide a link to the Creative Commons licence, and indicate if changes 
were made. The images or other third party material in this article are 
included in the article's Creative Commons licence, unless indicated 
otherwise in a credit line to the material. If material is not included in 
the article's Creative Commons licence and your intended use is not 
permitted by statutory regulation or exceeds the permitted use, you will 
need to obtain permission directly from the copyright holder. To view a 
copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.
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Long-Term Development of Training Characteristics and Performance-Determining Factors in Elite/International and World-Class Endurance Athletes: A Scoping Review.
Staff, Hanne C,Solli, Guro Strøm,Osborne, John O,Sandbakk, Øyvind