We sought to quantify head impact frequency and location for individual players on 3 collegiate football teams during a single season. We focused on these 2 measures of head impact exposure because of the lack of data on individual exposures and on concussion injury mechanisms. To date, the only reported exposure measure for individual players is the risk of injury through participation defined using A-E.13
Although A-E is a useful factor for comparing the risk of injury across sports, sex, and other environmental factors, it has limited applicability to the study of injury mechanisms.
The ability to directly measure head impacts of individual players is critical to establishing the relationship between head impacts and concussion injury and to examining the potential effects of cumulative subconcussive impacts. Only a few of the 188 players enrolled in our study received an impact in all team practices and games. More typically, head impacts occurred in approximately one-half to two-thirds of the team sessions. Head impact frequency recorded over the entire season for practices and games varied by team. This was not unexpected given that players on 1 team had substantially more practice sessions, but this team also had the lowest median number of average impacts per practice. Although the number of team sessions certainly influenced the number of individual head impacts, the structure of the practice plan and the philosophies of the coaching staff also were likely factors that were difficult to quantify. Interestingly, the number of impacts a player received per game did not vary by team. We presume this is because of the controlled and timed nature of football games, which are less dependent on a team's style of play or specific practice tendencies. The total numbers of impacts players received during all practices and all games were comparable (); however, after accounting for the number of sessions of each, the number of impacts per game was 2 to 3 times greater than the number of impacts per practice, which was consistent with the reported findings that injury rates are higher in games than in practices.27
The number of impacts recorded per practice and per game for an individual player reached maximums of 24 and 86.1, respectively. The median values for these players were 6.3 impacts per practice and 14.3 impacts per game. For some individual players, the values that we recorded might be underestimates of the actual impacts because a player might have started a practice or game but might not have completed the session and because we were not able to instrument all players on each team.
Researchers have not reported head impact measures for individual players, so direct comparison with our data is limited but instructive. Using an earlier version of the instrumented helmet technology, Duma et al25
reported 2114 impacts in 35 practices while monitoring 38 different players (up to 8 players per session), giving a value of approximately 7.6 impacts per player per practice. In 10 games, they recorded 1198 impacts, for an estimated 15.0 impacts per player per game. Brolinson et al23
604 impacts over 84 sessions of games and practices. During each session, they monitored up to 18 players, with 52 different players wearing the instrumented helmets over the 2-season period. From their results, we estimate that the average number of impacts per player per session was approximately 4, which would be in the lower 20% of the 188 players from our study. However, this prediction of impacts per player per session likely is an underestimate considering that 18 players were not instrumented each day for the entire study. Using similar technology, Schnebel et al22
154 impacts for 40 players over 105 sessions at 1 NCAA Division I school during 1 season. Their overall average number of player head impacts per session was approximately 13, which was greater than our median value of 9.4 impacts per player per session. Mihalik et al24
reported that the total number of impacts sustained in full-contact practice (28
610) was about twice the number of those sustained in games (12
873). This ratio is roughly consistent with our findings.
We found that player position affected both head impact frequency and location. Other researchers have suggested similar trends. Schnebel et al22
reported that their nonlinemen (“skill positions”) received only 25% of the total impacts, in contrast to linemen, who received 75% of the total impacts. In another study of 1 collegiate football team over 2 seasons, the largest percentages of impacts were recorded in OFs (36%) and DLs (22%),24
which is consistent with our findings. In that study, LBs received only one-third of the impacts that the linemen received, whereas in our study, DLs, OLs, and LBs received approximately the same number of impacts per practice and per game.
We found that most impacts occurred to the front of the helmet for all player positions except QBs. The OLs had the highest percentage of impacts to the front of the helmet, which is consistent with the observation that OLs are more likely to initiate and control the site of impact than other position groups. The highest percentage of impacts to the back of the helmet occurred in QBs, suggesting that the QBs most often were hit from behind or were tackled, falling backward and hitting the backs of their heads on the ground. These explanations are based upon general observation of football and have not been confirmed by video analysis. Mihalik et al24
did not examine impact location by player position, but their overall results on impact location are in general agreement with our findings for all players.
We focused our analysis on head impact frequency and impact location for individual players. We chose this focus because this analysis for individual players has not been reported and the resulting data are crucial in establishing baseline exposures for the mechanism and the risk of concussion injury, as well as any risk of cumulative subconcussive injury. Accordingly, a substantial number of data from our project were not reported in this study. The severity (magnitude) of the linear and rotational acceleration and the duration of head acceleration during impacts were not reported because these are the subject of an ongoing analysis of specific biomechanical input variables and their relationship to symptoms and cognitive function. In addition, cumulative measures of head impacts have not been formulated and, hence, were not included in this analysis. We did not report concussion injuries or any measure of long-term cognitive deficits. Our study also was limited to 3 teams during a single football season. Our multiyear study is ongoing, and we will analyze any differences among seasons as the study continues. We selected a lower range cutoff of 10g of peak linear acceleration of the head for inclusion as an impact to be consistent with data-collection thresholds across the 3 test sites. Given the size of the data set and number of levels of within-subjects (5 [location] × 2 [activity]) and between-subjects (3 [team]) factors, not all sources of heterogeneity of variance could be tested in our statistical analyses. Although we believe that the numbers of samples would minimize this effect, heterogeneity of variance across some factors could affect the mixed-model analyses.
Head impact in sports continues to be an important and growing concern at all levels of football and other sports because of the known adverse outcomes in some cases and the potential for long-term detrimental cognitive effects. The exact mechanisms for and variability of concussion signs, symptoms, and long-term sequelae from head impacts, particularly in helmeted sports, are not well understood. Few data address possible differences in mechanisms and susceptibilities among athletes of different ages, including children, and between sexes. Estimates of concussion injury thresholds based on laboratory reconstructions using animal, cadaver, and manikin surrogates15,28,29
have been inadequately predictive of injury when compared with measurements of actual head acceleration.26
To appropriately evaluate the risk of concussion injury and the potential for interventions likely to reduce the incidence of concussions in sports, as well as the potential role of accumulated subconcussive events, a detailed understanding of the exposure and the mechanism of injury is needed. Using animal models, researchers have suggested that multiple factors likely influence the risk of neurologic and somatic symptoms after concussive head impacts and that these might include previous head impact events, location or direction of head impact, and other mechanical and physiologic factors.7–,12
The data that we presented begin this process of quantifying head impact exposure in collegiate football players by focusing on head impact frequency and location.