Next Article in Journal
Morphometrics of the Blue Crab Callinectes sapidus Rathbun, 1896 in a Northern Adriatic Saline Marsh Under Environmental Stress
Previous Article in Journal
Study of Online Testing of Void Defects in AM Components with Grating Laser Ultrasonic Spectrum Method
Previous Article in Special Issue
The Effects of Six Months of Exercise on Single- and Dual-Task Posture, Gait, and Functional Mobility Relative to Usual Care Alone Among People Living with Dementia: The ENABLED Pilot Randomized Controlled Trial
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Born to Win? The Hidden Bias of Birthdates in Spanish Orienteering Talent Selection

by
Javier Montiel-Bonmatí
1,
Javier Marco-Siles
1 and
Alberto Ferriz-Valero
1,2,*
1
Department of General and Specific Didactics, Faculty of Education, University of Alicante, 03690 Alicante, Spain
2
Physical Education and Knowledge Advancement (PEAK) Research Group, 03690 Alicante, Spain
*
Author to whom correspondence should be addressed.
Appl. Sci. 2025, 15(14), 7993; https://doi.org/10.3390/app15147993
Submission received: 20 June 2025 / Revised: 5 July 2025 / Accepted: 15 July 2025 / Published: 17 July 2025
(This article belongs to the Special Issue Advances in Sports Science and Movement Analysis)

Abstract

The Relative Age Effect (RAE) refers to the advantage that relatively older athletes within the same age group may have in sports. While this phenomenon has been widely documented in numerous disciplines, its presence in orienteering remains largely unexplored. This study aimed to analyse the existence of RAE among Spanish orienteers selected for international competitions organised by the International Orienteering Federation (IOF) between 1987 and 2023. A total of 384 participations (225 male, 159 female) were examined across the European Youth Orienteering Championships (EYOC), Junior World Orienteering Championships (JWOC), and the European and World Orienteering Championships (EOC + WOC). The distribution of birth dates by quartiles and semesters was compared using chi-square tests, Cramér’s V, Z-tests, and odds ratios with 95% confidence intervals. The results revealed a significant RAE in male athletes, particularly in JWOC, where those born in the first quartile were up to 3.77 times more likely to be selected than those in the third quartile. In contrast, no significant associations were found in female athletes, which may reflect structural or developmental differences related to sex. These gender-based disparities highlight the importance of integrating sex-specific considerations into selection policies. Overall, the findings suggest a selection bias favouring relatively older males, which may hinder the development of late-born talent. Therefore, it is recommended that selection criteria be reassessed to ensure fairer and more inclusive talent identification and development in youth and elite orienteering.

1. Introduction

Orienteering is an endurance sport that combines physical and cognitive demands, challenging participants to navigate through unfamiliar terrain—whether in natural, urban, or park settings—using only a map and a compass [1]. This discipline consists of completing the course by visiting a series of control points in a predetermined order, without following a predefined route. In addition to requiring a high level of physical fitness, orienteering depends upon decision-making and terrain analysis [2], making it a sport that stimulates both the body and the mind.
Competition plays a central role in this sport, not only as a competitive framework but also as a tool for identifying and promoting talent [3]. Selection processes in orienteering are predominantly based on results from regional and national events, where athletes are evaluated for their physical resistance and navigational skills [3]. Furthermore, coaches play a key role in managing training opportunities for their athletes, frequently giving priority to those who show outstanding performance from the earliest phases of their development [1]. Each season, the competitive season includes a range of regional and national events, offering athletes opportunities to score points and improve their skills through deliberate practice [4]. The results obtained in these competitions are frequently decisive for accessing higher competitive levels, as strong performance paves the way toward greater opportunities [5], such as representing Spain in international orienteering events.
In many sports, including international orienteering competitions for youth, athletes are grouped by their chronological age in order to guarantee fairness [6]. Theoretically, this system allows the most talented within each age group to emerge and access further developmental opportunities under equal conditions. However, numerous studies have demonstrated a phenomenon known as the Relative Age Effect (RAE), which involves an overrepresentation of athletes born in the first months of the selection year [7].
This age-based inequality is often explained by the maturity-selection hypothesis, positing that chronologically older children within their cohorts tend to be more physically developed, possessing anthropometric and physiological traits that enhance their performance [7,8]. In this context, grouping by year of birth introduces substantial differences in physical and psychological maturity, as an athlete born in January may be nearly twelve months more developed than another born in December of the same year. These differences are especially pronounced between the ages of 10 and 19, coinciding with the period of biological maturation. They tend to diminish or even disappear in adulthood [8].
This initial overrepresentation of relatively older athletes may contribute to the premature exclusion of potentially talented individuals born later in the year, thereby reducing the pool of talent at higher levels [9,10]. In addition to physical advantages, relatively older athletes may also benefit from greater competitive experience and training opportunities, which may influence their cognitive and tactical skills in orienteering [6,7,11].
In orienteering, competitive groups are formed within a two-year range with a January 1st cut-off date. This structure can further accentuate the RAE [12]. Nevertheless, the RAE’s impact is not uniform across all sports, as its magnitude depends on mediating factors such as physical demands, popularity, and competition structure [7]. The RAE is more pronounced in male athletes and in sports with greater popularity and physical demands [7,11], while in orienteering, the existing evidence is limited and inconclusive.
Beyond its immediate performance implications, the competitive structure and selection processes may play a key role in the long-term development of orienteers. Participation and strong performance in international events not only facilitate progression toward higher competition levels but also foster confidence and continued motivation [13]. Being selected to represent one’s country or delivering a strong performance at these competitions serves as both an indicator of talent and a motivational stimulus for the athlete’s future [14]. In this context, these competitive opportunities may aid talent identification while offering valuable developmental experience. Nevertheless, the RAE’s influence on talent identification [15] raises questions about fairness in the processes used to identify and promote talent in orienteering, as it can inadvertently disadvantage some athletes with potential.
Despite extensive evidence of the RAE across various sports [16], research into its manifestation in orienteering remains scarce. This discipline, combining physical endurance with high cognitive demands such as decision-making under pressure and map reading, presents a unique scenario for the RAE. The interaction between these diverse factors may modulate the RAE differently compared to other sports, underscoring the need for further investigation within this specific context.
Few studies have evaluated the influence of the RAE in orienteering [2,15,17,18]. Jakobsson et al. [2] observed a medium RAE, primarily affecting younger athletes, though without a direct correlation between birth quarter and performance. Romann et al. [18] found an overrepresentation of athletes born in the second half of the year in a small sample (n = 7) of elite Swiss orienteers, which may limit the generalisability of their results. Agricola et al. [17], however, found no significant RAE in elite orienteers from the Czech Republic. More recently, Ferriz-Valero et al. [19] reported significant differences in performance in favour of relatively older orienteers within the same age group in the lower categories. Collectively, this limited body of research suggests that while the RAE may manifest in orienteering—especially during the initial phases of athlete development—its magnitude and significance vary depending on context and methodology.
For these reasons, the main objective of this study is to analyse the presence and magnitude of the RAE in both young and elite, and male and female orienteers selected to represent Spain in international orienteering competitions. These international orienteering competitions serve as a criterion or performance variable that denotes the highest level of sport-specific talent, classified by Gagné [20] as Level 5 or Extreme—a level which occurs in only 1 in 100,000 cases—reflecting the exceptionally restrictive criteria for identifying talent in orienteering.
Based on previous findings regarding the RAE in sport, the following hypotheses were proposed: (1) In the youth sample, relatively older male orienteers (i.e., born earlier in the selection year) are expected to exhibit higher rates of selection compared to their younger peers; (2) In the youth sample, relatively older female orienteers are also expected to show a greater frequency of selection compared to their younger peers; (3) In the senior male sample, a greater proportion of participants in international events is hypothesized to be observed among orienteers born in the early months of the year; (4) In the senior female sample, a higher representation in international events is also hypothesized among those born earlier in the year.

2. Materials and Methods

An observational, retrospective cross-sectional study was conducted. This study analysed the distribution of birth quartiles (Q1–Q4) and semesters (S1–S2) among athletes selected to represent Spain in international orienteering competitions between 1987 and 2023. The following sections describe the characteristics of the sample, the procedures for data collection and organisation, and the statistical methods used for analysis.

2.1. Participants

The sample comprised all Spanish orienteering athletes holding a national licence who were selected to represent Spain in international competitions organised by the International Orienteering Federation (IOF) between 1987 and 2023 (n = 252; 103 women and 149 men). Records lacking birthdate information (11 women and 19 men) were excluded. The events considered were the European Youth Orienteering Championships (EYOC), the Junior World Orienteering Championships (JWOC), the European Orienteering Championships (EOC), and the World Orienteering Championships (WOC).
To avoid overrepresentation of individual athletes due to repeated selections, only one participation per athlete per event type was considered. This yielded a total of 384 participation records (159 for the female group and 225 for the male group). This approach ensured the independence of observations. It also prevented repeated performances from disproportionately influencing the birthdate distribution, thereby enhancing the robustness of the statistical analysis.
It is important to note that this approach focused on identifying the RAE’s influence on selection into different international competition tiers (EYOC, JWOC, EOC + WOC) by considering one selection per athlete per event type. While this ensured the independence of observations and robustness of the statistical analysis regarding birthdate distribution within each competition type, it did not account for the frequency of selection across multiple competition types or across different years for the same event. Therefore, it does not distinguish between athletes experiencing ‘continuous selection’ versus ‘one-time selection’, which could offer additional insights into long-term athlete development. Future research could explore these aspects to provide a more comprehensive understanding of selection patterns.
The data were further segmented by type of event and competitive group (female or male), as shown in Table 1. As can be observed, WOC and EOC participations are presented jointly since they alternate biennially and never occur in the same year. Grouping them increased the sample size and improved statistical power.
Data were obtained from the Lithuanian database portal DB Sportas (n.d. Lithuanian Orienteering Federation, Vilnius, Lithuania), which provides historical records of participation in IOF events from their inaugural editions: WOC since 1966; JWOC since 1990; EYOC since 1999; and EOC since 2000. In the case of Spain, participation records are available for WOC from 1987 onwards, while EYOC, JWOC, and EOC data are available from their respective first editions. To ensure data accuracy, records were cross-checked with those published by the Spanish Orienteering Federation (FEDO) and the IOF.
In the EYOC, the IOF defines two biennial age-group categories for athletes aged 16 to 18: W/M-16 and W/M-18 (W = Women; M = Men). In the JWOC, athletes aged 19–20 compete in a single W/M-20 category. At the senior level (EOC and WOC), there are only two absolute categories: one for women and one for men.
To compare the selected athletes with the total population of licensed orienteers in Spain, data from previous research [1] were used (Table 2). Specifically, athletes selected for EYOC were compared to the F/M-16 and F/M-18 groups; those selected for JWOC were compared to F/M-20; and those selected for WOC and EOC were compared to the elite category (F/M-E).
Furthermore, for the EYOC event, it is important to acknowledge that the data combine W/M-16 and W/M-18 age groups as defined by the IOF’s biennial categorization system. While this grouping was necessary to achieve a sufficient sample size for analysis given the historical data, it introduces a broader chronological age range within the youth sample. The combination of these age groups might potentially influence the manifestation of age-related differences in selection, a factor that should be considered when interpreting the EYOC results.

2.2. Procedure

In order to compare the distribution of birth quartiles and semesters among athletes selected by the Spanish Orienteering Federation (FEDO) with the distribution within the broader population of licensed athletes—stratified by age group—data were analysed at a single point in time, without longitudinal follow-up. This ensured that there was no intervention in the natural setting of the assessed groups.
Anonymous data were collected regarding athletes’ sex, date of birth, and competitive groups through a formal collaboration agreement signed with FEDO, who were duly informed about the study’s objectives and authorised the publication of the data. The study protocol was approved by the Ethics Committee of the University of Alicante (Reference: UA-2024-06-17).
At both national and international levels, age-group categorisation in orienteering uses January 1 as the cut-off date. Therefore, athletes’ birthdates were considered solely by month—regardless of year—and categorised into four relative age quartiles (Q) and, simultaneously, into two birth semesters (S). The quartiles were defined as follows: Q1 (January–March), Q2 (April–June), Q3 (July–September), and Q4 (October–December). The semesters were defined as S1 (January–June) and S2 (July–December).

2.3. Statistical Analysis

Statistical analysis was performed using IBM SPSS software (version 28; IBM Corp., Armonk, NY, USA) and Microsoft Excel for Mac (version 16.83; Microsoft Corp., Redmond, WA, USA). To assess differences in the distribution of birth quartiles and semesters in the international events analysed, the chi-square (χ2) goodness-of-fit test was applied with a significance level of 5%. Observed distributions were compared to the actual distributions of licensed athletes in Spain by sex and age group, following the recommendations of Delorme et al. [21].
To quantify the magnitude of the association in the chi-square test, Cramér’s V was calculated, in line with the guidelines provided by Wattie et al. [22] and in agreement with previous research [2]. Cramér’s V is one of the most widely used effect size indicators when the chi-square statistic is significant (Sapra & Saluja, 2021 [23]). It is calculated using the following formula (Equation (1)):
Equation (1). Cramér’s V
C r a m e r s   V = χ 2 N   ( k 1 )
where χ2 is the chi-square value, N is the total sample size, and k is the lesser of the number of rows or columns in the contingency table.
Additionally, a Z-test was conducted to compare proportions between birth quartiles and semesters, using a significance threshold of p < 0.05.
Finally, odds ratios (OR) and their corresponding 95% confidence intervals (95% CI) were calculated to evaluate the likelihood of selection based on relative age quartiles and semesters, disaggregated by sample and sex. This was carried out according to the method proposed by Cobley et al. [7]. The OR interpretation followed these criteria: if the 95% CI includes the value 1, the association is considered non-significant; if the CI is greater than 1, a positive association is suggested; and if below 1, a negative association is inferred [24]. The strength of association was interpreted following Olivier and Bell [25], where an OR ≈ 1.22 indicates a small effect, ≈1.86 a medium effect, and ≈3.00 a large effect.

3. Results

The results presented in Table 3 indicate a statistically significant association between birth quartile and selection to represent Spain in international competitions, exclusively within the male JWOC category (χ2 (3) = 8.13; p = 0.043). Furthermore, this group exhibited the largest effect size among all competitions and competitive groups studied (V = 0.34). For the remaining events and categories, although medium effect sizes were observed (V ranging from 0.20 to 0.23), the association between birth quartile and selection for these championships did not reach statistical significance (p > 0.05). The smallest effect was observed in the female EYOC group (V = 0.11, small-to-medium association).
In contrast to the JWOC male group, no statistically significant RAE was observed in the female sample when analysing birth quartile distribution across all competitions (e.g., EYOC: χ2(3) = 0.86, p = 0.834; JWOC: χ2(3) = 2.01, p = 0.570; WOC + EOC: χ2(3) = 2.17, p = 0.537). Similarly, no significant effect was found for semester distribution (e.g., EYOC: χ2(1) = 0.06, p = 0.867; JWOC: χ2(1) = 0.18, p = 0.822; WOC + EOC: χ2(1) = 1.27, p = 0.259).
While no statistical significance was reached, a qualitative examination of the female distribution revealed a less pronounced pattern of RAE compared to males, with effect sizes (Cramér’s V) generally lower across all female categories.
Although there was an apparent overrepresentation of athletes born in the first half of the year (S1) across all events—especially among male athletes—chi-square analysis by semester (Table 4) revealed no statistically significant associations (p > 0.05). Effect sizes (Cramér’s V), although following a similar pattern to that observed for quartiles, were slightly lower.
As shown in Figure 1, male athletes born in Q1 were most represented across all international competitions. In the EYOC, athletes born in Q1 significantly outnumbered those in Q3 (Z = 2.702; p = 0.007) and Q4 (Z = 2.335; p = 0.020). In JWOC, statistically significant differences were found between Q1 and all other quartiles—Q1 vs. Q2 (Z = 2.152; p = 0.031); Q1 vs. Q3 (Z = 3.358; p = 0.001); Q1 vs. Q4 (Z = 2.740; p = 0.006). Similarly, in senior-level events (WOC + EOC), athletes born in Q1 differed significantly from those born in Q3 (Z = 3.193; p = 0.001) and Q4 (Z = 2.314; p = 0.021).
In the female sample (Figure 2), the participation frequency in EYOC followed the typical RAE pattern, with a decreasing distribution from Q1 to Q4 (Q1 > Q2 > Q3 > Q4), although no statistically significant differences were found between quartiles. In other competitions, the only significant difference was between Q2 and Q3 (Z = 2.159; p = 0.031) in the senior-level events (WOC + EOC).
The semester-based analysis (Figure 3) reinforces the quartile distribution results from Figure 1 and Figure 2, clearly showing that the differences between S1 and S2 are more pronounced in male categories (right side of the chart) than in female ones (left side), regardless of the event. This trend is statistically supported by the Z-test, which reveals significant differences between S1 and S2-born male athletes in EYOC (Z = 3.148; p = 0.002), JWOC (Z = 3.525; p < 0.001), and WOC + EOC (Z = 3.684; p < 0.001).
Odds ratio (OR) results, along with 95% confidence intervals, are shown in Table 5. Statistically significant differences (marked with an asterisk *) align with those identified via Z-tests. Among females, the relative likelihood of being selected for senior-level international competitions (WOC + EOC) was nearly three times higher for athletes born in Q2 compared to those born in Q3 (OR = 2.95; 95% CI = 1.08–8.05). Among males, the relative likelihood of being selected to represent Spain in any international competition was between two and four times higher for athletes born in Q1 or S1 compared to those born in later quartiles or the second semester (S2).
In OR analyses comparing quartiles and semesters, it is common practice to use Q4 (relatively youngest individuals) and S2 as reference groups [7]. Within this framework, Figure 4 and Figure 5 present ORs and 95% CIs for Q1 vs. Q4 and S1 vs. S2, respectively, across all international competitions and competitive groups. Consistent with earlier findings, no significant associations were observed between birth timing and national team selection in female groups, regardless of whether Q1/Q4 or S1/S2 comparisons were used. In contrast, among male athletes, both Q1/Q4 and S1/S2 comparisons revealed statistically significant associations (OR > 1) across all evaluated competitions.
It is important to note that the EYOC data, as per the IOF’s categorization, combined W/M-16 and W/M-18 age groups. This introduces a broader chronological age range within the ‘youth’ category that should be carefully considered when interpreting these specific results, as it may influence the observed RAE patterns.

4. Discussion

The objective of this study was to evaluate the Relative Age Effect (RAE) in elite young male and female orienteers selected to represent Spain in international competitions organised by the IOF.
However, prior to these international events, the national selection process exerts significant pressure on athletes and selectors, since the number of spots per sex and category is strictly limited. This circumstance compels orienteers to optimise their performance in order to secure their participation. In this context, the results revealed the presence of the RAE among male orienteers in the cadet, youth, junior, and senior categories. These results are consistent with previous findings in other physically demanding individual sports [16,26,27,28,29] which have reported similar RAE patterns, particularly among male athletes.
Although the chi-square analyses did not show significant deviations in the frequency distribution of orienteers from the expected distribution—except for the JWOC—the Z-test for proportions and the odds ratio (OR) analyses (Table 5) revealed that male orienteers born in the first quartile (Q1) showed a two- to four-fold higher representation in international events compared to those born in the third and/or fourth quartile (Q3 and Q4), with statistically significant differences (Figure 1 and Figure 4). This trend was replicated in the distribution by birth semester (Table 5), as significant differences were found in all events for the male sample. Specifically, the probability of selection for an orienteer born in the first semester (S1) was nearly twice as high (OR ranging from 1.61 to 2.19) as for one born in the second semester (S2) (Figure 3 and Figure 5). These results are consistent with previous studies in individual endurance sports, which have also demonstrated a predominance of athletes born in the earlier months of the year [9,26,27].
The findings of this study suggest that, regardless of other possible influencing factors (e.g., social or environmental), the selection processes for major international orienteering events are biased in favour of relatively older athletes. As a consequence, numerous young orienteers may face reduced opportunities to accumulate critical sporting experiences and deliberate practice hours [4], potentially undermining their long-term athletic development and limiting their future opportunities within the sport [30].
Accordingly, the meta-analysis by Cobley et al. [7] indicated that the risk of the RAE is intensified during mid to late adolescence (ages 14–18), particularly at national-level competitive representation. In the same vein, the findings by Till et al. [31], which examined the structured development pathway in Rugby League, confirmed that such risk increases as selection processes become more stringent and performance levels rise. Both studies highlight that talent evaluation mechanisms, performance appraisal, and player selection practices play a critical role in perpetuating inequalities associated with the RAE. This phenomenon may help explain the results of the present study, in which a marked RAE was observed among male athletes in the cadet (15–16 years), youth (17–18 years), junior (19–20 years), and senior categories who represented Spain in international competitions. Such overrepresentation may reinforce long-term developmental advantages for early-born athletes by increasing their access to structured training, higher-quality coaching, and performance feedback loops—all of which are key to progression through talent pathways [32]. Furthermore, early identification and selection may confer a long-term advantage by increasing the likelihood of future selection and, potentially, long-term retention within the athlete development system [33].
Several studies have shown that the influence of the RAE tends to diminish progressively following maturation [7,11,28,34], even disappearing entirely in older age groups [26,35,36]. However, a less pronounced RAE was observed in the EYOC event among orienteers aged 15–18 years, which contrasts with the majority of existing literature. A plausible explanation for this discrepancy is the limitation of the dataset, which did not allow for discrimination between the W/M-16 (15 and 16 years) and W/M-18 (17 and 18 years) subcategories, thereby potentially masking differences due to maturation. This internal age heterogeneity may have diluted the observable RAE, as combining two distinct age subgroups introduces variability in biological maturity, physical development, and accumulated experience. For example, an athlete close to the age limit of M-18 may enjoy considerable physical and tactical advantages over a newly promoted M-16 athlete, which complicates the detection of consistent age-related patterns. Within this context, the age of 16 could represent a critical threshold: while female orienteers may have already completed their somatic maturation, their male counterparts may still be undergoing development, which could affect the manifestation of the RAE [37]. Future research should consider analysing these age groups separately to better capture age-specific manifestations of the RAE in youth orienteering.
Research on the RAE and sex differences among athletes has produced contradictory results. While some studies report no observable RAE among females competing in individual sports [27,30,38], others do find evidence of the RAE, although its impact is significantly smaller than that observed in males [1,2,7,15,17,18,22,39,40]. For example, Romann et al. [18] reported a slight RAE among both female athletes (OR = 1.35; 95% CI: 1.24–1.47) and male athletes (OR = 1.84; 95% CI: 1.74–1.95) within a talent development programme. However, at the national selection level, the RAE was similar among women (OR = 1.30; 95% CI: 1.08–1.57) but significantly more pronounced among men (OR = 2.40; 95% CI: 1.42–1.97). Overall, the RAE appears to be more pronounced in men than in women, with a stronger effect at higher levels of selection being observed almost exclusively among male athletes. Similarly, Cobley et al. [7] found that the OR comparing Q1 and Q4 was higher in males (OR = 1.65; 95% CI: 1.54–1.77) than in females (OR = 1.21; 95% CI: 1.10–1.33). Moreover, in sports such as artistic gymnastics, an inverse RAE has even been reported [30,38,40]. In the present study, although a highly significant RAE was detected among male athletes, the quartile and semester distribution of birth dates among female orienteers did not reveal a significant bias, thereby not supporting the second and fourth initial hypotheses.
The absence of a significant RAE among female athletes in our study may be partially explained by their earlier physical and psychological maturation, typically achieved by around age 16 [37]. This timing coincides with the start of the selection process for international events (EYOC), potentially narrowing maturational differences within categories [34]. Moreover, the greater proportional representation of female athletes in orienteering (41% at youth level, 37% at senior level in our sample) may indicate a less competitive or more inclusive environment, which could reduce selection pressure and attenuate the effect of birthdate. These findings partially align with previous studies in similar sports [26,35], yet highlight the need to explore how sex-based participation dynamics shape.
Conversely, Wattie et al. [22] proposed that relatively older female athletes may face an increased risk of sport dropout, attributed to early maturation, which has been associated with negative psychosocial effects [41]. In addition, several authors argue that traditional gender stereotypes may reduce the motivation of early-maturing girls to engage in sport, as they may feel pressured to conform to pre-established gender roles [42]. Finally, it has been suggested that participation depth, selection intensity, and competition level may contribute to explaining the disparity between males and females in the manifestation of the RAE [43,44,45].
An alternative hypothesis applicable to the female sample is the so-called “underdog hypothesis” [46], which posits that the challenges faced by relatively younger athletes—such as non-selection or reduced attention—may, over time, foster psychological resilience, motivation, and stronger coping strategies [22,46]. Although our study did not reveal a reversed RAE pattern, the lack of significant effects in female categories could suggest that these athletes are less influenced by initial disadvantages, possibly due to adaptive mechanisms of this kind [22,46]. This perspective aligns with previous work highlighting that long-term success in sport may not solely depend on early advantage, but also on how athletes respond to early adversity [47].
In light of our findings, it is essential to consider the implementation of practical measures aimed at reducing the impact of the RAE in orienteering talent selection. Several strategies have been proposed in the literature [22]. One approach is to incorporate biological age assessment rather than relying solely on chronological age, thereby aligning selection processes more closely with athletes’ developmental status [8,38]. Another possibility is to apply birthdate-based corrective adjustments or RAE compensation systems, such as point weighting or quotas based on birth quarters, to balance representation [7,35]. A third option involves the use of multi-age or bio-banding groupings, which have been trialled successfully in other sports to equalize maturational differences [48]. A focus on long-term athlete development models that prioritize skill acquisition and holistic development over early competitive success could foster a more equitable and sustainable talent pool in orienteering [22]. Finally, increasing awareness among coaches and selectors about RAE-related biases through educational interventions may help mitigate unconscious favouritism toward relatively older athletes [22]. While no single solution is universally applicable, a combination of these approaches—tailored to the structure of orienteering—may contribute to more equitable talent identification and development systems.

5. Conclusions

This study confirms the existence of a Relative Age Effect (RAE) in Spanish orienteering, particularly among male athletes across all age categories, with a marked over-representation of those born in the first half of the year. In contrast, no significant RAE was observed in elite female athletes. These results provide novel evidence within an under-researched sport, suggesting that the RAE manifests differently depending on sex.
The findings have important implications for talent identification and selection, underscoring the need to reassess current practices to ensure greater equity. To move toward fairer and more inclusive talent identification systems, specific measures should be considered, such as adjusting for relative age (e.g., birth quarter or month weighting), adopting more flexible age group classifications, or diversifying selection criteria to include assessments beyond performance in chronological cohorts. Furthermore, these findings highlight the need for follow-up studies incorporating multivariate analyses that account for biological maturity, psychological variables, training history, etc. Cross-national comparisons could also offer insights into how different selection systems and cultural contexts influence the RAE in orienteering and other niche sports. Such investigations would strengthen the evidence base and guide the implementation of more equitable selection policies at both national and international levels.

Author Contributions

Conceptualization, J.M.-B. and A.F.-V.; methodology, J.M.-B. and A.F.-V.; software, J.M.-B.; validation, J.M.-B., A.F.-V. and J.M.-S.; formal analysis, J.M.-B. and A.F.-V.; investigation, J.M.-B.; resources, A.F.-V.; data curation, J.M.-B.; writing—original draft preparation, J.M.-B.; writing—review and editing, A.F.-V. and J.M.-S.; visualization, J.M.-B.; supervision, A.F.-V.; project administration, J.M.-B. and A.F.-V.; funding acquisition, A.F.-V. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the University of Alicante (protocol code UA-2024-06-17 and date of approval 17 June 2024). Anonymous data regarding athletes’ sex, date of birth, and competitive groups were collected through a formal collaboration agreement signed with FEDO, who were duly informed about the study’s objectives and authorised the publication of the data.

Informed Consent Statement

Informed consent was obtained from the Spanish Federation to process the data anonymously.

Data Availability Statement

The data regarding the birth dates of federated athletes were provided by the FEDO. These data are not publicly accessible. As such, there are legal restrictions on sharing this dataset, as imposed by the FEDO. Designated contact for data inquiries: secretaria.fedo@gmail.com.

Acknowledgments

Authors thank the collaboration of FEDO (Federación Española del Deporte de Orientación) from Spain. Finally, this work contributes to the development of Javier Montiel’s doctoral thesis.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

RAERelative Age
IOFInternational Orienteering Federation
Q1–Q4Quartiles 1 to 4
S1–S2Semesters 1 and 2
EYOCEuropean Youth Orienteering Championships
WOCWorld Orienteering Championships
EOCEuropean Orienteering Championships
CIConfidence Interval

References

  1. Montiel-Bonmatí, J.; Marco-Siles, J.; Ferriz-Valero, A. Prevalence of the Relative Age Effect in Spanish Orienteering: An Analysis by Sex and Competitive Level. Appl. Sci. 2025, 15, 4102. [Google Scholar] [CrossRef]
  2. Jakobsson, J.; Julin, A.L.; Persson, G.; Malm, C. Darwinian Selection Discriminates Young Athletes: The Relative Age Effect in Relation to Sporting Performance. Sports Med.—Open 2021, 7, 16. [Google Scholar] [CrossRef] [PubMed]
  3. Batista, M.M.; Paludo, A.C.; Gula, J.N.; Pauli, P.H.; Tartaruga, M.P. Physiological and Cognitive Demands of Orienteering: A Systematic Review. Sport Sci. Health 2020, 16, 591–600. [Google Scholar] [CrossRef]
  4. Anders Ericsson, K.; Towne, T.J. Expertise. WIRES Cogn. Sci. 2010, 1, 404–416. [Google Scholar] [CrossRef] [PubMed]
  5. Hébert-Losier, K.; Platt, S.; Hopkins, W.G. Sources of Variability in Performance Times at the World Orienteering Championships. Med. Sci. Sports Exerc. 2015, 47, 1523–1530. [Google Scholar] [CrossRef] [PubMed]
  6. Helsen, W.F.; Van Winckel, J.; Williams, A.M. The Relative Age Effect in Youth Soccer across Europe. J. Sports Sci. 2005, 23, 629–636. [Google Scholar] [CrossRef] [PubMed]
  7. Cobley, S.; Baker, J.; Wattie, N.; McKenna, J. Annual Age-Grouping and Athlete Development: A Meta-Analytical Review of Relative Age Effects in Sport. Sports Med. 2009, 39, 235–256. [Google Scholar] [CrossRef] [PubMed]
  8. Romann, M.; Cobley, S. Relative Age Effects in Athletic Sprinting and Corrective Adjustments as a Solution for Their Removal. PLoS ONE 2015, 10, e0122988. [Google Scholar] [CrossRef] [PubMed]
  9. Wattie, N.; Tietjens, M.; Cobley, S.; Schorer, J.; Baker, J.; Kurz, D. Relative Age-related Participation and Dropout Trends in German Youth Sports Clubs. Eur. J. Sport Sci. 2014, 14, S213–S220. [Google Scholar] [CrossRef] [PubMed]
  10. Barnsley, R.H.; Thompson, A.H.; Legault, P. Hockey success and birthdate: The relative age effect. CAHPER J. 1985, 51, 23–28. [Google Scholar]
  11. Musch, J.; Grondin, S. Unequal Competition as an Impediment to Personal Development: A Review of the Relative Age Effect in Sport. Dev. Rev. 2001, 21, 147–167. [Google Scholar] [CrossRef]
  12. Ferriz-Valero, A.; García Martínez, S.; Olaya-Cuartero, J.; García-Jaén, M. Sustainable Sport Development: The Influence of Competitive-Grouping and Relative Age on the Performance of Young Triathletes. Sustainability 2020, 12, 6792. [Google Scholar] [CrossRef]
  13. Bloom, B.S. Developing Talent in Young People; Ballantine Books: New York, NY, USA, 1985. [Google Scholar]
  14. Jonker, L.; Elferink-Gemser, M.T.; Visscher, C. Differences in Self-Regulatory Skills among Talented Athletes: The Significance of Competitive Level and Type of Sport. J. Sports Sci. 2010, 28, 901–908. [Google Scholar] [CrossRef] [PubMed]
  15. Ferriz Valero, A.; Sellés Pérez, S.; García Jaén, M.; Cejuela Anta, R. Relative Age Effect for Talents’ Development in Young Triathletes. Retos 2019, 37, 27–32. [Google Scholar] [CrossRef]
  16. Ortigosa-Márquez, J.M.; Reigal, R.; Serpa, S.; Hernández-Mendo, A. Relative Age Effect on National Selection Process in Triathlon. RIMCAFD 2018, 18, 199–211. [Google Scholar] [CrossRef]
  17. Agricola, A.; Poloprutská, M.; Růžička, I. The Relative Age Effect in Czech Orienteering Runners. Stud. Kinanthropologica 2024, 24, 43–49. [Google Scholar] [CrossRef]
  18. Romann, M.; Rössler, R.; Javet, M.; Faude, O. Relative Age Effects in Swiss Talent Development—A Nationwide Analysis of All Sports. J. Sports Sci. 2018, 36, 2025–2031. [Google Scholar] [CrossRef] [PubMed]
  19. Ferriz-Valero, A.; Montiel-Bontmatí, J.; Østerlie, O.; Caraça-Valente, J.P.; Mínguez-Viñambres, A.; Esteve-Ibáñez, H. Tell me your date of birth, and I will tell you how good you are in orienteering. Front. Sports Act. Living 2025, 7, 1558135. [Google Scholar] [CrossRef] [PubMed]
  20. Gagne, F. A Proposal for Subcategories Within Gifted or Talented Populations. Gift. Child Q. 1998, 42, 87–95. [Google Scholar] [CrossRef]
  21. Delorme, N.; Chalabaev, A.; Raspaud, M. Relative Age Is Associated with Sport Dropout: Evidence from Youth Categories of French Basketball. Scand. J. Med. Sci. Sports 2011, 21, 120–128. [Google Scholar] [CrossRef] [PubMed]
  22. Wattie, N.; Schorer, J.; Baker, J. The Relative Age Effect in Sport: A Developmental Systems Model. Sports Med. 2015, 45, 83–94. [Google Scholar] [CrossRef] [PubMed]
  23. Sapra, R.L.; Saluja, S. Understanding statistical association and correlation. Curr. Med. Res. Pract. 2021, 11, 31–38. [Google Scholar] [CrossRef]
  24. Szumilas, M. Explaining odds ratios. J. Can. Acad. Child Adolesc. Psychiatry 2010, 19, 227–229. [Google Scholar] [PubMed]
  25. Olivier, J.; Bell, M.L. Effect Sizes for 2 × 2 Contingency Tables. PLoS ONE 2013, 8, e58777. [Google Scholar] [CrossRef] [PubMed]
  26. Brazo-Sayavera, J.; Martínez-Valencia, M.A.; Müller, L.; Andronikos, G.; Martindale, R.J.J. Relative Age Effects in International Age Group Championships: A Study of Spanish Track and Field Athletes. PLoS ONE 2018, 13, e0196386. [Google Scholar] [CrossRef] [PubMed]
  27. Müller, L.; Hildebrandt, C.; Schnitzer, M.; Raschner, C. The Role of a Relative Age Effect in the 12th Winter European Youth Olympic Festival in 2015. Percept. Mot. Ski. 2016, 122, 701–718. [Google Scholar] [CrossRef] [PubMed]
  28. Costa, A.M.; Marques, M.C.; Louro, H.; Ferreira, S.S.; Marinho, D.A. The Relative Age Effect among Elite Youth Competitive Swimmers. Eur. J. Sport Sci. 2013, 13, 437–444. [Google Scholar] [CrossRef] [PubMed]
  29. Werneck, F.Z.; Lima, J.R.P.D.; Coelho, E.F.; Matta, M.D.O.; Figueiredo, A.J.B. Efeito Da Idade Relativa Em Atletas Olímpicos de Triatlo. Rev. Bras. Med. Esporte 2014, 20, 394–397. [Google Scholar] [CrossRef]
  30. Hancock, D.J.; Adler, A.L.; Côté, J. A Proposed Theoretical Model to Explain Relative Age Effects in Sport. Eur. J. Sport Sci. 2013, 13, 630–637. [Google Scholar] [CrossRef] [PubMed]
  31. Till, K.; Cobley, S.; Wattie, N.; O’Hara, J.; Cooke, C.; Chapman, C. The prevalence, influential factors and mechanisms of relative age effects in UK Rugby League: Relative age effects in Rugby League. Scand. J. Med. Sci. Sports 2009, 20, 320–329. [Google Scholar] [CrossRef] [PubMed]
  32. Dudink, A. Birth Date and Sporting Success. Nature 1994, 368, 592. [Google Scholar] [CrossRef]
  33. Simmons, C.; Paull, G.C. Season-of-Birth Bias in Association Football. J. Sports Sci. 2001, 19, 677–686. [Google Scholar] [CrossRef] [PubMed]
  34. Brustio, P.R.; Kearney, P.E.; Lupo, C.; Ungureanu, A.N.; Mulasso, A.; Rainoldi, A.; Boccia, G. Relative Age Influences Performance of World-Class Track and Field Athletes Even in the Adulthood. Front. Psychol. 2019, 10, 1395. [Google Scholar] [CrossRef] [PubMed]
  35. Smith, K.L.; Weir, P.L.; Till, K.; Romann, M.; Cobley, S. Relative Age Effects Across and Within Female Sport Contexts: A Systematic Review and Meta-Analysis. Sports Med. 2018, 48, 1451–1478. [Google Scholar] [CrossRef] [PubMed]
  36. Saavedra-García, M.; Gutiérrez-Aguilar, Ó.; Sa-Marques, P. Efecto de la edad relativa en el atletismo español Relative age effect in Spanish athletics. Cuad. Psicol. Deporte 2016, 16, 275–286. [Google Scholar]
  37. Malina, R.M.; Eisenmann, J.C.; Cumming, S.P.; Ribeiro, B.; Aroso, J. Maturity-Associated Variation in the Growth and Functional Capacities of Youth Football (Soccer) Players 13–15 years. Eur. J. Appl. Physiol. 2004, 91, 555–562. [Google Scholar] [CrossRef] [PubMed]
  38. Baker, J.; Janning, C.; Wong, H.; Cobley, S.; Schorer, J. Variations in Relative Age Effects in Individual Sports: Skiing, Figure Skating and Gymnastics. Eur. J. Sport Sci. 2014, 14, S183–S190. [Google Scholar] [CrossRef] [PubMed]
  39. González Aramendi, J.M. El efecto relativo de la edad en el fútbol. Arch. Med. Deporte 2007, 24, 5–13. [Google Scholar]
  40. Langham-Walsh, E.; Gottwald, V.; Hardy, J. Relative Age Effect? No “Flipping” Way! Apparatus Dependent Inverse Relative Age Effects in Elite, Women’s Artistic Gymnastics. PLoS ONE 2021, 16, e0253656. [Google Scholar] [CrossRef] [PubMed]
  41. Davison, K.K.; Werder, J.L.; Trost, S.G.; Baker, B.L.; Birch, L.L. Why Are Early Maturing Girls Less Active? Links between Pubertal Development, Psychological Well-Being, and Physical Activity among Girls at Ages 11 and 13. Soc. Sci. Med. 2007, 64, 2391–2404. [Google Scholar] [CrossRef] [PubMed]
  42. Shakib, S. Female Basketball Participation: Negotiating the Conflation of Peer Status and Gender Status from Childhood through Puberty. Am. Behav. Sci. 2003, 46, 1405–1422. [Google Scholar] [CrossRef]
  43. Schorer, J.; Cobley, S.; Büsch, D.; Bräutigam, H.; Baker, J. Influences of Competition Level, Gender, Player Nationality, Career Stage and Playing Position on Relative Age Effects. Scand. Med. Sci. Sports 2009, 19, 720–730. [Google Scholar] [CrossRef] [PubMed]
  44. Wattie, N.; Cobley, S.; Macpherson, A.; Howard, A.; Montelpare, W.J.; Baker, J. Injuries in Canadian Youth Ice Hockey: The Influence of Relative Age. Pediatrics 2007, 120, 142–148. [Google Scholar] [CrossRef] [PubMed]
  45. Vincent, J.; Glamser, F.D. Gender Differences in the Relative Age Effect among US Olympic Development Program Youth Soccer Players. J. Sports Sci. 2006, 24, 405–413. [Google Scholar] [CrossRef] [PubMed]
  46. Gibbs, B.G.; Jarvis, J.A.; Dufur, M.J. The Rise of the Underdog? The Relative Age Effect Reversal Among Canadian-born NHL Hockey Players: A Reply to Nolan and Howell. Int. Rev. Sociol. Sport 2011, 47, 644–649. [Google Scholar] [CrossRef]
  47. McCarthy, N.; Collins, D.; Court, D. Start Hard, Finish Better: Further Evidence for the Reversal of the RAE Advantage. J. Sports Sci. 2016, 34, 1461–1465. [Google Scholar] [CrossRef] [PubMed]
  48. Cumming, S.P.; Lloyd, R.S.; Oliver, J.L.; Eisenmann, J.C.; Malina, R.M. Bio-Banding in Sport: Applications to Competition, Talent Identification, and Strength and Conditioning of Youth Athletes. Strength Cond. J. 2017, 39, 34–47. [Google Scholar] [CrossRef]
Figure 1. Bar chart showing the number of participations by male athletes in the three international competitions under study (EYOC, JWOC, and WOC + EOC), grouped by birth quartile (Q1–Q4). Note. * = Statistically significant difference compared to Q1 (p < 0.05).
Figure 1. Bar chart showing the number of participations by male athletes in the three international competitions under study (EYOC, JWOC, and WOC + EOC), grouped by birth quartile (Q1–Q4). Note. * = Statistically significant difference compared to Q1 (p < 0.05).
Applsci 15 07993 g001
Figure 2. Bar chart showing the number of participations by female athletes in the three international competitions under study, grouped by birth quartile (Q1–Q4). Note. α = Statistically significant difference compared to Q2 (p < 0.05).
Figure 2. Bar chart showing the number of participations by female athletes in the three international competitions under study, grouped by birth quartile (Q1–Q4). Note. α = Statistically significant difference compared to Q2 (p < 0.05).
Applsci 15 07993 g002
Figure 3. Bar chart showing the total number of participations in the three international competitions under study (EYOC, JWOC, and WOC + EOC), grouped by semester of birth (S1 and S2) and competitive group (female or male). Note. * = Statistically significant difference compared to Q1 (p < 0.05).
Figure 3. Bar chart showing the total number of participations in the three international competitions under study (EYOC, JWOC, and WOC + EOC), grouped by semester of birth (S1 and S2) and competitive group (female or male). Note. * = Statistically significant difference compared to Q1 (p < 0.05).
Applsci 15 07993 g003
Figure 4. Odds ratios (OR) and 95% confidence intervals (CI) for Q1/Q4 comparisons across international competitions and competitive groups (W: Women; M: Male). Note. (----) No association threshold (OR = 1); (■) OR with 95% CI.
Figure 4. Odds ratios (OR) and 95% confidence intervals (CI) for Q1/Q4 comparisons across international competitions and competitive groups (W: Women; M: Male). Note. (----) No association threshold (OR = 1); (■) OR with 95% CI.
Applsci 15 07993 g004
Figure 5. Odds ratios (OR) and 95% confidence intervals (CI) for S1/S2 comparisons across international competitions and competitive groups (W: Women; M: Male). Note. (----) No association threshold (OR = 1); (■) OR with 95% CI.
Figure 5. Odds ratios (OR) and 95% confidence intervals (CI) for S1/S2 comparisons across international competitions and competitive groups (W: Women; M: Male). Note. (----) No association threshold (OR = 1); (■) OR with 95% CI.
Applsci 15 07993 g005
Table 1. Frequency of participation in international competitions by competitive group, birth quartile (Q1–Q4), and semester (S1 and S2).
Table 1. Frequency of participation in international competitions by competitive group, birth quartile (Q1–Q4), and semester (S1 and S2).
EventCompetitive GroupQ1Q2Q3Q4S1S2
EYOCFemale221817154032
Male322316185534
JWOCFemale8131092119
Male291711144625
WOC + EOCFemale12167122819
Male25189134322
Note. EYOC = European Youth Orienteering Championships; JWOC = Junior World Orienteering Championships; EOC = European Orienteering Championships; WOC = World Orienteering Championships. Q1 = January–March; Q2 = April–June; Q3 = July–September; Q4 = October–December; S1 = January–June; S2 = July–December.
Table 2. Percentage distribution by birth quartile (Q1–Q4) and semester (S1–S2) among Spanish licensed orienteers (2009–2023), by reference age group and corresponding international competition.
Table 2. Percentage distribution by birth quartile (Q1–Q4) and semester (S1–S2) among Spanish licensed orienteers (2009–2023), by reference age group and corresponding international competition.
Reference Age Group
(International Event)
Q1 (%)Q2 (%)Q3 (%)Q4 (%)S1 (%)S2 (%)
F-16 y F-18 (EYOC)27.4226.7321.4824.3854.1445.86
F-20 (JWOC)29.7226.1022.7421.4555.8144.19
F-E (WOC y EOC)22.6928.6523.6525.0051.3548.65
M-16 y M-18 (EYOC)26.4727.0923.6322.8153.5646.44
M-20 (JWOC)26.5628.0424.0421.3654.6045.40
M-E (WOC y EOC)30.9225.5917.8925.5956.5143.49
Note. M/F-16 = ages 15–16; M/F-18 = ages 17–18; M/F-20 = ages 19–20; M/F-E = senior elite categories (M = male; F = female). Q1 = January–March; Q2 = April–June; Q3 = July–September; Q4 = October–December; S1 = January–June; S2 = July–December.
Table 3. Chi-square test results by birth quartiles (Q1–Q4) for the different international competitions, stratified by competitive group. χ2 (critical) (3) = 7.8147 (p = 0.05).
Table 3. Chi-square test results by birth quartiles (Q1–Q4) for the different international competitions, stratified by competitive group. χ2 (critical) (3) = 7.8147 (p = 0.05).
EventCompetitive GroupQ1Q2Q3Q4χ2pV
EYOCFemale221817150.860.8340.11
Male322316184.540.2090.23
JWOCFemale8131092.010.5700.22
Male291711148.130.0430.34
WOC + EOCFemale12167122.170.5370.22
Male25189132.700.4410.20
Note. EYOC = European Youth Orienteering Championships; JWOC = Junior World Orienteering Championships; EOC = European Orienteering Championships; WOC = World Orienteering Championships. Q1 = born in January–March; Q2 = April–June; Q3 = July–September; Q4 = October–December.
Table 4. Chi-square test results by birth semester (S1–S2) for the different international competitions, stratified by competitive group. χ2 (critical) (1) = 3.8415 (p = 0.05).
Table 4. Chi-square test results by birth semester (S1–S2) for the different international competitions, stratified by competitive group. χ2 (critical) (1) = 3.8415 (p = 0.05).
EventCompetitive GroupS1S2χ2pV
EYOCFemale40320.060.8670.03
Male55342.430.2890.17
JWOCFemale21190.180.8220.07
Male46252.970.0850.20
WOC + EOCFemale28191.270.2590.16
Male43222.460.1170.19
Note. S1 = January–June; S2 = July–December.
Table 5. Odds ratios (OR) and 95% confidence intervals (CI) for comparisons between birth quartiles and semesters across international competitions and competitive groups.
Table 5. Odds ratios (OR) and 95% confidence intervals (CI) for comparisons between birth quartiles and semesters across international competitions and competitive groups.
S1/S2Q1/Q2Q1/Q3Q1/Q4Q2/Q3Q2/Q4Q3/Q4
EYOC (F)1.56
(0.81–3.02)
1.32
(0.63–2.74)
1.42
(0.68–2.98)
1.67
(0.78–3.57)
1.08
(0.50–2.31)
1.27
(0.58–2.76)
1.17
(0.53–2.58)
EYOC (M)2.62 *
(1.43–4.79)
1.61
(0.85–3.06)
2.56 *
(1.28–5.12)
2.21 *
(1.13–4.35)
1.59
(0.77–3.27)
1.37
(0.68–2.77)
0.86
(0.41–1.83)
JWOC (F)1.22
(0.51–2.94)
0.52
(0.19–1.44)
0.75
(0.26–2.15)
0.86
(0.29–2.52)
1.44
(0.55–3.83)
1.66
(0.61–4.48)
1.15
(0.41–3.22)
JWOC (M)3.39 *
(1.70–6.74)
2.19 *
(1.07–4.51)
3.77 *
(1.70–8.37)
2.81 *
(1.33–5.96)
1.72
(0.74–3.99)
1.28
(0.58–2.85)
0.75
(0.31–1.78)
WOC + EOC (F)2.17
(0.95–4.95)
0.66
(0.27–1.62)
1.96
(0.69–5.52)
1.00
(0.40–2.53)
2.95 *
(1.08–8.05)
1.51
(0.62–3.67)
0.51
(0.18–1.44)
WOC + EOC (M)3.82 *
(1.85–7.90)
1.63
(0.78–3.41)
3.89 *
(1.64–9.22)
2.50 *
(1.14–5.49)
2.38
(0.98–5.80)
1.53
(0.68–3.46)
0.64
(0.25–1.63)
Note. (F) = Female competitive group; (M) = Male competitive group. Q1 = January–March; Q2 = April–June; Q3 = July–September; Q4 = October–December; S1 = January–June; S2 = July–December. (*) Statistically significant (95% CI does not include 1).
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Montiel-Bonmatí, J.; Marco-Siles, J.; Ferriz-Valero, A. Born to Win? The Hidden Bias of Birthdates in Spanish Orienteering Talent Selection. Appl. Sci. 2025, 15, 7993. https://doi.org/10.3390/app15147993

AMA Style

Montiel-Bonmatí J, Marco-Siles J, Ferriz-Valero A. Born to Win? The Hidden Bias of Birthdates in Spanish Orienteering Talent Selection. Applied Sciences. 2025; 15(14):7993. https://doi.org/10.3390/app15147993

Chicago/Turabian Style

Montiel-Bonmatí, Javier, Javier Marco-Siles, and Alberto Ferriz-Valero. 2025. "Born to Win? The Hidden Bias of Birthdates in Spanish Orienteering Talent Selection" Applied Sciences 15, no. 14: 7993. https://doi.org/10.3390/app15147993

APA Style

Montiel-Bonmatí, J., Marco-Siles, J., & Ferriz-Valero, A. (2025). Born to Win? The Hidden Bias of Birthdates in Spanish Orienteering Talent Selection. Applied Sciences, 15(14), 7993. https://doi.org/10.3390/app15147993

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop