The Relative Age Effect and Performance in Rhythmic Gymnastics: An Analysis of the 2023 Junior and Senior World Championships

Abstract

The relative age effect (RAE) refers to the advantage often observed in sports selection processes, where athletes born earlier in the calendar year are favored over those born later. While the RAE has been widely studied in various sports, little is known about its presence in rhythmic gymnastics (RG), a female-dominated esthetic sport characterized by early specialization. This study investigated the presence of the RAE among elite rhythmic gymnasts (RGs) at the international level, focusing on differences in birth quarter distribution across age categories and performance levels. The sample included 578 RGs—356 juniors and 222 seniors—competing in individual and group events. Birthdates were categorized into four quartiles (Q1–Q4). Chi-square goodness-of-fit tests and standardized residuals as post hoc tests were used to analyze the RAE. No significant RAE was found in the overall sample or when analyzed by geographic region (p > 0.05). However, a significant under-representation in Q4 occurred for Group RGs (SR = −2.17), and among all juniors (SR = −2.54) (χ²[3, 356] = 9.833, p < 0.05, w = 0.17), particularly in the subgroup of 15-year-old gymnasts, who were over-represented in Q3 (SR = 2.55; χ²[3, 183] = 10.027, p < 0.05, w = 0.23). Finalists—especially those in group events—also showed a higher proportion of Q3 athletes and a lower proportion of those born in Q4. Among junior finalists, Q4 was significantly under-represented (p < 0.05). These novel sport-specific findings suggest the presence of an atypical RAE pattern in RG, particularly in younger age groups and among high-performing athletes. RG coaches and policymakers should consider alternative selection models and adapt training approaches for Q4-born gymnasts in order to prevent early deselection.

1. Introduction

The relative age effect (RAE) refers to the worldwide tendency in sports to favor children and adolescents born earlier in the same calendar year, typically around or shortly after the common cut-off date of 1 January [1]. Athletes who are relatively older within their age cohort tend to have advantages in physical, cognitive, and psychological development, as well as more time for deliberate training, compared to their younger peers [2,3]. This leads to an uneven distribution of birth dates among athletes, with a noticeable overrepresentation of those born in the early months and an underrepresentation of those born later in the year—ultimately resulting in unequal opportunities for younger, less physically mature individuals [4]. The likelihood of the RAE increases from childhood into adolescence but tends to diminish at the senior level [2]. The RAE has also been observed in international athletic populations, varying by geographical origin [5], and it plays a substantial role in talent selection processes [6]. Moreover, the RAE can significantly influence athletic performance in certain sports [7].

Over the past few decades, the relative age effect (RAE) has been extensively studied and confirmed across a wide range of competitive sports [2,8]. Evidence of the RAE has been observed in both team sports—such as soccer [9], basketball [10], handball [11], and volleyball [12]—and individual sports, including swimming [13], wrestling [14], judo [15], tennis [16], track and field [17], and alpine skiing [7]. However, most of the existing research has focused primarily on male athletes [2]. Studies have also highlighted notable gender differences in the manifestation of the RAE [18], indicating that findings based on male populations cannot be directly applied to female athletes [10]. A meta-analysis encompassing 25 sports found that while the RAE does have a significant impact on female sports participation, its effect size is generally small to moderate. The strength of the RAE was shown to vary according to age group, competitive level, and the specific sporting context. Notably, the effect was most pronounced in pre-adolescent athletes (aged 11 and under) and adolescents (aged 12–14), decreased during late adolescence (15–19 years), and was largely absent in adults (over 19 years) [19].

Some researchers argue that esthetic sports rely more heavily on technical skill than on physical maturity, suggesting that disciplines such as dance may not be influenced by the RAE [20]. This hypothesis has been supported in studies involving male and female figure skaters [21] as well as Croatian gymnasts [22]. However, contrasting findings have also emerged. For instance, an overrepresentation of relatively older male athletes was identified in pair skating and men’s singles figure skating over a ten-year period, although season-specific analyses revealed a reverse trend in three particular seasons, and no significant RAE was found among female skaters during the same decade [23]. Similarly, an inverse RAE was detected among Korean male and female middle and high school artistic gymnasts [24]. Thus, esthetic sports exhibited RAE patterns that differed markedly from those in high-contact sports such as wrestling and judo, which were dominated by relatively older athletes [14,15]. In Canadian junior and senior national teams in women’s artistic gymnastics, an unexpected birthdate distribution was observed, with a notable overrepresentation of gymnasts born in the second quartile in both the overall sample and among senior athletes analyzed separately, but not among junior gymnasts [21]. Some studies that explored within-sport variations emphasized the need for more granular analysis. For example, investigations focusing on apparatus specialization among female artistic gymnastics finalists revealed subtle birthdate-related patterns that were not evident in the broader international samples [25]. Interestingly, one study found that female gymnasts born early in the year were significantly less likely to compete at the European Artistic Gymnastics Championships than those born later in the year [26]. Overall, findings related to the RAE in esthetic sports, particularly among female athletes, remain inconclusive. The presence of atypical and inconsistent patterns underscores the need for further research in this area.

Rhythmic gymnastics (RG) is an Olympic esthetic sport practiced exclusively by women, notable for its early specialization and high training demands placed on athletes [27,28]. Talent identification in this discipline often involves anthropometric measurements [29], assessments of coordination and motor learning [30], body composition analysis, and tests of explosive strength and flexibility [31,32]—all of which are known to influence competitive success. At the junior and senior World Championships (WCHs), competitions are held in both individual and group formats, with group events consisting of five gymnasts and one reserve. Based on qualification scores, the top eight individual gymnasts in each of the four apparatuses (hoop, ball, clubs, and ribbon), and the top eight teams in each of the two routines (each with a single type of apparatus for juniors and a routine with one or two types of apparatuses for seniors), advance to the finals [33]. Eligibility for the junior WCH includes athletes aged 13 to 15, determined by the calendar year (1 January to 31 December) [34], which can result in an age gap of up to 36 months among competitors. In the senior category, gymnasts who turn 16 in the year of competition or are older are eligible, with no upper age limit [35]. Several natural differences between the junior and senior RGs, i.e., chronological age, training experience, and competition experience, may influence the occurrence of the RAE [19]. Despite RG’s structural and developmental features, limited research has explored the presence of the RAE in this sport. One study conducted in Bizkaia, Spain, found no evidence of the RAE among rhythmic gymnasts (RGs) aged 9 to 14 [36]. Similarly, Tatlibal et al. [37] reported no significant differences in performance scores (Difficulty Total Scores, Execution Total Scores, and Total Scores) between gymnasts born in the first and second halves of the year among 13-, 14-, and 15-year-old individual junior competitors. However, there is a lack of data regarding group gymnasts and those competing at the senior level.

This study is the first to examine the occurrence of the RAE among elite-group and senior RGs. Consequently, research on the RAE in RG remains limited, particularly concerning individual and group RGs across the junior and senior categories, athletes’ regions of origin, and competition outcomes. In light of this gap, the present study aimed to examine whether the RAE exists within an international sample of elite individual and group RGs and to assess differences in birthdate distribution by age category and level of performance.

2. Materials and Methods

2.1. Participants

The study included a total of 578 elite RGs, comprising 356 juniors and 222 seniors, who competed in both individual and group events. These athletes represented 70 different countries. Data on athletes’ birthdates and competition outcomes were obtained from the official records of the International Gymnastics Federation for the junior WCH (held from 7 to 9 July 2023, in Cluj-Napoca, Romania) and the Senior WCH (held from 23 to 27 August 2023, in Valencia, Spain) [38]. All participants of the 2023 WCH were included in the study, and no exclusion criteria were applied. The research adhered to the principles outlined in the Declaration of Helsinki [39] and conformed to accepted ethical standards in sports science research [40]. As the analysis was based solely on publicly accessible data, formal ethical committee approval was not required.

2.2. Study Variables

Athletes’ birthdates were categorized into four birth quartiles: the first quarter (Q1) included those born from January to March, the second quarter (Q2) from April to June, the third quarter (Q3) from July to September, and the fourth quarter (Q4) from October to December. Birth dates were divided into quartiles to identify trends within each quartile for a detailed analysis of the RAE.

These quartiles were analyzed across the following variables:

• Geographical region: Countries of origin were grouped into four major regions—Europe, Asia and Oceania, the Americas (North and South America combined), and Africa [5];
• Age category: junior total, additionally split among juniors according to the age categories of gymnasts licensed to participate (born in 2010—13 years old (13 y), born in 2009—14 years old (14 y), and born in 2008—15 years old (15 y)), and senior (born in 2007 or earlier);
• Program, i.e., competition format: individual exercises (individual) or group exercises (group);
• Performance level: Athletes were divided into finalists—those who qualified for at least one final or more finals—and non-finalists (N-Fs). Analyses were conducted across the entire sample and within subgroups: individual (junior and senior combined), group (junior and senior combined), junior total, junior individual, junior group, senior total, senior individual, and senior group.

The competition program at the 2023 WCH included the following events: for juniors, Individual Qualifications and Apparatus Finals, as well as the Group All-Around and Group Apparatus Finals [34]; and for seniors, the program consisted of Individual Qualifications, the All-Around Final, Apparatus Finals, Group All-Around Competition, Qualifications for Finals, and Apparatus Finals [35].

2.3. Statistical Analysis

Frequency analyses were conducted to determine the distribution of RGs across the four birth quartiles (Q1–Q4). A chi-square (χ²) goodness-of-fit test was used to compare the observed birthdate distributions with the expected uniform distribution, with statistical significance set at p < 0.05. The assumption of an equal distribution of birth dates across the four quartiles has been widely used in previous studies analyzing international athlete samples. In line with prior RAE research involving international athlete samples [41,42,43], the expected distribution assumed equal representation across all quartiles (i.e., 25% in each). Cohen’s w was calculated to assess effect size, with thresholds interpreted as follows: small = 0.1, medium = 0.3, and large = 0.5 [44]. For any significant chi-square findings, standardized residuals (SRs) were examined as post hoc indicators. An SR greater than 1.96 denoted a statistically significant over-representation, while an SR less than −1.96 indicated a significant under-representation in a given quartile (p < 0.05) [45]. All statistical analyses were performed using Statgraphics Centurion, Version XIX (Statpoint Technologies, Warrenton, VA, USA).

3. Results

The regional distribution of participants at the 2023 RG WCH revealed that the majority (54.1%) originated from Europe, followed by 27.7% from Asia and Oceania, 13.5% from the Americas, and 4.7% from Africa. Figure 1 presents the frequency distribution of athletes’ birthdates based on their respective geographical regions. Results from the χ² goodness-of-fit tests indicated no statistically significant differences in birth quartile distributions across any of the regions: Africa (χ²[3, 27] = 1.296, p > 0.05, w = 0.22), the Americas (χ²[3, 78] = 7.538, p > 0.05, w = 0.31), Asia and Oceania (χ²[3, 160] = 3.35, p > 0.05, w = 0.14), and Europe (χ²[3, 313] = 4.482, p > 0.05, w = 0.12).

The frequency and percentage distributions of birthdates among junior and senior RGs competing in both individual and group events, along with the results of the χ² goodness-of-fit analyses, are presented in

Table 1. Percentage distribution of RGs birthdates and χ² test results by age category and competition format (individual/group) in the Entire Sample.

Sample	Subsample Category		Q1		Q2		Q3		Q4
		n	n	%	n	%	n	%	n	%	χ2	p	w
Entire Sample	Total	578	141	24.4	153	26.5	164	28.4	120	20.7	7.370	0.061	0.11
	Individual	229	62	27.0	53	23.1	61	26.6	53	23.1	1.270	0.736	0.07
	Group	349	79	22.6	100	28.7	103	29.5	67	19.2 ↓	10.186	0.017	0.17
Junior	Total	356	89	24.8	99	27.9	103	29.0	65	18.3 ↓	9.833	0.020	0.17
	13 y	43	13	30.2	15	34.9	8	18.6	7	16.3	4.162	0.244	0.31
	14 y	130	37	28.5	38	29.2	32	24.6	23	17.7	4.338	0.227	0.18
	15 y	183	39	21.3	46	25.2	63	34.4 ↑	35	19.1	10.027	0.001	0.23
	Individual	141	38	26.9	40	28.4	39	27.7	24	17.0	4.843	0.183	0.19
	Group	215	51	23.7	59	27.4	64	29.8	41	19.1	5.633	0.131	0.16
Senior	Total	222	52	23.4	54	24.3	61	27.5	55	24.8	0.810	0.846	0.06
	Individual	88	24	27.3	13	14.8	22	25.0	29	32.9	6.091	0.107	0.26
	Group	134	28	20.9	41	30.6	39	29.1	26	19.4	5.160	0.160	0.20

Note: ↑ = significant (p < 0.05) over-representation of participants compared to the expected value in the quartile; ↓ = significant (p < 0.05) under-representation of participants compared to the expected value in the quartile. Expected quartile distributions were equal (i.e., 0.25%).

. The analysis revealed a statistically significant deviation from the expected uniform distribution in the Group gymnast sample, accompanied by a small effect size (χ²[3, 349] = 10.186, p < 0.05, w = 0.17). Post hoc analysis showed a significant under-representation of athletes born in the fourth quartile (Q4; SR = −2.17). Similarly, the total junior sample demonstrated a significant under-representation of gymnasts born in Q4 (SR = −2.54), also with a small effect size (χ²[3, 356] = 9.833, p < 0.05, w = 0.17). Within the junior category, 15-year-old gymnasts showed a significant departure from the expected distribution (χ²[3, 183] = 10.027, p < 0.05, w = 0.23), marked by an atypical over-representation of those born in Q3 (SR = 2.55). No statistically significant differences in birthdate distribution were found for the entire sample of elite RGs, the overall individual category, junior individuals, junior groups, or any of the senior subgroups (p > 0.05). Some comparisons yielded non-significant results, potentially due to limitations in sample size affecting the findings.

The distribution frequencies and percentages of birthdates for finalists and N-Fs, along with corresponding χ² test results, are provided in

Table 2. Percentage distribution of RGs’ birth quartiles and χ² analysis by performance level (finalists vs. N-Fs) and competition format (individual/group) across the entire 2023 RG WCH sample, including junior and senior categories.

	Level of Performance		Q1		Q2		Q3		Q4
		n	n	%	n	%	n	%	n	%	χ2	p	w
Entire Sample	Finalists	167	41	24.5	41	24.5	58	34.8 ↑	27	16.2 ↓	11.563	0.009	0.26
	N-Fs	411	100	24.3	112	27.3	106	25.8	93	22.6	1.934	0.586	0.07
Subsample category
Individual Total	Finalists	40	10	25.0	10	25.0	11	27.7	9	27.7	0.200	0.977	0.07
	N-Fs	189	52	27.5	43	22.8	50	26.4	44	23.3	1.243	0.742	0.08
Group Total	Finalists	127	31	24.4	31	24.4	47	37.0 ↑	14.2	14.2 ↓	13.315	0.004	0.32
	N-Fs	222	48	21.6	69	31.1	56	25.2	49	22.1	5.063	0.167	0.15
Junior Total	Finalists	79	22	27.9	21	26.6	28	35.4	8	10.1 ↓	10.772	0.013	0.37
	N-Fs	277	67	24.2	78	28.1	75	27.1	57	20.6	3.823	0.280	0.12
Junior Individual	Finalists	20	6	30.0	8	40.0	4	20	2	10.0	4.000	0.261	0.45
	N-Fs	121	32	26.5	32	26.5	35	28.9	22	18.1	3.198	0.362	0.16
Junior Group	Finalists	59	16	27.1	13	22.0	24	40.7 ↑	6	10.2 ↓	11.305	0.010	0.44
	N-Fs	156	35	22.5	46	29.5	40	25.6	35	22.4	2.102	0.551	0.12
Senior Total	Finalists	88	19	21.6	20	22.7	30	34.1	19	21.6	3.909	0.271	0.21
	N-Fs	134	33	24.6	34	25.4	31	23.1	36	26.9	0.388	0.942	0.05
Senior Individual	Finalists	20	4	20.0	2	10.0	7	35.0	7	35.0	3.600	0.308	0.42
	N-Fs	68	20	29.4	11	16.2	15	22.1	22	32.3	4.350	0.225	0.25
Senior Group	Finalists	68	15	22.1	18	26.5	23	33.8	12	17.6	3.882	0.274	0.24
	N-Fs	66	13	19.7	23	34.8	16	24.3	14	21.2	3.696	0.296	0.24

Note: N-Fs = non-finalists; ↑ = significant (p < 0.05) over-representation of participants compared to the expected value in the quartile; ↓ = significant (p < 0.05) under-representation of participants compared to the expected value in the quartile. Expected quartile distributions were equal (i.e., 0.25%).

. The overall finalists group showed a significant deviation from the expected distribution, with a small effect size (χ²[3, 167] = 11.563, p < 0.05, w = 0.26). Adjusted residuals indicated a significant over-representation of athletes born in Q3 (SR = 2.51) and an under-representation of those born in Q4 (SR = −2.28). In the group finalists sample, a similar pattern emerged: RGs born in Q3 were significantly over-represented (SR = 2.71), while those born in Q4 were under-represented (SR = −2.44), with a medium effect size (χ²[3, 127] = 13.315, p < 0.05, w = 0.32). The junior total finalists (χ²[3, 79] = 10.772, p < 0.05, w = 0.37) and junior group finalists (χ²[3, 59] = 11.305, p < 0.05, w = 0.44) also showed significant deviations from an equal distribution, both with medium effect sizes. In the junior total finalists subgroup, Q4 athletes were under-represented (SR = −2.64). Among junior group finalists, Q3 gymnasts were over-represented (SR = 2.41), while Q4 gymnasts were under-represented (SR = −2.28). No significant differences in birthdate distribution were found among any N-Fs subgroups, individual finalists, junior individuals, or senior finalists (p > 0.05).

4. Discussion

This study explored the prevalence of the RAE among individual and group participants of the 2023 RG WCH, considering both age categories and performance levels. Within this international cohort of elite RGs, no evidence of the RAE was identified in the overall sample or across different geographical regions of origin. However, a significantly lower-than-expected number of gymnasts born in the fourth quartile (Q4) was observed among group competitors and within the overall junior category. Additionally, among 15-year-old junior gymnasts, there was a notable over-representation of athletes born in the third quartile (Q3). Similar atypical patterns—marked by an over-representation of Q3 births and under-representation of Q4 births—were found in the overall finalist group, the total sample of group finalists, and the junior group finalists. Furthermore, junior total finalists also showed a significant under-representation of athletes born in Q4. The present work is the first study to date examining the occurrence of the RAE in group and senior RGs at the elite level. While the RAE in RG may not follow the traditional patterns observed in physically dominant sports [19], evidence of selection biases affecting certain athlete categories still exists.

In the overall sample, athletes born in Q2 and Q3 accounted for a larger proportion (54.9%) than those born in Q1 and Q4 (45.1%). These findings partially align with the results reported by Baker et al. [21], who identified a similar birthdate pattern among female artistic gymnasts—though with reversed prevalence between Q2 and Q3 (Q2 > Q3). Among junior participants aged 13 and 14, birthdate distributions did not significantly differ from expected values. However, a notable and atypical over-representation of athletes born in Q3 was detected in the 15-year-old subgroup, which may suggest intentional selection practices. Given their older chronological age compared to 13- and 14-year-old gymnasts, 15-year-olds likely possess more training experience and greater competition exposure [46], potentially enhancing the team’s performance. At the same time, 15-year-old gymnasts born in Q3 are still relatively younger than those born at the beginning of the calendar year. Potentially, this could coincide with a less physically mature and more slender body type—features that may be preferred by coaches [47] and positively valued by judges [48]. It is worth noting that 15-year-olds represented the largest age group among juniors, comprising 51.4% of the category, followed by 14-year-olds (36.5%) and 13-year-olds (12.1%). The distribution of birth quartiles by age group among juniors revealed similar trends in the 13- and 14-year-old subgroups, showing a pattern of Q2 > Q1 > Q3 > Q4, with a modest predominance of Q1 and Q2 births. This pattern shifted in the 15-year-old subgroup, where gymnasts born in Q3 significantly dominated (Q3 > Q2 > Q1 > Q4). Bağcı et al. [49] also found that, among RGs aged 7–14, those born in Q1 and Q2 were more frequent than those born in Q3 and Q4, although statistical significance was not evaluated. Conversely, Hancock et al. [50] found evidence of a standard RAE favoring relatively older gymnasts (under 15) and a reverse RAE favoring relatively younger gymnasts (over 15) in Canadian national-level artistic gymnastics. Wattie et al. [51] suggested that in recreational esthetic sports, relatively older girls born in Q1 and Q2 may be at greater risk of dropping out, possibly due to early pubertal development, which has been associated with adverse psychosocial outcomes and lower levels of physical activity [52]. In the current study, no evidence of the RAE was found in the senior individual, senior group, or senior total categories, which is consistent with findings from another international study on senior female artistic gymnasts [53]. However, a separate analysis of senior individual RGs across continental championships during one Olympic cycle showed a notable difference in chronological age, with a gap of up to 2.3 years between the median ages of American and African athletes [54].

The analysis of birth quartile distributions by performance level revealed a significant over-representation of RGs born in Q3 and an under-representation of those born in Q4 among the overall sample of finalists, as well as within the subgroups of group finalists and junior group finalists. Similar deviations were also observed among all junior finalists, with a notable under-representation of gymnasts born in Q4. In contrast, no evidence of the RAE was found among individual finalists, senior finalists (across all categories), or N-Fs. Performance-level analysis further confirmed that the trends seen in the qualification stage—favoring Q3 and disfavoring Q4—persisted among finalists. Moreover, effect sizes for the observed differences increased from small to medium in both the group finalists and junior group finalists categories, suggesting a stronger influence of this atypical RAE pattern at higher levels of competition. These findings point to the potential impact of relative age on competitive success in rhythmic gymnastics. On the other hand, the absence of significant birthdate distribution differences among junior individual finalists aligns with the findings of Tatlibal et al. [37], who reported no RAE-related differences in performance scores among participants in the first junior WCH in 2019. The significant under-representation of Q4-born athletes in the entire sample of finalists may be explained by early deselection of relatively younger gymnasts—those born at the end of the calendar year—during initial stages of the athlete development pathway. This trend is also reflected in the broader patterns observed among overall group RGs and the junior total sample during the qualification stage. Jakobson et al. [55] similarly documented systemic bias against athletes born later in the calendar year across both physically demanding and cognitive/skill-based sports. The exclusion of relatively younger junior gymnasts at early stages—and their under-representation among 2023 WCH finalists—highlights a potential concern for coaches. Talented RGs born in Q4 may not receive equal training opportunities, which could hinder their long-term development and competitive progression [56]. Less mature athletes may miss out on critical development opportunities if excluded from elite pathways. It is essential that coaches and organizations recognize the RAE and adapt their selection processes to ensure equal opportunities for all athletes, regardless of their chronological age or biological maturity. However, clear confirmation of the occurrence of such a phenomenon within RG requires longitudinal research across different age groups. In the senior categories, the proportion of Q3-born athletes among both total senior finalists and senior group finalists was slightly higher than in other quartiles, but the differences were not statistically significant—suggesting that the influence of atypical RAE diminishes as athletes progress to older age categories.

Talent identification and development in RG, particularly for selecting gymnasts for group exercise routines, is a complex, multi-phase process aimed at optimizing performance in artistry, difficulty, and execution [57]. Beyond ensuring uniform levels of technical skill and physical preparedness, it is also essential to foster positive interpersonal dynamics among group members during both training and competition. Additionally, achieving visual uniformity in body type among selected gymnasts is considered an important criterion [58]. Research has consistently shown that RGs often experience delayed biological maturation [59,60,61]. Intensive gymnastics training initiated in early childhood is associated with a later onset of menarche. For instance, the average age of menarche among RG World Cup participants under 18 was (14.8 ± 1.1) years, while for those over 18, it was (16.6 ± 1.2) years—both figures were significantly influenced by the length of training experience [62]. Furthermore, premenarchal status and a later age of peak height velocity have been linked to higher performance levels [63]. Negative correlations have also been identified between performance scores and various indicators of pubertal development, such as the onset of menarche and the development of breast and axillary hair, in a sample of RGs with a mean age of 11.95 ± 3.09 years [64]. Somatotype’s components, such as endomorphy (relative fatness) and mesomorphy (relative musculoskeletal robustness), were found to negatively affect performance across a range of national- and international-level RGs from beginner to senior levels [65]. As such, physical appearance—particularly a slender physique—is often regarded as a key factor in both talent identification and athlete selection in this highly esthetic sport [66]. On the other hand, biologically more advanced 13–15-year-old junior RGs have demonstrated superior results in flexibility, coordination, and strength tests, compared to their later-maturing peers [67]. This may help explain the current study’s finding of an under-representation of gymnasts born in the last quartile (Q4), who are likely to be the relatively youngest and biologically less mature within their age cohort.

Limitations

A key limitation of this study lies in its cross-sectional design, which captures data at a single point in time and may not fully reflect the broader dynamics of the RAE. Because this study relied on publicly available competition data, it was not possible to examine factors such as athletes’ biological maturity, training history, or selection processes. The findings primarily apply to elite-level athletes and may not be generalizable to younger or recreational gymnasts. Conducting longitudinal research that incorporates biological maturation measures and involves larger sample sizes would enable more robust and generalizable conclusions. Nonetheless, this study’s sequential analysis across different age groups within an international cohort of elite junior RGs—and extending into the senior category—revealed notable birthdate disparities across quartiles. These findings, which have not been widely reported in the previous literature, underscore the importance of continued investigation into the presence and implications of the RAE in RG. Future qualitative research, such as interviews with coaches or athletes, could provide valuable insights and highlight areas that remain unexplored.

5. Conclusions

Among junior and senior participants at the 2023 RG WCH, no clear dominance of relatively older athletes was observed. However, an atypical pattern of the RAE emerged, marked by a significant imbalance in birthdate distribution. Specifically, there was an over-representation of gymnasts born in Q3 and an under-representation of those born in Q4 among juniors during the qualification stage, as well as among finalists overall and within the junior finalists. In contrast, no significant differences in birthdate quartiles were found among seniors when analyzed separately. The presence of significant birthdate disparities among finalists—alongside increased effect sizes compared to the qualification stage—suggests that this atypical RAE may influence competitive success in RG. Its appearance in junior group finalists and the overall group finalist sample, combined with its absence among individual competitors, points to a possible selection bias within group gymnastics contexts.

This study offers new insights into the manifestation of the RAE, highlighting its presence in less anticipated contexts, especially in group events. The results of this study contribute to the growing body of literature on the RAE in elite female sports and highlight the need for further research into the mechanisms driving atypical RAE patterns among RGs. These novel sport-specific findings should prompt RG coaches to reflect on current talent identification, development, and selection practices to monitor both biological and chronological age and to reconsider the methods used in forming junior groups. Particular attention should be paid to avoiding the unintentional exclusion of relatively younger athletes, especially those born in Q4, who may be overlooked despite their potential. RG coaches and policymakers should consider alternative selection models and adapt training approaches for Q4-born gymnasts to help prevent early deselection.