https://orcid.org/0000-0002-9837-9957
ABSTRACT
Objectives
The purpose of this study is to examine NCAA Division I volleyball players’ return to play rates and performance statistics compared to pre-injury levels following ACL injury.
Methods
Female volleyball players that sustained ACL injuries from 2008 to 2020 and competed in one of seven collegiate conferences (n = 99) were identified via an internet search algorithm. Players were categorized by position, academic year, and playing time pre- and post-injury. Post-injury performance statistics were gathered for a subset of outside hitters and middle blockers that played in ≥35 sets in a single season for up to 3 years following injury (mean 1.7 seasons). A control group (n = 512) was generated for demographic and statistical comparison. Mean pre-injury and post-injury statistics were compared for players that did not change positions and played ≥35 sets before and after injury.
Results
Volleyball attackers were 54.7% of the control population but sustained 78.8% of identified injuries. Following ACL injury, 6.1% of players registered no in-game statistics, 16.2% played in <35 sets, 65.7% played in ≥35 sets, and 12.1% graduated. Mean performance statistics increased linearly the more years players were from ACL injury.
Conclusions
Female collegiate volleyball players return to play following ACL injury at high rates (93.1%) and maintain pre-injury performance levels. Volleyball attackers sustain ACL injuries more commonly than setters and libero/defensive specialists.
Introduction
Anterior cruciate ligament (ACL) tears are a common injury among collegiate women’s volleyball players. The injury rate among these NCAA athletes is estimated to range between 0.04 and 0.08 injuries per 1000 athletic exposures [Citation1]. Despite its prevalence, the literature regarding ACL tears among collegiate women’s volleyball players is sparse. Those studies that do include collegiate female volleyball players are often aggregates of athletes participating in a variety of sports and details of specific cohorts are difficult to extrapolate.
Most studies that included collegiate women’s volleyball players have investigated ACL injury risk factors [Citation2], the effectiveness of injury screening programs [Citation3], and effectiveness of ACL injury prevention programs [Citation4], while other studies analyzed populations including Division I Women’s volleyball players for post-injury biometrics and re-injury risk [Citation5,Citation6]. No studies have assessed changes in statistical performance of collegiate volleyball players or rate of return to play. Specific knowledge on return-to-play and performance following anterior cruciate ligament injury among female volleyball players will help counsel patients and set expectations following injuries in this cohort.
The purpose of this study is to determine the return-to-play rates and performance outcomes for NCAA Division I women’s volleyball players that have sustained ACL injuries. We hypothesized that female collegiate volleyball players will return to sport following ACL injuries at pre-injury performance levels.
Materials and methods
Search method
Press releases and articles were electronically gathered during the approximate period of 15 April 2021 to 15 June 2021, to identify NCAA Women’s volleyball players that sustained ACL tears from the years 2008 to 2020. Because of the 2008 NCAA Women’s volleyball rule changing each game from 30 to 25 points, players with injuries sustained before the 2008 season were not analyzed. The following terms were searched on the athletic department websites of all schools participating in conferences that sent a team to the NCAA Women’s Volleyball Final Four since 2008: ‘Volleyball ACL,’ ‘Volleyball Anterior Cruciate Ligament,’ and ‘Volleyball Knee Injury.’ The conferences studied were the Big Ten, Pac-12, Big 12, Southeastern (SEC), Atlantic Coast (ACC), Big West, and West Coast (WCC). In addition, Google searches were performed to identify articles by local or national news sources that reported ACL tears of players that compete in these conferences. The following search terms were entered into the Google search engine: ‘School Name Volleyball ACL,’ ‘School Name Volleyball Anterior Cruciate Ligament,’ and ‘School Name Volleyball Knee Injury,’ where ‘School Name’ was replaced by a university in the conferences stated above. When a search result from either of these methods described a player sustaining an unspecified knee injury, the following searches were performed in the Google search engine to attempt to identify the injury: ‘Player Name ACL,’ ‘Player Name Anterior Cruciate Ligament.’
Inclusion/exclusion
A player was included if an article was found describing her sustaining an ACL tear from a source that was a news outlet, university article, or contained an interview with the player. Players who sustained ACL tears in high school, prior to playing for their university, or had a tear where a time frame could not be identified were excluded. Players with eligibility beyond the 2021–2022 season that played in fewer than 35 sets post-injury were excluded from play time and statistical analysis.
Data analysis
Players were categorized based on pre-injury and post-injury playing time. Criteria for play time categories are shown in . Thirty-five sets were chosen as delineation between ‘limited’ and ‘significant’ playing time because that amount represents approximately one-third of a season. A player was considered as participating in a set if they registered any volleyball statistic in that set, as demonstrated by the official statistics published on their respective athletic website, their athletic conference website, or the NCAA website. There were no minimum points or time requirements. Injured players were also stratified by position and the year in school they were when tearing their ACL. Returning to play was defined as an athlete registering a statistic in a match after injury. Chi-square tests were used to examine the association between pre-injury play time as well as volleyball position on return to play rates.
Table 1. Categorization criteria for players sustaining an ACL tear.
For outside hitters and middle blockers who played a season with more than 35 sets after their tear, a player’s individual game statistics for each season were gathered via their respective athletic website, their athletic conference website, or the NCAA website. Performance statistics gathered were kills per set, hitting percentage, blocks per set, and digs per set. Statistical performance analysis was completed only on outside hitters and middle blockers because other positions did not have sufficient players for adequate analysis. Linear regression analyses were performed using Microsoft Excel for average statistics each year since a player returned from her tear to determine post-injury statistical trends. Statistics four or greater years from the time of ACL tear were excluded from analysis for middle hitters and outside hitters due to insufficient data size (less than five players).
In a subgroup of athletes who played more than 35 sets before and after their injury and stayed the same position, pre-injury and post-injury characteristics were analyzed with paired, two sample t-tests.
To evaluate performance over the course of an uninjured player’s career, a random sample (n = 512) of the entire population of volleyball players was created. This control group was generated by assigning each school in each conference a unique number and using a random number generator to select both a school and a season between 2008 and 2020. The volleyball positions, year in school, and performance statistics (kills per set, hitting percentage, blocks per set, and digs per set) were gathered for players that played at least 35 sets for the school in that selected season. For both positions, the average of each static for each academic year was calculated. Average statistics of each position were plotted against the player’s year in school for their first through fourth seasons.
Results
Ninety-nine female collegiate volleyball players that met inclusion criteria were identified. 512 players competing for 47 teams (mean 10.9 players/team) were identified in the control group. The majority of female collegiate volleyball players sustaining ACL tears were outside hitters (44.4%) and middle blockers (29.3%). A complete list of ACL tears by position as well as positional breakdown of the control group is shown in . Volleyball attackers (outside hitters, middle blockers, and opposite hitters) sustained a higher percentage of tears compared to libero/defensive specialists and setters.
Table 2. Positional breakdown by group.
When excluding graduating seniors, setters had the highest return to play rate of all positions at 100.0%, and opposites had the lowest return to play rate at 75.0%. Return to play rates and characterization of playing time after injury of each position is shown in . No significant differences in return to play were demonstrated between positions (p-value = 0.57).
Table 3. ACL tear outcomes by position.
If graduating seniors were not included in analysis, 93.1% of players returned to play with 74.7% returning to play greater than 35 sets the years after sustaining an ACL tear. Eighteen players (18.2%) did not return to play collegiate volleyball following the ACL tear, but 12 were graduating seniors.
graphs the average kills/set, hitting percentage, and total blocks/set of middle blockers at 1, 2, and 3 years returned from an ACL tear (mean 1.5 seasons of statistics collection) compared to the same statistics for control group middle blockers that played collegiately for 1 through 4 years. graphs the average kills/set, hitting percentage, total blocks/set and digs/set of outside hitters at 1, 2, and 3 years returned from an ACL tear (mean 1.8 seasons of statistics collection) compared to the same statistics for control group outside hitters that played collegiately for 1 through 4 years. Middle blockers had linear improvement in average kills per set, hitting percentage and total blocks per set in the years following return after ACL tear. Outside hitters demonstrated continued linear improvement in average kills per set, hitting percentage, total blocks per set, and digs per set in the years following return after ACL tear. The improvements in most outside hitter statistics were at rates better than or nearly equal to those of the control groups.
Figure 1. Kills/Set (1A), hitting percentage (1B), and total Blocks/Set of middle blockers that played 35 sets or more after ACL injury. Grey circle series: average statistics of middle blockers in their first (17), second year (9), and third year (5) returning from an ACL tear. Black triangle series: average statistics of middle blockers in the control group in their first (21), second (25), third (25), and fourth (33) years playing collegiately. Horizontal black lines demonstrate mean pre-injury kills/set (1.95), hitting percentage (0.28), and total blocks/set (0.87) for a subset of these middle blockers that played ≥35 sets prior to injury.
Figure 2. Kills/Set (2A), hitting percentage (2B), total Blocks/Set (2C), and Digs/Set (2D) of outside hitters that played 35 sets or more after ACL injury. Grey circle series: average statistics of outside hitters in their first (25), second (19), and third year (9) returning from an ACL tear. Black triangle series: average statistics of outside hitters in the control group in their first (36), second (36), third (32), and fourth (34) years playing collegiately. Horizontal black lines demonstrate mean pre-injury kills/set (2.45), hitting percentage (0.18), total blocks/set (0.42), and digs/set (1.48) for a subset of these outside hitters that played ≥35 sets prior to injury.
In the self-comparison group, no statistically significant differences were seen between middle blocker’s pre-injury and post-injury hitting percentages (p = 0.77) or kills/set (p = 0.30). A statistically significant difference was seen in middle blocker’s pre-injury total blocks/set compared to post-injury (p = 0.04). For outside hitters, no statistically significant differences were seen in pre-injury or post-injury hitting percentage (p = 0.35), kills/set (p = 0.75), digs/set (p = 0.19), or total blocks/set (p = 0.67).
Regardless of pre-injury playtime, players returned to play at high rates. shows differences in return to play rates by pre-injury playtime. 60.0% of players that played 0 sets prior to injury, 60.9% of players that played <35 sets prior to injury, and 67.6% of players that played ≥35 sets prior to injury returned to play ≥35 sets over the rest of their collegiate career. Overall return to play (registering an in-game statistic following injury) was 100.0%, 82.6%, and 96.7% for each of these groups, respectively, when graduating players were excluded. Differences in return to play rates between groups were not statistically significant (p = 0.18).
Figure 3. ACL tear group separated into three sub-groups: playing 0 sets prior to injury, playing in <35 sets prior to injury, and playing in ≥35 sets prior to injury. Bars demonstrate the number of players in each of these sub-groups that returned to play ≥35 sets, <35 sets, 0 sets, or graduated the years following the injury.
Discussion
This study demonstrates that the majority of NCAA female volleyball players that tear their ACL are outside hitters (44.4%) or middle blockers (29.3%). A large percentage of the NCAA female volleyball players studied returned to play: 81.2% were able to register a statistic in a collegiate women’s volleyball match and 64.6% played 35 sets or more after their injury. These percentages increase to 93.1% and 73.8%, respectively, when excluding seniors who tore their ACL and graduated. Pre-injury playtime or position did not demonstrate a statistically significant impact on an athlete’s ability to RTP. For those that do return to play, outside hitters and middle blockers continue to linearly improve in all their most important statistical categories.
Despite most post-injury statistics exceeding pre-injury statistics, we were unable to demonstrate statistically significant differences in pre-injury and post-injury statistics for any position other than total blocks/set in middle blockers. Though this finding may be interpreted as players remain at the same statistical performance level before and after ACL tears, our study was also potentially too underpowered to demonstrate statistical significance.
Overall, 63% of those sustaining anterior cruciate ligament reconstruction return to pre-injury level of play and only 44% return to competitive sports [Citation7]. The rates in this study are comparable to return-to-play rates in other NCAA athletes, specifically collegiate football players who returned 63.6% to 91.43% depending on position [Citation8].
Our study also suggests that volleyball attackers (outside hitters, middle blockers, and opposite hitters) are far more likely to injure their ACL than their libero/defensive specialist and setter counterparts. Attackers are characterized as players who all perform the similar skill of jumping and spiking the ball near the net, whereas setters, liberos, and defensive specialists normally contribute by bumping and setting the ball with almost no spiking. Volleyball attackers comprised 78.8% of tears identified in our ACL tear group while only making up 54.7% of total players (6.0 players per team out of 10.9) in the control group. This finding is consistent with a previous study of professional volleyball players which demonstrated that ‘spikers’ and middle blockers accounted for 41.2% and 29.4%, respectively, of the 34 ACL injuries identified [Citation9].
Landing during volleyball activities appears to place volleyball players at most risk for ACL tears [Citation9]. Several studies have demonstrated that certain jumping and blocking techniques encountered during volleyball may subject knee to stresses associated with increased risk of ACL tears [Citation10]. Beardt et al. demonstrated that the jump landing mechanics observed during volleyball competition is different than traditional drop jump and may contribute to ACL tears [Citation11]. Landing with a low knee flexion angle [Citation12], step back landing [Citation13], and/or an unanticipated block with arms and trunk laterally tilted (as opposed to arms straight up from body) [Citation14] have been demonstrated to be risk factors for sustaining an ACL tear among volleyball players. Evidence suggests that neuromuscular training to improve landing techniques may improve landing biomechanics and improve performance among female volleyball players [Citation15–17].
The search utilized to gather our population was not designed to evaluate ACL re-injury rate. However, it is surprising no articles used to include players classified injuries as recurrence or identified contralateral injury, as it has been reported that the incidence of these is as high as 18% [Citation18]. Several factors may explain this finding. Firstly, competitive volleyball players are highly motivated to return to play and have athletic and strength trainers available for daily rehabilitation. Thus, the resources available to athletes sustaining these injuries likely led to a more robust rehabilitation protocol for the affected limb and potentially a regimen to decrease risk of injury in the unaffected limb. Conversely, the follow-up period that only included each player’s remaining seasons until graduation may have been too short to capture the true incidence of retears. Players may have continued professional or recreational play following their collegiate career and sustained unidentified re-njury or contralateral injury during this period.
This study has several limitations. First, the sampling method may not have captured all NCAA division 1 female volleyball players that sustained an ACL tear in the conferences studied because not all players that sustained ACL tears may have had articles written about their injury. The method favors more noteworthy players that are key contributors to the team. However, there is no readily accessible database to capture player-specific injury information on NCAA athletes across conferences. Our method has been previously published [Citation8]. Second, variations in treatment choices including surgical technique and graft choice could have contributed significantly to varying outcomes, especially with sample size of 99 cases. Athletes also may have pursued non-operative management, but we believe this choice is unlikely in an elite athlete. Third, statistical analyses were limited by sample sizes. The values and regression line merely provide averages and a visual tool for comparison purposes. Finally, the return-to-play rates in this study are confounded by seniors who did not return to play but may have had the opportunity for another year of eligibility. Because of the nature of the study, we were unable to ascertain the reason for failure to return to collegiate volleyball.
Despite these, this article provides useful information for the orthopedic surgeon, patients who are collegiate volleyball players, and coaches in terms of return-to-play metrics and expected performance changes. Studies with specific surgical details, such as surgical technique and concomitant injuries (e.g. meniscus), and rehabilitation protocols may provide further insight into variations seen.
Disclosure statement
The authors report there are no competing interests to declare.
Additional information
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References
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