Comparing High School Sport Specialization Trends Between Division I and Club Collegiate Athletes

Abstract

Background:

Adolescent athletes report that sports specialization improves their ability to receive a collegiate athletics scholarship, though this is not well-understood. The purpose of this study was to examine self-reported trends in high school specialization and influences for sport participation between Division I (D-I) and college-aged club (club) athletes.

Hypothesis:

There would be no difference in high school sport specialization or sport participation influences between D-I and club athletes.

Study Design:

Retrospective cross-sectional study.

Level of Evidence:

Level 3.

Methods:

A survey included specialization classification (low, moderate, and high) for 9th to 12th grade, age that the athlete started organized sport and his or her collegiate sport, and several influential factors for participation in one’s primary high school sport (1 = no influence to 5 = extremely influential). Chi-square analyses were used to compare specialization classifications between groups. Nonparametric tests were used to determine significant differences in age-related variables and influential factors between D-I and club athletes. All analysis were also conducted with boys and girls separately.

Results:

Participants included 266 D-I (girls, 155; 58%) and 180 club (girls, 122; 68%) athletes. Club athletes were more likely to be classified as low specialization at every grade in high school, and this difference was more pronounced between D-I and club female athletes than male athletes. The number of years an athlete was classified as highly specialized in high school was not different between D-I and club athletes. Club athletes were more influenced by playing with friends than D-I athletes and D-I athletes were more influenced by pursuing a collegiate scholarship than club athletes.

Conclusion:

High levels of specialization in high school sport may not be necessary for playing at the collegiate level, though some level of specialization in high school might be necessary.

Clinical Relevance:

Clinicians should advocate for healthy long-term athlete development, which does not support high specialization in high school sports.

Within the United States, an estimated 30 million adolescents and children participate in some form of organized sport. ¹ The current culture of youth sports has shifted its focus from the mental and physical benefits of organized sport participation,^11,14,15 to current and future athletic success. ¹⁷ The desire for current and future athletic success has led adolescent athletes to try to gain a competitive edge on their peers by specializing in a specific sport. Recently, youth sport specialization has been defined through a Delphi process as “intentional and focused participation in a single sport for a majority of the year that restricts opportunities for engagement in other sports and activities.” ⁵

For adolescent athletes, one of the perceived benefits of specialization is the chance to obtain a collegiate athletic scholarship,^6,10 or they believe it is helpful for making their high school sport team. ¹⁰ There may be many external factors that promote this perception of sport specialization. Padaki et al ²⁷ found that 22% of their adolescent participants were advised by their parents not to play another sport, while 30% of participants reported that coaches encouraged only playing 1 sport. Yet, the efficacy of youth sport specialization is not well-understood. Several studies have noted that delayed specialization is advantageous for future success;^2,9,12,13 however, others posit that youth sport specialization may play a role in an athlete’s future athletic success.^3,34,35

The international range of these studies makes it difficult to compare results, as youth sports cultures and systems are vastly different from country to country. Particularly, the United States is not well-represented in this area of research. ¹³ Since future athletic success is an important factor in the decision to specialize during adolescence in the United States, it is paramount to understand how high school sport specialization may or may not affect advancement to the next level of athletics. DiFiori et al ¹³ compared Division I (D-I) athletes with undergraduate nonstudent athletes and found there was no difference of age when individuals specialized in a single sport between these 2 groups. However, the definition of sport specialization was the cessation of all sports to focus on 1 sport. ¹³ Though this is certainly sport specialization, it does not fit the current definition of sport specialization, which states that sport specialization can occur in multisport athletes. ⁵ Therefore, a more nuanced approach is needed in measuring sport specialization to better understand its efficacy in the United States.

An interesting athletic population in the United States is collegiate club sport athletes. Club sports have varying competitive levels and, though the most competitive levels boast impressive athletes, they still do not have the year-round structure, facilities, commitments, and elite play that D-I collegiate athletes exhibit. In general, club athletes are recreational athletes who play because they enjoy the sport or want to learn a new sport. Therefore, to compare high school sport specialization trends between these 2 populations can help better identify the efficacy of sport specialization. It is also important to examine the male and female populations in these 2 populations, as research has showed that sport specialization behaviors and effects of sport specialization may be different between adolescent males and females.^10,18,29 Better knowledge of the efficacy of youth sport specialization would allow health care professionals and researchers to better advise recommendations for those in high school sports. Additionally, identifying external factors that may affect high school sport specialization behavior could help identify groups of youth sport stakeholders that can be targeted for dissemination of information on sport specialization.

The purpose of this study was to examine high school specialization trends and influences for sports participation between D-I and college-aged club athletes. Additionally, we examined the differences in these trends by male and female athletes. We hypothesized that retrospective trends in high school sports specialization would not be different between D-I and club athletes, and the influences for high school sports participation would not be different between D-I and club athletes. Additionally, we hypothesized that the differences in high school sport specialization between D-I and club athletes would be more profound in female athletes compared with male athletes, but their influences for sport participation would not be different.

Methods

This cross-sectional study was approved by the institutional review board of the University of Wisconsin–Madison. The overall study design utilized an anonymous paper and online survey for athletes at the same university; freshman D-I athletes completed the survey during their preseason evaluation in the spring of 2015 as described by a previous study of the same D-I athletes. ³⁰ Club athletes, regardless of year in school, completed the survey from September 2019 through May 2020. The primary investigator presented the study to club sport teams at the university during practices or team meetings in fall 2019. Paper surveys were completed by club sport team members after the study presentation. Because of COVID-19 restrictions during spring 2020, the surveys were moved online and created in Qualtrics. The survey link was emailed to club sports presidents who then forwarded the email to their club sports participants. For comparison, only D-I and club athletes that competed in the same sports were included in the analysis. Therefore, the sports utilized within this study were men’s and women’s basketball, ice hockey, tennis, track and field, women’s soccer, softball, women’s volleyball, and men’s wrestling. Additionally, all participants were students at the same university in the Midwest region of the United States. Club athletes were provided a written description of the study, and completing the survey was deemed as gaining consent because the survey was anonymous.

Surveys

The survey contained demographics question such as sex and high school sport participation. The survey included specialization classification for each year of high school (9th-12th) by utilizing an adjusted 3-point scale (low, moderate, and high specialization),^19,30 age the athlete began competing in organized sport, and age the athlete started partaking in one’s collegiate sport. Additionally, multiple influential factors for engaging in one’s primary high school sport were set on a 5-point Likert-type scale (1 = no influence, 5 = extremely influential). These influential factors included parents, friends, best at their primary sport, liked their primary sport the best, tired of other sports, money, grades, time, and pursuit of a collegiate athletic scholarship. For every grade in high school, athletes were classified on a 3-point scale based on their response to 3 questions: (1) “In high school, did you consider one of your sports more important than your other sports? (if you played 1 sport, select ‘yes’)” (2) “In high school, did you train more than 8 months a year in 1 sport?” (3) “In high school, did you quit a sport to focus more on a single sport OR have you only played a single sport?” An athlete who selected “yes” was coded as 1 point, or if he or she marked “no,” then it was scored as 0 points. Summing up the points accumulated from the questions, the categories of specialization were determined (0-1 = low, 2 = moderate, 3 = high) for each grade (9th, 10th, 11th, and 12th). If an athlete selected “yes” to question 3 for a given grade, then that question was indicated as “yes” for his or her subsequent grades in high school; the number of years that a participant was classified as highly specialized (range, 0-4 years) during one’s time in high school was then calculated.

Statistical Analysis

Frequencies and percentages were used for categorical variables. Shapiro-Wilk test was used to test for normality of the distribution of age when athletes started organized sport and their collegiate sport and for all influential factors for D-I and club athletes, respectively. These variables were not normally distributed and were treated as ordinal variables for analysis. Thus, these data are presented as medians, 25% to 75% quartiles, and the range of the reported values. A chi-square analysis was used for categorical data to determine the difference in proportions for biological sex, sport, sport specialization at each high school grade (9th-12th), and the number of years in high school one was classified as a highly specialized athlete between D-I and club athletes. For positive chi-square tests, the standardized residuals for each cell were calculated to determine which cells were the most significant contributors to the significant chi-square analysis, and a standardized residual greater than 2 or less than −2 was considered a significant contributor. ²⁸ An independent-samples Mann-Whitney U test was used to assess the differences in age when athletes started organized sport and their collegiate sport and for all influential factors between D-I and club athletes. To assess if male and female athlete differences existed, the same statistical tests (chi-square and Mann-Whitney U) were used once the data were split by male and female participants. Statistical significance was set a priori at P < 0.05 and all analyses were performed using IBM SPSS statistics (Version 27.0; IBM Corp).

Results

Demographic information is outlined in Table 1. Classifications using the 3-point scale for sports specialization are highlighted within Table 2 where specialization for each grade demonstrated a significant difference between D-I and club athletes. Club athletes were more likely to be classified as low specialized athletes in 9th grade and were less likely to be classified as moderately specialized athletes compared with D-I athletes (Table 2). Club athletes were consistently more likely to be classified as a low specialized athlete compared with D-I athletes (Table 2). However, for 9th through 12th grade, the standardized residual for high specialization was never greater than 0.9 or less than −1.1 (Table 2). Therefore, high specialization was never a major contributor for the chi-square analysis between these 2 groups throughout high school. When a chi-square analysis of each individual 3-point scale question was performed for each grade, we found that D-I athletes were more likely to identify that their primary sport was more important than other sports (9th grade: D-I = 91% vs club = 80%, P = 0.001; 10th grade: D-I = 93% vs club = 87%, P = 0.023; 11th grade: D-I = 95% vs club = 91%, P = 0.080; 12th grade: D-I = 95% vs club = 88%, P = 0.012) and they were more likely to identify that they trained more than 8 months of the year in their primary sport compared with club athletes (9th grade: D-I = 88% vs club = 75%, P < 0.001; 10th grade: D-I = 89% vs club = 78%, P = 0.001; 11th grade: D-I = 90% vs club = 84%,P = 0.030; 12th grade: D-I = 92% vs club = 78%, P < 0.001). However, there was no significant difference at any grade (9th-12th) between D-I and club athletes in their answers to whether they have quit a sport to focus on a single sport or not (question 3). The number of years an athlete was specialized in high school, in addition to when one began participation in organized sport, revealed no significant difference between D-I and club athletes (Table 2). However, club athletes were more likely to begin their collegiate sport later in life compared with their D-I peers.

Table 1.

Demographic information and chi-square analysis for differences between club sport athletes and D-I varsity sport athletes

Variable	Club Athlete (n = 180), n (%)	D1 Athlete (n = 266), n (%)	P a
Sex			0.042
Male	58 (32.2)	111 (41.7)
Female	122 (67.8)	155 (58.3)
Sport			<0.001
Basketball	39 (21.7)	41 (15.4)
Ice hockey	26 (14.4)	69 (25.9)
Soccer	18 (10.0)	33 (12.4)
Softball	17 (9.4)	30 (11.3)
Tennis	13 (7.2)	17 (6.4)
Track	25 (13.9)	12 (4.5)
Volleyball	34 (18.9)	14 (5.3)
Wrestling	8 (4.4)	50 (18.8)

^aP values in boldface indicate statistical significance.

Table 2.

Association of sport specialization level throughout grades 9 to 12 and sport level (club or D-I athlete)

Sport Specialization Variable	Club Athlete, n/Total (%)	D-I Athlete, n/Total (%)	P a
9th grade b			<0.001
Low	59/175 (33.7)	36/265 (13.6)
Standardized residual	3.5	–2.8
Moderate	58/175 (33.1)	136/265 (51.3)
Standardized residual	–2.2	1.8
High	58/175 (33.1)	93/265 (35.1)
Standardized residual	–0.3	0.2
10th grade b			<0.001
Low	51/175 (29.1)	25/265 (9.4)
Standardized residual	3.8	–3.1
Moderate	62/175 (35.4)	128/265 (48.3)
Standardized residual	–1.6	1.3
High	62/175 (35.4)	112/265 (42.3)
Standardized residual	–0.9	0.7
11th grade b			0.012
Low	34/176 (19.3)	25/265 (9.4)
Standardized residual	2.2	–1.8
Moderate	62/176 (35.2)	106/265 (40.0)
Standardized residual	–0.6	0.5
High	80/176 (45.5)	134/265 (50.6)
Standardized residual	–0.6	0.5
12th grade b			<0.001
Low	40/174 (23.0)	22/264 (8.3)
Standardized residual	3.1	–2.5
Moderate	54/174 (31.0)	95/264 (36.0)
Standardized residual	–0.7	0.5
High	80/174 (46.0)	147/264 (55.7)
Standardized residual	–1.1	0.9
No. of years in high school being highly specialized			0.432
0	88/173 (50.9)	113/264 (42.8)
1	8/173 (4.6)	15/264 (5.7)
2	16/173 (9.2)	25/264 (9.5)
3	9/173 (5.2)	23/264 (8.7)
4	52/173 (30.1)	88/264 (33.3)
Age started organized sports (median [25%, 75% quartile]; max-min) c	6 [5, 8.8]; 5-18	6 [5, 7]; 3-14	0.142
Age started collegiate sports (median [25%, 75% quartile]; max-min) c	8 [5, 12]; 5-19	6 [5-10]; 3-20	0.029

^aP values in boldface indicate statistical significance.

^bStandardized residuals were used for the significant chi-square analysis to better determine which cells were the most significant drivers of the significant chi-square analysis. Cells with a larger absolute standardized residual value were cells that were most significant in the chi-square analysis.

^cAnalyzed using Mann-Whitney U ranked test because data were not normally distributed. When this analysis was separated by male and female, neither age started organized nor collegiate sport was significantly different between club and D-I athletes.

A comparison of influential factors between D-I and club athletes is illustrated in Table 3. Club athletes were more likely to be influenced by their friends than D-I athletes in deciding to participate in their high school primary sport (club median = “somewhat influential” vs D-I median = “slightly influential”). Club athletes were more likely to be influenced by grades and being tired of other sports compared with D-I athletes in deciding to participate in their high school primary sport. However, both groups’ median answer for both questions was “did not influence at all.” In comparison, D-I athletes were more likely to identify pursuit of a college scholarship as being more influential for playing their primary sport than club athletes (median of “extremely influential” compared with “slightly influential”). D-I athletes were also more likely to cite their parents and “being the best at that sport” as more influential than club athletes in deciding to participate in their high school primary sport. D-I athletes were also more likely to cite not having enough time for more than 1 sport as an influential factor for their primary high school sport compared with club athletes (D-I median = “slightly influential” vs club median = “did not influence decision”).

Table 3.

Median and quartiles for sport specialization influential factors and Mann-Whitney U ranked test for level of influence by sport level (club or Division I [D-I] athlete)

Survey question: Please select how much each of the following factors influenced your decision to participate in your primary sport in high school	Overall			Male			Female
	Club	D-I		Club	D-I		Club	D-I
	Ranking b , c	Ranking b , c	P a	Ranking b , c	Ranking b , c	P a	Ranking b , c	Ranking b , c	P a
Influence of parents	3 [2, 4]; 189.5	3 [2, 4]; 223.1	0.004	3 [2,4]; 78.5	3 [2, 4]; 83.1	0.539	3 [2, 4]; 112.5	3 [3, 4]; 141.3	0.001
Influence of friends playing that sport	3 [2, 4]; 249.2	2 [1, 3]; 179.7	<0.001	3 [2,4]; 99.8	2 [1, 3] 71.5	<0.001	3 [2, 4]; 150.5	2 [1, 3]; 108.3	<0.001
Influence best at that sport	4 [3, 5]; 187.4	5 [4, 5]; 224.0	0.001	4 [3, 5]; 68.1	5 [4, 5]; 88.1	0.005	4 [3, 5]; 119.1	5 [4, 5]; 135.8	0.053
Participant liked one’s primary sport the most	5 [4, 5]; 207.1	5 [4, 5]; 208.7	0.869	5 [4, 5]; 81.9	5 [4, 5]; 80.5	0.825	5 [4, 5]; 125.9	5 [4, 5]; 128.9	0.681
Participant had been injured in other sports	1 [1, 1]; 215.9	1 [1, 1]; 204.0	0.097	1 [1, 1]; 83.9	1 [1, 1]; 80.2	0.445	1 [1, 1]; 132.7	1 [1, 1]; 124.0	0.098
Participant was tired of other sports	1 [1, 2]; 226.1	1 [1, 1]; 196.5	0.002	1 [1, 2]; 89.3	1 [1,1]; 76.4	0.023	1 [1, 2]; 136.4	1 [1, 2]; 121.6	0.057
Participant did not have enough money to play more than 1 sport	1 [1, 1]; 212.6	1 [1, 1]; 206.3	0.205	1 [1,1]; 83.7	1 [1,1]; 80.3	0.293	1 [1,1]; 129.7	1 [1, 1]; 126.6	0.425
Participant’s grades suffered	1 [1, 1]; 215.6	1 [1, 1]; 205.1	0.005	1 [1,1]; 84.7	1 [1, 1]; 79.7	0.033	1 [1,1]; 131.5	1 [1, 1]; 125.9	0.055
Participant did not have enough time for more than 1 sport	1 [1, 2]; 184.0	2 [1, 3]; 227.3	<0.001	1 [1, 2]; 78.3	1 [1,3]; 83.2	0.461	1 [1, 2]; 105.6	3 [1, 4]; 147.6	<0.001
Participant’s parents did not have enough time for participant to play more than 1 sport	1 [1, 1]; 206.2	1 [1, 1]; 211.9	0.397	1 [1, 1]; 82.6	1 [1,1]; 80.9	0.632	1 [1, 1]; 123.9	1 [1, 1]; 132.5	0.126
Participant had the best opportunity to pursue a college scholarship in that sport	2 [1, 4]; 140.9	5 [4, 5]; 258.1	<0.001	3 [1, 4]; 55.7	4 [3, 5]; 94.9	<0.001	2 [1, 4]; 86.4	5 [4, 5]; 164.4	<0.001

^aP values in boldface indicate statistical significance.

^bRanking: 1 = did not influence decision at all, 2 = was slightly influential in decision, 3 = somewhat influential in decision, 4 = was very influential in decision, 5 = was extremely influential in decision.

^cPresented as median [25%, 75%]; mean rank from Mann-Whitney U test.

When all analyses were separated by boys and girls, several differences were noted. Figure 1 demonstrates the comparison of high school sport specialization trends between male and female club and D-I athletes. Sport specialization categorization in 9th and 10th grades was significantly different between club and D-I male athletes, but this significant difference did not exist for 11th and 12th grades (Figure 1). For 9th and 10th grades, male D-I athletes were more likely to be moderately specialized compared with male club athletes, and male club athletes were more likely to be classified as low specialized athletes compared with D-I athletes (low: D-I = 15.5%, standardized residual = −1.3 vs club = 32.1%, standardized residual = 1.8; moderate: D-I = 50.0%, standardized residual = 1.2 vs club = 28.6%, standardized residual = −1.6; P < 0.05). There was a significant difference in specialization in 9th, 10th, 11th, and 12th grades between D-I and club female athletes (Figure 1). In general, female D-I athletes were less likely to be categorized as low specialization athletes compared with female club athletes at every grade level (low 9th grade: D-I = 12.3% vs club = 34.5%; low 10th grade: D-I = 7.7% vs club = 30.5%; low 11th grade: D-I = 8.4% vs club = 21.0%; low 12th grade: D-I = 7.1% vs 25.6%). Though these chi-square values were significant, high specialization’s greatest residual was 0.9 (12th-grade female D-I athletes) and the lowest standardized residual was −1.0 (12th-grade female club athletes) demonstrating that high specialization was never a major contributor in the female-only chi-square analyses. Neither the male nor female analyses had significant differences in the number of years of high specialization throughout high school between D-I and club athletes (Figure 2).

Figure 1.

Graphical illustration of the change in sport specialization from 9th to 12th grade for club and Division I (D-I) male (top) and female (bottom) athletes. *P < 0.05, **P < 0.01, ***P < 0.001.

Figure 2.

Graphical illustration of the number of years an athlete was classified as highly specialized in high school compared between club and Division I (D-I) male (top) and female (bottom) athletes. Top: Chi-square comparing club and D-I male athletes: P = 0.678. Bottom: Chi-square comparing club and D-I female athletes: P = 0.352.

The differences for each influential factor between club and D-I athletes for both boys and girls are outlined in Table 3. Unlike the overall sample and female athletes, there was no significant difference in parental influence between club and D-I male athletes’ decision to participate in their high school primary sport (Table 3). There was a significant difference in the influence of pursuing a college scholarship between D-I and club athletes for both male and female athletes. However, this difference was much larger in girls than boys. D-I female athletes had a median response of “extremely influential” compared with club female athletes’ median response of “slightly influential”; however, male D-I athletes had a median response of “very influential” compared with the club male athletes’ median response of “somewhat influential.” There were no significant differences for influential factors such as “best at primary sport,” “tired of other sports,” and “grades” between D-I and club female athletes; however, all the P values were trending toward significance.

Discussion

Our findings did not support our hypothesis that sport specialization trends in high school did not differ between D-I and club athletes. Previous studies have demonstrated that the motivation for high school sport specialization is partially because of one’s desire to obtain a collegiate athletic scholarship.^10,27 Several studies have demonstrated the association of delayed sport specialization with later sporting success;^2,9,12,13 however, there are some contrary statements and findings.^3,34,35 Compared with the few sport specialization efficacy studies in the United States, our study partially agrees with results from DiFiori et al, ¹³ Swindell et al, ³⁷ and Black et al. ⁸ Our results are similar to previous research, which found no difference in the age individuals started to specialize in a single sport.^8,13 Our results are also in agreement with the findings of DiFiori et al that the average age of organized sport initiation was not different between student athletes and nonstudent athlete undergraduate students (7.2 ± 2.6 vs 7.7 ± 3.5 years, respectively).

Club athletes may have started their collegiate sport significantly later than D-I athletes because of the nature of club sports compared with D-I athletics. For many collegiate club sports, any student is eligible to try out for university club teams, and most club teams do not cut but divide teams into skill-based divisions. ³¹ However, our results may support previous evidence that deliberate engagement in a primary sport early in life may help improve skills later in life. ³⁴ Additionally, our results align with previous findings that 45% of D-I athletes played multiple sports until they were 16 years old. ³⁷ Therefore, it is possible that a high school athlete who can identify a primary sport and has dedicated more of his or her year to a single sport is more likely to become a D-I athlete than a club collegiate athlete regardless of quitting participation in other high school sports. However, this interpretation must be made with caution, as load management and injury risk must be considered for proper long-term youth athlete development.^20-22

Our hypothesis was incorrect for differences in influential factors for sport participation between D-I and club athletes. We did not expect such a difference between these 2 groups in influential factors to participation in high school sport, as Padaki et al ²⁷ found that 70% of 235 athletes between the ages of 7 and 18 years aspired to play at the collegiate level or professional level. Similarly, Brooks et al ¹⁰ reported that 66% of their adolescent participants thought receiving a college athletic scholarship was a “very” or “extremely” important reason for why they participated in sport. It is possible that the retrospective nature of the current study influenced the responses to the survey. For example, D-I athletes may remember their high school sporting career as a steppingstone to their current athletic engagement whereas club athletes may not remember their high school motives for playing at the D-I level because their high school sport engagement did not actualize that desire. However, because of these differences between D-I and club athletes, it also seems plausible that the athlete’s influences for sport participation may highlight differences in the high school sporting environment that D-I and club athletes experienced. DiFiori et al ¹³ demonstrated that the initiation of sport specialization was not different between nonathlete undergraduate students and D-I student-athletes, but found that there was a significant difference in the number of family members who played collegiate or professional sports between nonathlete undergraduate students and student-athletes. We theorize that genetics and the environment of a high achieving athletic family dynamic may be important factors that enhance one’s chances at playing at the D-I level. ¹³ Our results seem to support the environmental and family dynamic aspect of DiFiori et al’s theory. ¹³

Male and Female Differences

Our results may suggest that sport specialization is more efficacious for female athletes than male athletes, and that hypothesis is worth considering and needs further investigation. If that theory is true, it may explain why sport specialization has been found to be more common in female athletes than male athletes in previous studies^7,29 and why adolescent female athletes believe sport specialization is more beneficial than do their adolescent male counterparts. ¹⁰ However, it is also possible that this trend of higher specialization in D-I female athletes is a product of the current female sport culture in the United States. A report in 2017 by the National Collegiate Athletic Association identified the average grade when certain sports began to recruit athletes. ²⁵ Eight out of the 15 women’s sports reported that over 50% of their first recruiting contact with female athletes occurred in 9th and 10th grades. ²⁵ In comparison, only 2 out of 11 men’s sports reported that over 50% of their first recruiting contact occurred in 9th and 10th grades with the remaining 9 sports reporting that over 50% of their first recruiting contact occurred in 11th and 12th grades. ²⁵ Some of these differences may be due to sport as well, as female gymnastics and figure skating have some of the earliest ages when sport specialization starts to occur.^33,36 Our reported difference in high school participation characteristics between club and D-I female athletes needs to be interpreted with caution; our results may suggest that some level (ie, moderate) of sport specialization may be necessary for female athletes in high school, but not “high” levels of sport specialization as defined by the 3-point scale.

It is possible that family dynamics and potential family success ¹³ were more advantageous for our female D-I population than our male D-I population. Padaki et al ²⁶ identified that parents have an influence on their children to specialize in a single sport. It is possible that suggestions to specialize from parents are more impactful for adolescent female athletes than male athletes. If so, parents may be a crucial influencer in preventing adolescent female sport specialization. However, this was not found in a recent study, as parental modeling was not significantly different at predicting male and female physical activity. ³² Therefore, the role of parental influence on female sport success and participation needs to be explored in future studies.

Limitations

Several limitations exist with this study that should be recognized. Though we used a common method for measuring sport specialization,^4,19,23 it is important to recognize that many methods have been used in operationally defining sport specialization.^8,13,16,24 We have used the method that we believed aligns best with the most recent definition of sport specialization. ⁵ High school sports specialization was based on retrospective answers to high school participation and volume. Therefore, none of these associations can be interpreted as causational, and recall bias may affect some of our results. It is also important to recognize that recall bias may have been more pronounced in the club athletes since they were of all collegiate grade levels whereas the D-I athletes in this study answered the survey as first-year college students. However, we feel our results provide further support for future studies to better address the question of the efficacy of sport specialization in high school athletes. It is important to note that both populations were playing sports at the collegiate level, and therefore these results may not be generalized to other populations such as high school athletes that never compete in sport after high school. A longitudinal study design that follows high school students into their early collegiate years would provide the best information for high school sport specialization efficacy.

Conclusion

The duration of being highly specialized in a single sport throughout his or her high school career were not significantly different between D-I and club athletes. However, it appears that a moderate level of specialization throughout high school was different between D-I and club athletes, and this difference was more pronounced between female D-I and club athletes. Differences in influential factors for high school sports participation were demonstrated between D-I and club athletes. These findings continue to support the idea that parents may be a significant avenue for health care providers to disseminate information about the effects and potential risks of sport specialization. Our reported differences in influential factors between D-I and club athletes may demonstrate the importance of the culture and perspective of sports in one’s upbringing and expectation of what they wished to get out of high school sport participation. Our results along with previous literature can help to advance the discussion of the potential rewards and risks of high school sport specialization and provide new knowledge that will allow future research to better answer questions related to sport specialization.