G Model
ARTICLE IN PRESS
JSAMS-1032; No. of Pages 5
Journal of Science and Medicine in Sport xxx (2014) xxx–xxx
Contents lists available at ScienceDirect
Journal of Science and Medicine in Sport journal homepage: www.elsevier.com/locate/jsams
Original research
Time trends for injuries and illness, and their relation to performance in the National Basketball Association Leslie Podlog a,∗ , Craig F. Buhler b , Harvey Pollack c , Paul N. Hopkins d , Paul R. Burgess e a
Department of Exercise and Sport Science, University of Utah, United States Buhler Athletic Injuries & Human Performance Clinic, United States Philadelphia 76ers of the National Basketball Association, United States d Cardiovascular Genetics, University of Utah School of Medicine, United States e Department of Physical Therapy, University of Utah, United States b c
a r t i c l e
i n f o
Article history: Received 6 December 2013 Received in revised form 2 March 2014 Accepted 11 May 2014 Available online xxx Keywords: Games missed Injury reporting Team performance Collective bargaining agreement
a b s t r a c t Objectives: To survey injury/illness in the National Basketball Association over a 25-year period and examine the relationship of injury/illness to team performance. Design: A retrospective correlational design. Methods: Trends were examined in reported numbers of players injured/ill during a season and games missed due to injury/illness from seasons ending in 1986 through 2005. This period was compared to years 2006–2010, when NBA teams were allowed to increase the total number of players on the team from 12 to 15. Results: There was a highly significant trend (p < 0.0001) of increasing numbers of players injured/ill and games missed from 1986 through 2005. After the team expansion in 2006, these rates fell abruptly by 13% and 39% respectively (both p < 0.0001 compared to the previous 5-year period). We also found a significant inverse association between games missed due to injury/illness and percent games won (r = −0.29, p < 0.0001). Conclusions: Results demonstrate an increased rate of injury in the National Basketball Association up until the expansion of team size in 2006. Following 2006, team expansion was positively associated with decreased injury/illness rates. The latter finding suggests the importance of maintaining a healthy roster with respect to winning outcomes. © 2014 Published by Elsevier Ltd on behalf of Sports Medicine Australia.
1. Introduction The National Basketball Association (NBA) is one of the most popular professional sports leagues in the United States and beyond. Given the physical nature of play in the NBA, injury is likely a common occurrence. Surprisingly, a search of relevant databases revealed minimal research examining injury time trends in the NBA. Evidence of injury rates among basketball players at other levels1–4 suggests that injury may also be prevalent at the highest level of the game. As injury rates likely have implications for team success, knowledge of the extent of injury occurrence is important. Furthermore, data on injury rates is also relevant for identifying potential NBA teams where injury prevention initiatives may
∗ Corresponding author. E-mail address: [email protected] (L. Podlog).
be important and for enabling comparisons between injury rates occurring at different time periods in the league. In one of the few epidemiological studies of injury in the NBA, Starkey5 examined the number of players injured/ill for the 10 seasons ending in 1989 to 1998. There was no significant trend over this time period. Orchard and Hayes6 also examined NBA-player injury rates during the 1999–2000 and 2000–2001 seasons using data posted on several websites. The researchers found that the true injury prevalence among NBA players in season 1999–2000 averaged at least 12% and the average injury prevalence was higher among the bench players (15.1%) than the 5 designated starting players (12.4%). The researchers speculated that some of the reported injuries to bench players might have been spurious and were possibly cited for the purpose of creating space on the 12-man roster. Given the dearth of epidemiological data on injury rates within the NBA, the lack of readily verifiable indices of injury/illness, the relatively short time-frames examined, and the absence of data
http://dx.doi.org/10.1016/j.jsams.2014.05.005 1440-2440/© 2014 Published by Elsevier Ltd on behalf of Sports Medicine Australia.
Please cite this article in press as: Podlog L, et al. Time trends for injuries and illness, and their relation to performance in the National Basketball Association. J Sci Med Sport (2014), http://dx.doi.org/10.1016/j.jsams.2014.05.005
G Model
ARTICLE IN PRESS
JSAMS-1032; No. of Pages 5
L. Podlog et al. / Journal of Science and Medicine in Sport xxx (2014) xxx–xxx
2
demonstrating the potential implications of injury for team success, it is apparent that further research is needed. To address the limited number of years examined in previous NBA research and to provide a more current picture of injury trends, the focus of the present investigation was to examine trends in player injury rates and reported illnesses over the past 25 years. Specifically, the study was guided by four questions: were there substantial changes in: (1) the number of players in the NBA who were injured or ill during the regular 82-game season, (2) the number of player-games missed during this time, and (3) the average number of games missed per player after an injury or illness? Finally, we also examined whether there was any relationship between injury/illness and the percentage of games won during a particular season? We hypothesized that injury and illness would decline over time due to health-care improvements and better training methods. We also hypothesized an inverse relationship between injury/illness and the percentage of games won during a particular season. 2. Methods The number of injured/ill players on each NBA team and games missed were obtained from archival data, specifically the annual Statistical Yearbooks prepared by one of the authors (HP) and his staff at the Philadelphia 76ers and from records kept by STATS Inc., in Northbrook, Illinois. For purposes of this study, we will refer to each season by its ending year. Following submission of the present study for IRB approval (IRB number 00069593), the IRB committee determined that the study “does NOT meet the definitions of Human Subjects Research according to Federal regulations. Therefore, IRB oversight is not required or necessary for your project.” The study was conducted in accord with institutional and American College of Sports Medicine (ACSM) ethical guidelines.
Consistent with the official NBA definition of an injury, a player was considered to be injured/ill if he missed one or more games during the 82-game regular season. A distinction between injury versus illness or the specific nature of the injury or illness was not available for further analysis. Only summary data for the number of players so affected for a team in a given season was available for analysis (rather than individual-player data). If the player missed games with two or more teams, the first team was assigned the player injury/illness. The total number of games missed during the regular season due to injury or illness by individual team players, or “player-games missed”, was also obtained. An index of severity of injury/illness was obtained by dividing player-games missed by players injured/ill. Finally, we collected percent of games won during the regular season, a widely available statistic, as our index of team performance. During the 1999 season, the number of games played was 50, rather than 82, because of a contract dispute. The number of playergames missed during this season was multiplied by 82/50 to make it comparable to an 82-game season. A similar correction was not made for the number of players injured/ill, since only a single game missed assigned the player to the injured/ill group and the correction appeared to over-inflate the estimate. Data were organized such that each line of data contained observations for one team during one season (observations included team, year, number of players missing any game due to injury or illness, number of games missed due to injury or illness, number of games missed per injured/ill player, and percent wins for the season). Thus, each team could contribute one observation for each year. For purposes of description, simple means and 95%confidence intervals (averaged over all teams) for each year are provided for each index of injury in Figs. 1–3. Formal hypothesis testing of the significance of the team expansion effect was
16 p for trend < 0.0001
14
p < 0.0001 vs prior years
Players injured/ill
12 10 8 6 4 2 0
Period One
Period Two
Period Three
Period Four
Period Five
Season ending year Fig. 1. Shown are simple means and 95% CI averaged over all teams for players injured or ill (missing at least one game in the regular season due to injury or illness). The p-values were generated by a random effects model which simultaneously tested the significance of the trend over all years (with “year” being treated as a continuous variable) and the team-expansion effect (treated as class or “yes/no” variable). Both effects were significant at p < 0.0001. The random effects model takes into account the correlation within team for year to year data as well as the variability introduced by having multiple teams contributing data. The difference in rates, simply comparing the 5 expansion years versus the prior 5 years, was also significant at p < 0.0001.
Please cite this article in press as: Podlog L, et al. Time trends for injuries and illness, and their relation to performance in the National Basketball Association. J Sci Med Sport (2014), http://dx.doi.org/10.1016/j.jsams.2014.05.005
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ARTICLE IN PRESS
JSAMS-1032; No. of Pages 5
L. Podlog et al. / Journal of Science and Medicine in Sport xxx (2014) xxx–xxx
3
300 p < 0.0001 vs prior years
p for trend < 0.0001
Player-games missed
250
200
150
100
50
0 Period One
Period Two
Period Three
Period Four
Period Five
Season ending year Fig. 2. Shown are player-games missed analyzed and presented as in Fig. 1.
performed using a random effects model in which each team was considered as a random effect, thereby taking into consideration the within-team correlation and the variability introduced by separate teams contributing data each year. Virtually identical results were obtained in a repeated measures analysis of variance model with team treated as both a random and repeated effect. In these analyses, team expansion (years 2006–2010) was treated as a separate dummy variable (0, 1), while year was treated as a continuous variable to account for and to test the significance of the trend in injury rates prior to the team expansion. All analyses were performed with SAS statistical software (Cary, NC), version 9.3. Descriptive statistics were generated using PROC GLM. Random effects and repeated measures models were tested using the PROC MIXED package in SAS. 3. Results The raw data collected for each team, which was used for all analyses, are available in the supplementary files (Tables 1–3). As shown in Fig. 1, there was a highly significant trend (p < 0.0001) for increasing numbers of injured/ill players from 1986 to 2005. In 2006 there was an abrupt decline, which persisted thereafter. It was at this time that the total number of players who could be on an NBA team increased from 12 to 15, although the game-day roster remained at 12. The effect of the team expansion on players injured/ill was highly significant (p < 0.0001) in a random effects model that included year as a continuous variable, and that considered teams as a random effect. This approach allows a statistically unbiased, formal testing of the hypothesis that team expansion had a significant effect by using a single model that takes into consideration the expected trend in injury/illness over the years of observation as well as the correlation of data within teams together with the variability between teams. To illustrate the magnitude of these changes, the 25 seasons covered by this analysis can be viewed as five periods of 5 seasons each. There was a 32% increase in the number of players injured/ill from 1986–1990 (i.e., period one; mean ± SE = 9.13 ± 0.28) to 2000–2005
(i.e., period four; 12.09 ± 0.26, p < 0.0001). After the team expansion, there was a 13% decrease to a mean of 10.47 ± 0.26 (p < 0.0001 versus the prior 5-year period, 2000–2005). Nevertheless, the number of players injured/ill after the team expansion remained 15% higher than from 1986 to 1990 (i.e., during period one, p < 0.0001). These statistically informal analyses were performed by simply pooling all observations from all teams for each of these time periods without taking into consideration the correlation of observations within teams or the variability between teams. In Fig. 2, player-games missed is seen to increase steeply from 1986 to 2005 (p for trend
ARTICLE IN PRESS
JSAMS-1032; No. of Pages 5
Journal of Science and Medicine in Sport xxx (2014) xxx–xxx
Contents lists available at ScienceDirect
Journal of Science and Medicine in Sport journal homepage: www.elsevier.com/locate/jsams
Original research
Time trends for injuries and illness, and their relation to performance in the National Basketball Association Leslie Podlog a,∗ , Craig F. Buhler b , Harvey Pollack c , Paul N. Hopkins d , Paul R. Burgess e a
Department of Exercise and Sport Science, University of Utah, United States Buhler Athletic Injuries & Human Performance Clinic, United States Philadelphia 76ers of the National Basketball Association, United States d Cardiovascular Genetics, University of Utah School of Medicine, United States e Department of Physical Therapy, University of Utah, United States b c
a r t i c l e
i n f o
Article history: Received 6 December 2013 Received in revised form 2 March 2014 Accepted 11 May 2014 Available online xxx Keywords: Games missed Injury reporting Team performance Collective bargaining agreement
a b s t r a c t Objectives: To survey injury/illness in the National Basketball Association over a 25-year period and examine the relationship of injury/illness to team performance. Design: A retrospective correlational design. Methods: Trends were examined in reported numbers of players injured/ill during a season and games missed due to injury/illness from seasons ending in 1986 through 2005. This period was compared to years 2006–2010, when NBA teams were allowed to increase the total number of players on the team from 12 to 15. Results: There was a highly significant trend (p < 0.0001) of increasing numbers of players injured/ill and games missed from 1986 through 2005. After the team expansion in 2006, these rates fell abruptly by 13% and 39% respectively (both p < 0.0001 compared to the previous 5-year period). We also found a significant inverse association between games missed due to injury/illness and percent games won (r = −0.29, p < 0.0001). Conclusions: Results demonstrate an increased rate of injury in the National Basketball Association up until the expansion of team size in 2006. Following 2006, team expansion was positively associated with decreased injury/illness rates. The latter finding suggests the importance of maintaining a healthy roster with respect to winning outcomes. © 2014 Published by Elsevier Ltd on behalf of Sports Medicine Australia.
1. Introduction The National Basketball Association (NBA) is one of the most popular professional sports leagues in the United States and beyond. Given the physical nature of play in the NBA, injury is likely a common occurrence. Surprisingly, a search of relevant databases revealed minimal research examining injury time trends in the NBA. Evidence of injury rates among basketball players at other levels1–4 suggests that injury may also be prevalent at the highest level of the game. As injury rates likely have implications for team success, knowledge of the extent of injury occurrence is important. Furthermore, data on injury rates is also relevant for identifying potential NBA teams where injury prevention initiatives may
∗ Corresponding author. E-mail address: [email protected] (L. Podlog).
be important and for enabling comparisons between injury rates occurring at different time periods in the league. In one of the few epidemiological studies of injury in the NBA, Starkey5 examined the number of players injured/ill for the 10 seasons ending in 1989 to 1998. There was no significant trend over this time period. Orchard and Hayes6 also examined NBA-player injury rates during the 1999–2000 and 2000–2001 seasons using data posted on several websites. The researchers found that the true injury prevalence among NBA players in season 1999–2000 averaged at least 12% and the average injury prevalence was higher among the bench players (15.1%) than the 5 designated starting players (12.4%). The researchers speculated that some of the reported injuries to bench players might have been spurious and were possibly cited for the purpose of creating space on the 12-man roster. Given the dearth of epidemiological data on injury rates within the NBA, the lack of readily verifiable indices of injury/illness, the relatively short time-frames examined, and the absence of data
http://dx.doi.org/10.1016/j.jsams.2014.05.005 1440-2440/© 2014 Published by Elsevier Ltd on behalf of Sports Medicine Australia.
Please cite this article in press as: Podlog L, et al. Time trends for injuries and illness, and their relation to performance in the National Basketball Association. J Sci Med Sport (2014), http://dx.doi.org/10.1016/j.jsams.2014.05.005
G Model
ARTICLE IN PRESS
JSAMS-1032; No. of Pages 5
L. Podlog et al. / Journal of Science and Medicine in Sport xxx (2014) xxx–xxx
2
demonstrating the potential implications of injury for team success, it is apparent that further research is needed. To address the limited number of years examined in previous NBA research and to provide a more current picture of injury trends, the focus of the present investigation was to examine trends in player injury rates and reported illnesses over the past 25 years. Specifically, the study was guided by four questions: were there substantial changes in: (1) the number of players in the NBA who were injured or ill during the regular 82-game season, (2) the number of player-games missed during this time, and (3) the average number of games missed per player after an injury or illness? Finally, we also examined whether there was any relationship between injury/illness and the percentage of games won during a particular season? We hypothesized that injury and illness would decline over time due to health-care improvements and better training methods. We also hypothesized an inverse relationship between injury/illness and the percentage of games won during a particular season. 2. Methods The number of injured/ill players on each NBA team and games missed were obtained from archival data, specifically the annual Statistical Yearbooks prepared by one of the authors (HP) and his staff at the Philadelphia 76ers and from records kept by STATS Inc., in Northbrook, Illinois. For purposes of this study, we will refer to each season by its ending year. Following submission of the present study for IRB approval (IRB number 00069593), the IRB committee determined that the study “does NOT meet the definitions of Human Subjects Research according to Federal regulations. Therefore, IRB oversight is not required or necessary for your project.” The study was conducted in accord with institutional and American College of Sports Medicine (ACSM) ethical guidelines.
Consistent with the official NBA definition of an injury, a player was considered to be injured/ill if he missed one or more games during the 82-game regular season. A distinction between injury versus illness or the specific nature of the injury or illness was not available for further analysis. Only summary data for the number of players so affected for a team in a given season was available for analysis (rather than individual-player data). If the player missed games with two or more teams, the first team was assigned the player injury/illness. The total number of games missed during the regular season due to injury or illness by individual team players, or “player-games missed”, was also obtained. An index of severity of injury/illness was obtained by dividing player-games missed by players injured/ill. Finally, we collected percent of games won during the regular season, a widely available statistic, as our index of team performance. During the 1999 season, the number of games played was 50, rather than 82, because of a contract dispute. The number of playergames missed during this season was multiplied by 82/50 to make it comparable to an 82-game season. A similar correction was not made for the number of players injured/ill, since only a single game missed assigned the player to the injured/ill group and the correction appeared to over-inflate the estimate. Data were organized such that each line of data contained observations for one team during one season (observations included team, year, number of players missing any game due to injury or illness, number of games missed due to injury or illness, number of games missed per injured/ill player, and percent wins for the season). Thus, each team could contribute one observation for each year. For purposes of description, simple means and 95%confidence intervals (averaged over all teams) for each year are provided for each index of injury in Figs. 1–3. Formal hypothesis testing of the significance of the team expansion effect was
16 p for trend < 0.0001
14
p < 0.0001 vs prior years
Players injured/ill
12 10 8 6 4 2 0
Period One
Period Two
Period Three
Period Four
Period Five
Season ending year Fig. 1. Shown are simple means and 95% CI averaged over all teams for players injured or ill (missing at least one game in the regular season due to injury or illness). The p-values were generated by a random effects model which simultaneously tested the significance of the trend over all years (with “year” being treated as a continuous variable) and the team-expansion effect (treated as class or “yes/no” variable). Both effects were significant at p < 0.0001. The random effects model takes into account the correlation within team for year to year data as well as the variability introduced by having multiple teams contributing data. The difference in rates, simply comparing the 5 expansion years versus the prior 5 years, was also significant at p < 0.0001.
Please cite this article in press as: Podlog L, et al. Time trends for injuries and illness, and their relation to performance in the National Basketball Association. J Sci Med Sport (2014), http://dx.doi.org/10.1016/j.jsams.2014.05.005
G Model
ARTICLE IN PRESS
JSAMS-1032; No. of Pages 5
L. Podlog et al. / Journal of Science and Medicine in Sport xxx (2014) xxx–xxx
3
300 p < 0.0001 vs prior years
p for trend < 0.0001
Player-games missed
250
200
150
100
50
0 Period One
Period Two
Period Three
Period Four
Period Five
Season ending year Fig. 2. Shown are player-games missed analyzed and presented as in Fig. 1.
performed using a random effects model in which each team was considered as a random effect, thereby taking into consideration the within-team correlation and the variability introduced by separate teams contributing data each year. Virtually identical results were obtained in a repeated measures analysis of variance model with team treated as both a random and repeated effect. In these analyses, team expansion (years 2006–2010) was treated as a separate dummy variable (0, 1), while year was treated as a continuous variable to account for and to test the significance of the trend in injury rates prior to the team expansion. All analyses were performed with SAS statistical software (Cary, NC), version 9.3. Descriptive statistics were generated using PROC GLM. Random effects and repeated measures models were tested using the PROC MIXED package in SAS. 3. Results The raw data collected for each team, which was used for all analyses, are available in the supplementary files (Tables 1–3). As shown in Fig. 1, there was a highly significant trend (p < 0.0001) for increasing numbers of injured/ill players from 1986 to 2005. In 2006 there was an abrupt decline, which persisted thereafter. It was at this time that the total number of players who could be on an NBA team increased from 12 to 15, although the game-day roster remained at 12. The effect of the team expansion on players injured/ill was highly significant (p < 0.0001) in a random effects model that included year as a continuous variable, and that considered teams as a random effect. This approach allows a statistically unbiased, formal testing of the hypothesis that team expansion had a significant effect by using a single model that takes into consideration the expected trend in injury/illness over the years of observation as well as the correlation of data within teams together with the variability between teams. To illustrate the magnitude of these changes, the 25 seasons covered by this analysis can be viewed as five periods of 5 seasons each. There was a 32% increase in the number of players injured/ill from 1986–1990 (i.e., period one; mean ± SE = 9.13 ± 0.28) to 2000–2005
(i.e., period four; 12.09 ± 0.26, p < 0.0001). After the team expansion, there was a 13% decrease to a mean of 10.47 ± 0.26 (p < 0.0001 versus the prior 5-year period, 2000–2005). Nevertheless, the number of players injured/ill after the team expansion remained 15% higher than from 1986 to 1990 (i.e., during period one, p < 0.0001). These statistically informal analyses were performed by simply pooling all observations from all teams for each of these time periods without taking into consideration the correlation of observations within teams or the variability between teams. In Fig. 2, player-games missed is seen to increase steeply from 1986 to 2005 (p for trend
