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Many head acceleration events (HAEs) observed in youth football emanate from a practice environment. This study aimed to evaluate HAEs in youth football practice drills using a mouthpiece-based sensor, differentiating between inertial and direct HAEs. Head acceleration data were collected from athletes participating on 2 youth football teams (ages 11–13 y) using an instrumented mouthpiece-based sensor during all practice sessions in a single season. Video was recorded and analyzed to verify and assign HAEs to specific practice drill characteristics, including drill intensity, drill classification, and drill type. HAEs were quantified in terms of HAEs per athlete per minute and peak linear and rotational acceleration and rotational velocity. Mixed-effects models were used to evaluate the differences in kinematics, and generalized linear models were used to assess differences in HAE frequency between drill categories. A total of 3237 HAEs were verified and evaluated from 29 football athletes enrolled in this study. Head kinematics varied significantly between drill categorizations. HAEs collected at higher intensities resulted in significantly greater kinematics than lower-intensity drills. The results of this study add to the growing body of evidence informing evidence-based strategies to reduce head impact exposure and concussion risk in youth football practices.

Soccer, one of the most popular sports in the world, has one of the highest rates of sports-related concussions. Additionally, soccer players are frequently exposed to nonconcussive impacts from intentionally heading the ball, a fundamental component of the sport. There have been many studies on head impact exposure in soccer, but few focus on soccer practices or practice activities. This study aimed to characterize the frequency and magnitude of head impacts in National Collegiate Athletic Association Division I female soccer practice activities using a custom-fit instrumented mouthpiece. Sixteen players were instrumented over the course of 54 practice sessions. Video analysis was performed to verify all mouthpiece-recorded events and classify practice activities. Category groupings of practice activities include technical training, team interaction, set pieces, position-specific, and other. Differences in head impact rates and peak resultant kinematics were observed across activity types and category groupings. Technical training had the highest impact rate compared to other category groupings. Impacts occurring during set piece activities had the highest mean kinematic values. Understanding drill exposure can help inform coaches on training plans aimed to reduce head impact exposure for their athletes.

The objective of this study was to utilize an instrumented mouthpiece sensor to characterize head kinematics experienced by grassroots dirt track race car drivers.Four dirt track race car drivers (ages 16-19) were instrumented with custom mouthpiece sensors capable of accurately measuring head motion during racing. Sensors were deployed before races and recorded tri-axial linear acceleration and rotational velocity for approximately 10 min at 200 Hz. Film review was performed to identify data associated with racing laps. For each lap, moving average kinematics were computed and subtracted from the head motion signals to obtain 'adjusted' head motion accounting for lower frequency variance due to periodic motion around the track. From adjusted data, linear and angular head perturbations (i.e., deviations from moving average) were extracted using a custom algorithm.Data was collected during 400 driver-races. A total of 2438 laps were segmented from mouthpiece recordings. The median (95th percentile) peak linear acceleration, rotational velocity, and rotational acceleration of all laps were 5.33 (8.28) g, 2.89 (4.60) rad/s, and 179 (310) rad/sMouthpiece sensors can be used to measure head kinematics during active racing. Laps, head perturbations, and crashes may be useful units of observation to describe typical head kinematic exposure experienced by drivers while racing. Subsequent research is needed to understand the associations between repetitive racing exposure and neurological function. Higher magnitude events (i.e., crashes) are not uncommon and may result in concussion or more severe injury. Results represent novel characterizations of head kinematic exposure experienced in a dirt track racing environment. This information may inform evidence-based strategies (e.g., vehicle/seat design) to improve driver safety.

Approximately 3.5 million youth and adolescents in the US play football, a sport with one of the highest rates of concussion. Repeated subconcussive head impact exposure (HIE) may lead to negative neurological sequelae. To understand HIE as an independent predictive variable, quantitative cumulative kinematic metrics have been developed to capture the volume (i.e., number), severity (i.e., magnitude), and frequency (i.e., time-weighting by the interval between head impacts). In this study, time-weighted cumulative HIE metrics were compared with directional changes in diffusion tensor imaging (DTI) metrics. Changes in DTI conducted on a per-season, per-player basis were assessed as a dependent variable. Directional changes were defined separately as increases and decreases in the number of abnormal voxels relative to non-contact sport controls. Biomechanical and imaging data from 117 athletes (average age 11.9 ± 1.0 years) enrolled in this study was analyzed. Cumulative HIE metrics were more strongly correlated with increases in abnormal voxels than decreases in abnormal voxels. Additionally, across DTI sub-measures, increases and decreases in mean diffusivity (MD) had the strongest relationships with HIE metrics (increases in MD: average R(2) = 0.1753, average p = 0.0002; decreases in MD: average R(2) = 0.0997, average p = 0.0073). This encourages further investigation into the physiological phenomena represented by directional changes.

The goal of this work was to collect on-track driver head kinematics using instrumented mouthpieces and characterize environmental exposure to accelerations and vibrations. Six NASCAR drivers were instrumented with custom-fit mouthpieces to collect head kinematic data. Devices were deployed at four tracks during practice and testing environments and configured to collect approximately 11 min of linear acceleration and rotational velocity data at 200 Hz. This continuous data collection, combined with film review, allowed extraction of complete laps of data. In addition to typical data processing methods, a moving-point average was calculated and subtracted from the overall signal for both linear acceleration and rotational velocity to determine the environmental component of head motion. The current analysis focuses on 42 full laps of data collected at four data collection events. The number of laps per track ranged from 2 to 23. Linear acceleration magnitudes for all 42 laps ranged from 2.46 to 7.48 g and rotational velocity ranged from 1.25 to 3.35 rad/s. After subtracting the moving average, linear acceleration ranged from 0.92 to 5.45 g and rotational velocity ranged from 0.57 to 2.05 rad/s. This study has established the feasibility of using an instrumented mouthpiece to measure head kinematics in NASCAR and presented a technique for isolating head motion due to cornering acceleration from those due to short-term perturbations experienced by the driver.

Understanding characteristics of head acceleration events (HAEs) in youth football is vital in developing strategies to improve athlete safety. This study aimed to characterize HAEs in youth football using an instrumented mouthpiece. Youth football athletes (ages 11-13) participating on two teams were enrolled in this study for one season. Each athlete was instrumented with a mouthpiece-based sensor throughout the season. HAEs were verified on film to ensure that mouthpiece-based sensors triggered during contact. The number of HAEs, peak resultant linear and rotational accelerations, and peak resultant rotational velocity were quantified. Mixed effects models were used to evaluate differences in mean kinematic metrics among all HAEs for session type, athlete position, and contact surface. A total of 5,292 HAEs were collected and evaluated from 30 athletes. The median (95th percentile) peak resultant linear acceleration, rotational acceleration, and rotational velocity was 9.5 g (27.0 g), 666.4 rad s

With the concern of concussion risk and repetitive head impacts in youth football, organizations have adopted rules that limit contact during practice. However, rule changes are not ubiquitous among organizations and are challenging to monitor and enforce. Ultimately, football practice activities are determined by coaches, but it is unknown whether providing objective data to coaches relating activities to their athletes' head impact exposure (HIE) would alter practice structure or help reduce HIE. This study evaluated the effect of coach awareness of HIE on practice structure over time. Head impact data from three intervention (56 players) and three control (38 players) teams were collected over two youth football seasons. Athletes were instrumented with the Head Impact Telemetry (HIT) System and time-synchronized video was recorded for practices and games. Impact frequencies and head accelerations were compiled into weekly HIE practice and game reports and shared with the head coach of each intervention team. Time per drill, impact rate, and impact magnitude were compared across three time frames (pre-season, mid-season, and late-season) using generalized linear models. Control teams had higher impact rates than intervention teams in all drills across time frames. Among all teams, 95th percentile linear and rotational accelerations were highest during mid-season. Among intervention teams, more time was spent on scrimmage and skill development from pre-season to late-season, with less time spent on tackling. This study suggests that receiving objective data informing HIE in practice may contribute to changes in practice structure and help inform intervention efforts to improve head impact safety in football.

To reduce head impact exposure (HIE) in youth football, further understanding of the context in which head impacts occur and the associated biomechanics is needed. The objective of this study was to evaluate the effect of contact characteristics on HIE during player versus player contact scenarios in youth football. Head impact data and time-synchronized video were collected from 4 youth football games over 2 seasons in which opposing teams were instrumented with the Head Impact Telemetry (HIT) System. Coded contact characteristics included the player’s role in the contact, player speed and body position, contact height, type, and direction, and head contact surface. Head accelerations were compared among the contact characteristics using mixed-effects models. Among 72 instrumented athletes, 446 contact scenarios (n = 557 impacts) with visible opposing instrumented players were identified. When at least one player had a recorded impact, players who were struck tended to have higher rotational acceleration than players in striking positions. When both players had a recorded impact, lighter players and taller players experienced higher mean head accelerations compared with heavier players and shorter players. Understanding the factors influencing HIE during contact events in football may help inform methods to reduce head injury risk.

The relationship between head impact and subsequent brain injury for American football players is not well-defined, especially for youth. The objective of this study is to quantify and assess Head Impact Exposure (HIE) metrics among youth and collegiate football players. This multi-season study enrolled 639 unique athletes (354 collegiate; 285 youth, ages 9-14), recording 476,209 head impacts (367,337 collegiate; 108,872 youth) over 971 sessions (480 collegiate; 491 youth). Youth players experienced 43% and 65% fewer impacts per competition and practice, respectively, and lower impact magnitudes compared to collegiate players (95(th) percentile peak linear acceleration (PLA, g) competition: 45.6 vs 61.9; 95(th) percentile PLA practice: 42.6 vs 58.8; 95(th) percentile peak rotational acceleration (PRA, rads·(−2)) competition: 2262 vs 4422; 95(th) percentile PRA practice: 2081 vs 4052; 95(th) percentile HITsp competition: 25.4 vs 32.8; 95(th) percentile HITsp practice: 23.9 vs 30.2). Impacts during competition were more frequent and of greater magnitude than during practice at both levels. Quantified comparisons of head impact frequency and magnitude between youth and collegiate athletes reveal HIE differences as a function of age, and expanded insight better informs the development of age-appropriate guidelines for helmet design, prevention measures, standardized testing, brain injury diagnosis, and recovery management.

Objectives:Head impact exposure (HIE) in youth football is a public health concern. The objective of this study was to determine if one season of HIE in youth football was related to cognitive changes.Method:Over 200 participants (ages 9–13) wore instrumented helmets for practices and games to measure the amount of HIE sustained over one season. Pre- and post-season neuropsychological tests were completed. Test score changes were calculated adjusting for practice effects and regression to the mean and used as the dependent variables. Regression models were calculated with HIE variables predicting neuropsychological test score changes.Results:For the full sample, a small effect was found with season average rotational values predicting changes in list-learning such that HIE was related to negative score change: standardized beta (β) = -.147, t(205) = -2.12, and p = .035. When analyzed by age clusters (9–10, 11–13) and adding participant weight to models, the R2 values increased. Splitting groups by weight (median split), found heavier members of the 9–10 cohort with significantly greater change than lighter members. Additionaly, significantly more participants had clinically meaningful negative changes: X2 = 10.343, p = .001.Conclusion:These findings suggest that in the 9–10 age cluster, the average seasonal level of HIE had inverse, negative relationships with cognitive change over one season that was not found in the older group. The mediation effects of age and weight have not been explored previously and appear to contribute to the effects of HIE on cognition in youth football players.

BACKGROUND AND PURPOSE: SWI is an advanced imaging modality that is especially useful in cerebral microhemorrhage detection. Such microhemorrhages have been identified in adult contact sport athletes, and the sequelae of these focal bleeds are thought to contribute to neurodegeneration. The purpose of this study was to utilize SWI to determine whether the prevalence and incidence of microhemorrhages in adolescent football players are significantly greater than those of adolescent noncontact athletes. MATERIALS AND METHODS: Preseason and postseason SWI was performed and evaluated on 78 adolescent football players. SWI was also performed on 27 adolescent athletes who reported no contact sport history. Two separate one-tailed Fisher exact tests were performed to determine whether the prevalence and incidence of microhemorrhages in adolescent football players are greater than those of noncontact athlete controls. RESULTS: Microhemorrhages were observed in 12 football players. No microhemorrhages were observed in any controls. Adolescent football players demonstrated a significantly greater prevalence of microhemorrhages than adolescent noncontact controls (P = .02). Although 2 football players developed new microhemorrhages during the season, microhemorrhage incidence during 1 football season was not statistically greater in the football population than in noncontact control athletes (P = .55). CONCLUSIONS: Adolescent football players have a greater prevalence of microhemorrhages compared with adolescent athletes who have never engaged in contact sports. While microhemorrhage incidence during 1 season is not significantly greater in adolescent football players compared to adolescent controls, there is a temporal association between playing football and the appearance of new microhemorrhages.

Soccer is a popular youth sport in the United States, but the effect of repetitive head impacts experienced during training on neurocognitive outcomes is not well understood. Modifying practice structure may be an avenue for reducing head impact exposure and concussion risk in soccer, but research has yet to characterize head impact exposure across common soccer activities. The objective of this study was to compare head impact exposure across common training activities in soccer. Eight female soccer players practicing on an age 15 and under (U15) club team participated in this study for two soccer seasons. Players wore an instrumented mouthpiece sensor during all practice and game sessions. Research personnel recorded duration of all activities performed by each player to characterize player-specific exposure time. Film review was performed to identify head contact events during each session and classify events according to the activity and drill the player was performing. Head impact exposure for each athlete was quantified in terms of peak kinematics and impact rate. Mixed effects models were used to compare peak kinematics and generalized linear models were used to compare impact rates across drills and activity type. Drill and activity type were associated with peak kinematics and impact rate. Technical training activities accounted for the second-highest exposure time and were associated with higher impact rates and lower mean kinematics than other activity types. Team interaction activities and game play were associated with the highest rotational kinematics but the lowest impact rates. Head impact exposure in female youth soccer is influenced by the type of activity in which the athlete is engaged. Interventions designed to reduce head impact frequency in female youth soccer can benefit from targeting technical training activities; whereas, interventions designed to reduce head impact magnitude should target team interaction and game activities.

Ice hockey has one of the highest concussion rates among youth sports. Sensor technology has been implemented in contact and collision sports to inform the frequency and severity of head impacts experienced on-ice. However, existing studies have utilized helmet-mounted sensors with limited accuracy. The objective of this study was to characterize head kinematics of contact events in a sample of youth boys' hockey players using a validated instrumented mouthpiece with improved accuracy. Head kinematics from 892 video-verified events were recorded from 18 athletes across 127 sessions. Median peak resultant linear acceleration, rotational velocity, and rotational acceleration of video-verified events were 7.4 g, 7.7 rad/s, and 576 rad/s2, respectively. Contact events occurred at a higher rate in games (2.48 per game) than practices (1.30 per practice). Scenarios involving head contact had higher peak kinematics than those without head contact. This study improves our understanding of head kinematics in boys' youth hockey.

Hockey is a fast-paced sport known for body checking, or intentional collisions used to separate opponents from the puck. Exposure to these impacts is concerning, as evidence suggests head impact exposure (HIE), even if noninjurious, can cause long-term brain changes. Currently, there is limited understanding of the effect of impact direction and collision speed on HIE. Video analysis was used to determine speed and direction for 162 collisions from 13 youth athletes. These data were paired with head kinematic data collected with an instrumented mouthpiece. Relationships between peak resultant head kinematics and speeds were evaluated with linear regression. Mean athlete speeds and relative velocity between athletes ranged from 2.05 to 2.76 m/s. Mean peak resultant linear acceleration, rotational velocity, and rotational acceleration were 13.1 g, 10.5 rad/s, and 1112 rad/s2, respectively. Significant relationships between speeds and head kinematics emerged when stratified by contact characteristics. HIE also varied by direction of collision; most collisions occurred in the forward-oblique (ie, offset from center) direction; frontal collisions had the greatest magnitude peak kinematics. These findings indicate that HIE in youth hockey is influenced by speed and direction of impact. This study may inform future strategies to reduce the severity of HIE in hockey.

The purpose of this study is to assess the relationship between regional white matter diffusion imaging changes and finite element strain measures in nonconcussed youth football players. Pre- and post-season diffusion-weighted imaging was performed in 102 youth football subject-seasons, in which no concussions were diagnosed. The diffusion data were normalized to the IXI template. Percent change in fractional anisotropy (%ΔFA) images were generated. Using data from the head impact telemetry system, the cumulative maximum principal strain one times strain rate (CMPS1 × SR), a measure of the cumulative tensile brain strain and strain rate for one season, was calculated for each subject. Two linear regression analyses were performed to identify significant positive or inverse relationships between CMPS1 × SR and %ΔFA within the international consortium for brain mapping white matter mask. Age, body mass index, days between pre- and post-season imaging, previous brain injury, attention disorder diagnosis, and imaging protocol were included as covariates. False discovery rate correction was used with corrected alphas of 0.025 and voxel thresholds of zero. Controlling for all covariates, a significant, positive linear relationship between %ΔFA and CMPS1 × SR was identified in the bilateral cingulum, fornix, internal capsule, external capsule, corpus callosum, corona radiata, corticospinal tract, cerebral and middle cerebellar peduncle, superior longitudinal fasciculus, and right superior fronto-occipital fasciculus. Post hoc analyses further demonstrated significant %ΔFA differences between high-strain football subjects and noncollision control athletes, no significant %ΔFA differences between low-strain subjects and noncollision control athletes, and that CMPS1 × SR significantly explained more %ΔFA variance than number of head impacts alone.

BACKGROUND AND PURPOSE: Magnetoencephalography is sensitive to functional connectivity changes associated with concussion. However, the directional influences between functionally related regions remain unexplored. In this study, we therefore evaluated concussion-related magnetoencephalography-based effective connectivity changes within resting-state default mode network regions. MATERIALS AND METHODS: Resting-state magnetoencephalography was acquired for 8 high school football players with concussion at 3 time points (preseason, postconcussion, postseason), as well as 8 high school football players without concussion and 8 age-matched controls at 2 time points (preseason, postseason). Time-series from the default mode network regions were extracted, and effective connectivity between them was computed for 5 different frequency bands. The default mode network regions were grouped into anterior and posterior default mode networks. The combined posterior-to-anterior and anterior-to-posterior effective connectivity values were averaged to generate 2 sets of values for each subject. The effective connectivity values were compared using a repeated measures ANOVA across time points for the concussed, nonconcussed, and control groups, separately. RESULTS: A significant increase in posterior-to-anterior effective connectivity from preseason to postconcussion (corrected P value = .013) and a significant decrease in posterior-to-anterior effective connectivity from postconcussion to postseason (corrected P value = .028) were observed in the concussed group. Changes in effective connectivity were only significant within the delta band. Anterior-to-posterior connectivity demonstrated no significant change. Effective connectivity in the nonconcussed group and controls did not show significant differences. CONCLUSIONS: The unidirectional increase in effective connectivity postconcussion may elucidate compensatory processes, invoking use of posterior regions to aid the function of susceptible anterior regions following brain injury. These findings support the potential value of magnetoencephalography in exploring directional changes of the brain network following concussion.

Various studies have characterized head kinematics in specific everyday activities by looking at linear and/or rotational acceleration characteristics, but each has evaluated a limited number of activities. Furthermore, these studies often present dissimilar and sometimes incomplete descriptions of the resulting kinematics, so the characteristics of normal everyday activities as a whole are not easily collectively summarized. The purpose of this study was to evaluate the literature investigating head kinematics associated with everyday activities and to generate a comprehensive kinematic boundary envelope describing these motions. The envelope constructed constitutes the current state of published knowledge regarding ‘normally occurring’ head accelerations. The envelope of kinematics represents activities commonly encountered and posing zero to minimal risk of injury to healthy individuals. Several kinematic measures, including linear accelerations, rotational velocities, and rotational accelerations, one may encounter as a result of normal everyday activities are summarized. A total of 11 studies encompassing 49 unique activities were evaluated. Examples of activities include sitting in a chair, jumping off a step, running, and walking. The peak resultant linear accelerations of the head reported in the literature were all less than 15 g, while the peak resultant rotational accelerations and rotational velocities approach 1375 rad/s2 and 12.8 rad/s, respectively. The resulting design envelope can be used to understand the range of acceleration magnitudes a typical active person can expect to experience. The results are also useful to compare to other activities exposing the head to motion or impact including sports, military, automotive, aerospace and other sub-injurious and injurious events.

Physical differences between youth and adults, which include incomplete myelination, limited neck muscle development, and a higher head-body ratio in the youth population, likely contribute towards the increased susceptibility of youth to concussion. Previous research efforts have considered the biomechanics of concussion for adult populations, but these known age-related differences highlight the necessity of quantifying the risk of concussion for a youth population. This study adapted the previously developed Generalized Acceleration Model for Brian Injury Threshold (GAMBIT) that combines linear and rotational head acceleration to model the risk of concussion for a youth population with the Generalized Acceleration Model for Concussion in Youth (GAM-CY). Survival analysis was used in conjunction with head impact data collected during participation in youth football to model risk between individuals who sustained medically-diagnosed concussions (n = 15). Receiver operator characteristic curves were generated for peak linear acceleration, peak rotational acceleration, and GAM-CY, all of which were observed to be better injury predictors than random guessing. GAM-CY was associated with an area under the curve of 0.89 (95% confidence interval: 0.82–0.95) when all head impacts experienced by the concussed players were considered. Concussion tolerance was observed to be lower for youth athletes, with average peak linear head acceleration of 62.4 ± 29.7 g compared to 102.5 ± 32.7 g for adults and average peak rotational head acceleration of 2609 ± 1591 rad/s2 compared to 4412 ± 2326 rad/s2. These data provide further evidence of age-related differences in concussion tolerance and may be used for the development of youth-specific protective designs.

OBJECTIVEThere is a growing body of literature informing efforts to improve the safety of football; however, research relating on-field activity to head impacts in youth football is limited. Therefore, the objective of this study was to compare head impact exposure (HIE) measured in game plays among 3 youth football teams.METHODSHead impact and video data were collected from athletes (ages 10–13 years) participating on 3 youth football teams. Video analysis was performed to verify head impacts and assign each to a specific play type. Each play was categorized as a down, punt, kickoff, field goal, or false start. Kickoffs and punts were classified as special teams. Downs were classified as running, passing, or other. HIE was quantified by play type in terms of mean, median, and 95th percentile linear and rotational acceleration. Mixed-effects models were used to assess differences in acceleration among play types. Contact occurring on special teams plays was evaluated using a standardized video abstraction form.RESULTSA total of 3003 head impacts over 27.5 games were analyzed and paired with detailed video coding of plays. Most head impacts were attributed to running (79.6%), followed by passing (14.0%), and special teams (6.4%) plays. The 95th percentile linear acceleration measured during each play type was 52.6g, 50.7g, and 65.5g, respectively. Special teams had significantly greater mean linear acceleration than running and passing plays (both p = 0.03). The most common kick result on special teams was a deep kick, of which 85% were attempted to be returned. No special teams plays resulted in a touchback, and one resulted in a fair catch. One-third of all special teams plays and 92% of all nonreturned kicks resulted in athletes diving toward the ball.CONCLUSIONSThe results demonstrate a trend toward higher head impact magnitudes on special teams than for running and passing plays, but a greater number of impacts were measured during running plays. Deep kicks were most common on special teams, and many returned and nonreturned kicks resulted in athletes diving toward the ball. These results support policy changes to youth special teams plays, including modifying the yard line the ball is kicked from and coaching proper return technique. Further investigation into biomechanical exposure measured during game impact scenarios is needed to inform policy relevant to the youth level.

While many research efforts have focused on head impact exposure in professional soccer, there have been few studies characterizing exposure at the youth level. The aim of this study is to evaluate a new instrumentation approach and collect some of the first head impact exposure data for youth female soccer players. Athletes were instrumented with custom-fit mouthpieces that measure head impacts. Detailed video analysis was conducted to identify characteristics describing impact source (e.g., kick, header, throw). A total of 763 verified head impacts were collected over 23 practices and 8 games from 7 athletes. The median peak linear accelerations, rotational velocities, and rotational accelerations of all impacts were 9.4 g, 4.1 rad/s, and 689 rad/s2, respectively. Pairwise comparisons resulted in statistically significant differences in kinematics by impact source. Headers following a kicked ball had the highest accelerations and velocity when compared to headers from thrown or another header.

OBJECTIVELimiting contact in football practice can reduce the number of head impacts a player receives, but further research is needed to inform the modification of optimal drills that mitigate head impact exposure (HIE) while the player develops the skills needed to safely play the game. This study aimed to compare HIE in practice drills among 6 youth football teams and to evaluate the effect of a team on HIE.METHODSOn-field head impact data were collected from athletes (ages 10–13 years) playing on 6 local youth football teams (teams A–F) during all practices using the Head Impact Telemetry System. Video was recorded and analyzed to verify and assign impacts to a specific drill. Drills were identified as follows: dummy/sled tackling, half install, install, install walk through, multiplayer tackle, Oklahoma, one-on-one, open field tackling, other, passing, position skill work, scrimmage, special teams, tackling drill stations, and technique. HIE was quantified in terms of impacts per player per minute (ppm) and peak linear and rotational head acceleration. Generalized linear models were used to assess differences in head impact magnitude and frequency among drills as well as among teams within the most common drills.RESULTSAmong 67 athlete-seasons, a total of 14,718 impacts during contact practices were collected and evaluated in this study. Among all 6 teams, the mean linear (p < 0.0001) and rotational (p < 0.0001) acceleration varied significantly among all drills. Open field tackling had significantly (p < 0.001) higher mean linear acceleration than all other drills. Multiplayer tackle had the highest mean impact rate (0.35 ppm). Significant variations in linear acceleration and impact rate were observed among teams within specific drills. Team A had the highest mean linear acceleration in install, one-on-one, and open field tackling and the highest mean impact rate in Oklahoma and position skill work. Although team A spent the greatest proportion of their practice on minimal- or no-player versus player contact drills (27%) compared to other teams, they had the highest median (20.2g) and 95th percentile (56.4g) linear acceleration in practice.CONCLUSIONSFull-speed tackling and blocking drills resulted in the highest HIE. Reducing time spent on contact drills relative to minimal or no contact drills may not lower overall HIE. Instead, interventions such as reducing the speed of players engaged in contact, correcting tackling technique, and progressing to contact may reduce HIE more effectively.

OBJECTIVE The objective of this study was to characterize changes in head impact exposure (HIE) across multiple football seasons and to determine whether changes in HIE correlate with changes in imaging metrics in youth football players. METHODS On-field head impact data and pre- and postseason imaging data, including those produced by diffusion tensor imaging (DTI), were collected from youth football athletes with at least two consecutive seasons of data. ANCOVA was used to evaluate HIE variations (number of impacts, peak linear and rotational accelerations, and risk-weighted cumulative exposure) by season number. DTI scalar metrics, including fractional anisotropy, mean diffusivity, and linear, planar, and spherical anisotropy coefficients, were evaluated. A control group was used to determine the number of abnormal white matter voxels, which were defined as 2 standard deviations above or below the control group mean. The difference in the number of abnormal voxels between consecutive seasons was computed for each scalar metric and athlete. Linear regression analyses were performed to evaluate relationships between changes in HIE metrics and changes in DTI scalar metrics. RESULTS There were 47 athletes with multiple consecutive seasons of HIE, and corresponding imaging data were available in a subsample (n = 19) of these. Increases and decreases in HIE metrics were observed among individual athletes from one season to the next, and no significant differences (all p > 0.05) in HIE metrics were observed by season number. Changes in the number of practice impacts, 50th percentile impacts per practice session, and 50th percentile impacts per session were significantly positively correlated with changes in abnormal voxels for all DTI metrics. CONCLUSIONS These results demonstrate a significant positive association between changes in HIE metrics and changes in the numbers of abnormal voxels between consecutive seasons of youth football. Reducing the number and frequency of head impacts, especially during practice sessions, may decrease the number of abnormal imaging findings from one season to the next in youth football.

Concerns about the effects of intentional heading in soccer have led to regulatory restrictions on headers for youth players. However, there is limited data describing how header exposure varies across age levels, and few studies have attempted to compare head impact exposure across different levels of play with the same sensor. Additionally, little is known about the biomechanical response of the brain to header impacts. The objective of this study was to evaluate head kinematics and the resulting tissue-level brain strain associated with intentional headers among youth and collegiate female soccer players. Six youth and 13 collegiate participants were instrumented with custom mouthpiece-based sensors measuring six-degree-of-freedom head kinematics of headers during practices and games. Kinematics of film-verified headers were used to drive impact simulations with a detailed brain finite element model to estimate tissue-level strain. Linear and rotational head kinematics and strain metrics, specifically 95th percentile maximum principal strain (e1,95) and the area under the cumulative strain damage measure curve (VSM1), were compared across levels of play (i.e., youth vs. collegiate) while adjusting for session type and ball delivery method. A total of 483 headers (n = 227 youth, n = 256 collegiate) were analyzed. Level of play was significantly associated with linear acceleration, rotational acceleration, rotational velocity, e1,95, and VSM1. Headers performed by collegiate players had significantly greater mean head kinematics and strain metrics compared to those performed by youth players (all p

Head impact exposure is often quantified using peak resultant kinematics. While kinematics describes the inertial response of the brain to impact, they do not fully capture the dynamic brain response. Strain, a measure of the tissue-level response of the brain, may be a better predictor of injury. In this study, kinematic and strain metrics were compared to contact characteristics in youth football. Players on 2 opposing teams were instrumented with head impact sensors to record impact kinematics. Video was collected to identify contact scenarios involving opposing instrumented players (ie, paired contact scenarios) and code contact characteristics (eg, player role, impact location). A previously validated, high-resolution brain finite element model, the atlas-based brain model, was used to simulate head impacts and calculate strain metrics. Fifty-two paired contact scenarios (n = 105 impacts) were evaluated. Lighter players tended to have greater biomechanical metrics compared to heavier players. Impacts to the top of the helmet were associated with lower strain metrics. Overall, strain was better correlated with rotational kinematics, suggesting these metrics may be better predictors of the tissue-level brain response than linear kinematics. Understanding the effect of contact characteristics on brain strain will inform future efforts to improve sport safety.

Repetitive head impact (RHI) exposure in collision sports may contribute to adverse neurological outcomes in former players. In contrast to a concussion, or mild traumatic brain injury, “subconcussive” RHIs represent a more frequent and asymptomatic form of exposure. The neural network‐level signatures characterizing subconcussive RHIs in youth collision‐sport cohorts such as American Football are not known. Here, we used resting‐state functional MRI to examine default mode network (DMN) functional connectivity (FC) following a single football season in youth players (n = 50, ages 8–14) without concussion. Football players demonstrated reduced FC across widespread DMN regions compared with non‐collision sport controls at postseason but not preseason. In a subsample from the original cohort (n = 17), players revealed a negative change in FC between preseason and postseason and a positive and compensatory change in FC during the offseason across the majority of DMN regions. Lastly, significant FC changes, including between preseason and postseason and between in‐ and off‐season, were specific to players at the upper end of the head impact frequency distribution. These findings represent initial evidence of network‐level FC abnormalities following repetitive, non‐concussive RHIs in youth football. Furthermore, the number of subconcussive RHIs proved to be a key factor influencing DMN FC., Using resting‐state functional MRI, DeSimone and colleagues demonstrate transient network‐level functional connectivity abnormalities of the default mode network following repetitive, non‐concussive head impact exposure over the course of a single youth football season.

Athletes participating in contact sports are exposed to repetitive subconcussive head impacts that may have long-term neurological consequences. To better understand these impacts and their effects, head impacts are often measured during football to characterize head impact exposure and estimate injury risk. Despite widespread use of kinematic-based metrics, it remains unclear whether any single metric derived from head kinematics is well-correlated with measurable changes in the brain. This shortcoming has motivated the increasing use of finite element (FE)-based metrics, which quantify local brain deformations. Additionally, quantifying cumulative exposure is of increased interest to examine the relationship to brain changes over time. The current study uses the atlas-based brain model (ABM) to predict the strain response to impacts sustained by 116 youth football athletes and proposes 36 new, or derivative, cumulative strain-based metrics that quantify the combined burden of head impacts over the course of a season. The strain-based metrics developed and evaluated for FE modeling and presented in the current study present potential for improved analytics over existing kinematically-based and cumulative metrics. Additionally, the findings highlight the importance of accounting for directional dependence and expand the techniques to explore spatial distribution of the strain response throughout the brain.

Soccer players are regularly exposed to head impacts by intentionally heading the ball. Evidence suggests repetitive subconcussive head impacts may affect the brain, and females may be more vulnerable to brain injury than males. This study aimed to characterize head impact exposure among National Collegiate Athletic Association women’s soccer players using a previously validated mouthpiece-based sensor. Sixteen players were instrumented during 72 practices and 24 games. Head impact rate and rate of risk-weighted cumulative exposure were compared across session type and player position. Head kinematics were compared across session type, impact type, player position, impact location, and ball delivery method. Players experienced a mean (95% confidence interval) head impact rate of 0.468 (0.289 to 0.647) head impacts per hour, and exposure rates varied by session type and player position. Headers accounted for 89% of head impacts and were associated with higher linear accelerations and rotational accelerations than nonheader impacts. Headers in which the ball was delivered by a long kick had greater peak kinematics (all P

The objective of this research was to characterize head impacts with a validated mouthpiece sensor in competitive youth female soccer players during a single season with a validated mouthpiece sensor. Participants included 14 youth female soccer athletes across 2 club-level teams at different age levels (team 1, ages 12–13 y; team 2, ages 14–15 y). Head impact and time-synchronized video data were collected for 66 practices and games. Video data were reviewed to characterize the type and frequency of contact experienced by each athlete. A total of 2216 contact scenarios were observed; heading the ball (n = 681, 30.7%) was most common. Other observed contact scenarios included collisions, dives, falls, and unintentional ball contact. Team 1 experienced a higher rate of headers per player per hour of play than team 2, while team 2 experienced a higher rate of collisions and dives. A total of 935 video-verified contact scenarios were concurrent with recorded head kinematics. While headers resulted in a maximum linear acceleration of 56.1g, the less frequent head-to-head collisions (n = 6) resulted in a maximum of 113.5g. The results of this study improve the understanding of head impact exposure in youth female soccer players and inform head impact exposure reduction in youth soccer.

The objective of this study was to determine the psychometrics (reliability, validity) of the original Standardized Assessment of Concussion (SAC) in a youth sample (ages 11 to 13). Demographic factors of race, level of vocabulary knowledge, mother's level of education were also considered. Over 150 youth football athletes completed the SAC and a brief battery of NIH Toolbox cognitive tests as part of a larger study on biomechanical factors in youth sport concussion. This was a within-subjects design (pre-season, post-season assessments), and correlational analysis of convergent and discriminant validity. Between groups analysis based on demographic differences was also employed. The pre-season SAC scores were not different by age; however, SAC scores were statistically different by race

Although most head impacts in soccer are headers, limited knowledge exists about how header magnitude varies by on-field scenario. This study aimed to compare head kinematics during on-field headers by play state (i.e., corner kick, goal kick, free kick, throw-in, drill, or live ball), intent (i.e., pass, shot, or clearance), and outcome (i.e., successful or unsuccessful). Fifteen female collegiate soccer players were instrumented with mouthpiece-based head impact sensors during 72 practices and 24 games. A total of 336 headers were verified and contextualized via film review. Play state was associated with peak linear acceleration, rotational acceleration, and rotational velocity (all p .001) while outcome was associated with peak linear acceleration (p .010). Header intent was not significantly associated with any kinematic metric. Headers during corner kicks (22.9 g, 2189.3 rad/s

Accumulation of head impacts may contribute to acute and long-term brain trauma. Wearable sensors can measure impact exposure, yet current sensors do not have validated impact detection methods for accurate exposure monitoring. Here we demonstrate a head impact detection method that can be implemented on a wearable sensor for detecting field football head impacts. Our method incorporates a support vector machine classifier that uses biomechanical features from the time domain and frequency domain, as well as model predictions of head-neck motions. The classifier was trained and validated using instrumented mouthguard data from collegiate football games and practices, with ground truth data labels established from video review. We found that low frequency power spectral density and wavelet transform features (10~30 Hz) were the best performing features. From forward feature selection, fewer than ten features optimized classifier performance, achieving 87.2% sensitivity and 93.2% precision in cross-validation on the collegiate dataset (n = 387), and over 90% sensitivity and precision on an independent youth dataset (n = 32). Accurate head impact detection is essential for studying and monitoring head impact exposure on the field, and the approach in the current paper may help to improve impact detection performance on wearable sensors.

OBJECTIVEThis study evaluated the frequency, magnitude, and location of head impacts in practice drills within a youth football team to determine how head impact exposure varies among different types of drills.METHODSOn-field head impact data were collected from athletes participating in a youth football team for a single season. Each athlete wore a helmet instrumented with a Head Impact Telemetry (HIT) System head acceleration measurement device during all preseason, regular season, and playoff practices. Video was recorded for all practices, and video analysis was performed to verify head impacts and assign each head impact to a specific drill. Eleven drills were identified: dummy/sled tackling, install, special teams, Oklahoma, one-on-one, open-field tackling, passing, position skill work, multiplayer tackle, scrimmage, and tackling drill stations. Generalized linear models were fitted to log-transformed data, and Wald tests were used to assess differences in head accelerations and impact rates.RESULTSA total of 2125 impacts were measured during 30 contact practices in 9 athletes (mean age 11.1 ± 0.6 years, mean mass 44.9 ± 4.1 kg). Open-field tackling had the highest median and 95th percentile linear accelerations (24.7g and 97.8g, respectively) and resulted in significantly higher mean head accelerations than several other drills. The multiplayer tackle drill resulted in the highest head impact frequency, with an average of 0.59 impacts per minute per athlete, but the lowest 95th percentile linear accelerations of all drills. The front of the head was the most common impact location for all drills except dummy/sled tackling.CONCLUSIONSHead impact exposure varies significantly in youth football practice drills, with several drills exposing athletes to high-magnitude and/or high-frequency head impacts. These data suggest that further study of practice drills is an important step in developing evidence-based recommendations for modifying or eliminating certain high-intensity drills to reduce head impact exposure and injury risk for all levels of play.

The objective of this study was to compare the performance of six validated brain finite element (FE) models to localized brain motion validation data in five experimental configurations. Model performance was measured using the objective metric CORA (CORrelation and Analysis), where higher ratings represent better correlation. The KTH model achieved the highest average CORA rating, and the ABM received the highest average rating among models robustly validated against five cadaver impacts in three directions. This technique can be more frequently employed to build better models and, when associated limitations are well understood, to compare inter-model performance under similar conditions.

The effect of repetitive sub-concussive head impact exposure in contact sports like American football on brain health is poorly understood, especially in the understudied populations of youth and high school players. These players, aged 9-18 years old may be particularly susceptible to impact exposure as their brains are undergoing rapid maturation. This study helps fill the void by quantifying the association between head impact exposure and functional connectivity, an important aspect of brain health measurable via resting-state fMRI (rs-fMRI). The contributions of this paper are three fold. First, the data from two separate studies (youth and high school) are combined to form a high-powered analysis with 60 players. These players experience head acceleration within overlapping impact exposure making their combination particularly appropriate. Second, multiple features are extracted from rs-fMRI and tested for their association with impact exposure. One type of feature is the power spectral density decomposition of intrinsic, spatially distributed networks extracted via independent components analysis (ICA). Another feature type is the functional connectivity between brain regions known often associated with mild traumatic brain injury (mTBI). Third, multiple supervised machine learning algorithms are evaluated for their stability and predictive accuracy in a low bias, nested cross-validation modeling framework. Each classifier predicts whether a player sustained low or high levels of head impact exposure. The nested cross validation reveals similarly high classification performance across the feature types, and the Support Vector, Extremely randomized trees, and Gradboost classifiers achieve F1-score up to 75%.

The effect of subconcussive head impact exposure during contact sports, including American football, on brain health is poorly understood particularly in young and adolescent players, who may be more vulnerable to brain injury during periods of rapid brain maturation. This study aims to quantify the association between cumulative effects of head impact exposure from a single season of football on white matter (WM) integrity as measured with diffusion MRI. The study targets football players aged 9-18 years old. All players were imaged pre- and post-season with structural MRI and diffusion tensor MRI (DTI). Fractional Anisotropy (FA) maps, shown to be closely correlated with WM integrity, were computed for each subject, co-registered and subtracted to compute the change in FA per subject. Biomechanical metrics were collected at every practice and game using helmet mounted accelerometers. Each head impact was converted into a risk of concussion, and the risk of concussion-weighted cumulative exposure (RWE) was computed for each player for the season. Athletes with high and low RWE were selected for a two-category classification task. This task was addressed by developing a 3D Convolutional Neural Network (CNN) to automatically classify players into high and low impact exposure groups from the change in FA maps. Using the proposed model, high classification performance, including ROC Area Under Curve score of 85.71p and F1 score of 83.33p was achieved. This work adds to the growing body of evidence for the presence of detectable neuroimaging brain changes in white matter integrity from a single season of contact sports play, even in the absence of a clinically diagnosed concussion.

Purpose Head impact exposure (HIE) (i.e., magnitude and frequency of impacts) can vary considerably among individuals within a single football team. To better understand individual-specific factors that may explain variation in head impact biomechanics, this study aimed to evaluate the relationship between physical performance measures and HIE metrics in youth football players. Methods Head impact data were collected from youth football players using the Head Impact Telemetry System. Head impact exposure was quantified in terms of impact frequency, linear and rotational head acceleration, and risk-weighted cumulative exposure metrics (RWELinear, RWERotational, and RWECP). Study participants completed four physical performance tests: vertical jump, shuttle run, three-cone, and 40-yard sprint. The relationships between performance measures, and HIE metrics were evaluated using linear regression analyses. Results A total of 51 youth football athletes (ages, 9-13 yr) completed performance testing and received combined 13,770 head impacts measured with the Head Impact Telemetry System for a full season. All performance measures were significantly correlated with total number of impacts in a season, RWELinear-Season, and all RWE-Game metrics. The strongest relationships were between 40-yard sprint speed and all RWE-Game metrics (all P ≤ 0.0001 and partial R > 0.3). The only significant relationships among HIE metrics in practice were between shuttle run speed and total practice impacts and RWELinear-Practices, 40 yard sprint speed and total number of practice impacts, and three-cone speed and 95th percentile number of impacts/practice. Conclusions Generally, higher vertical jump height and faster times in speed and agility drills were associated with higher HIE, especially in games. Physical performance explained less variation in HIE in practices, where drills and other factors, such as coaching style, may have a larger influence on HIE.

The objective of this study was to develop a mouthpiece sensor with improved head kinematic measurement for use in non-helmeted and helmeted sports through laboratory validation and pilot field deployment in female youth soccer. For laboratory validation, data from the mouthpiece sensor was compared to standard sensors mounted in a headform at the center of gravity as the headform was struck with a swinging pendulum. Linear regression between peak kinematics measured from the mouthpiece and headform showed strong correlation, with r2 values of 0.95 (slope = 1.02) for linear acceleration, 1.00 (slope = 1.00) for angular velocity, and 0.97 (slope = 0.96) for angular acceleration. In field deployment, mouthpiece data were collected from four female youth soccer players and time-synchronized with film. Film-verified events (n = 915) were observed over 9 practices and 5 games, and 632 were matched to a corresponding mouthpiece event. This resulted in an overall sensitivity of 69.2% and a positive predictive value of 80.3%. This validation and pilot field deployment data demonstrates that the mouthpiece provides highly accurate measurement of on-field head impact data that can be used to further study the effects of impact exposure in both helmeted and non-helmeted sports.

To understand the biomechanical basis of head impacts, finite element (FE) modeling is used to estimate the response throughout the brain in various impact conditions. FE simulation of head motion requires a complete description of kinematics, such as six degrees of freedom (6DOF) linear and rotational acceleration curves defining the boundary conditions. These are not available from many common head impact sensors such as the Head Impact Telemetry (HIT) System. At the same time, there are hundreds of thousands of impacts, likely millions of impacts, collected by HITS which represent an underutilized resource for computational modeling. The goal of this study was to develop an algorithm to determine 6DOF acceleration curves based on the corresponding HITS output data for use in FE modeling. The transformation algorithm was developed from a dataset of 14,767 head impacts collected with the HIT System and the corresponding 6DOF information provided by a published algorithm for this study. The impacts were sorted into impact regions and classified by the polarity of peak accelerations, and characteristic curves for each polarity combination were calculated. The algorithm was validated against 50 random impacts by comparing predicted and true acceleration curves using an objective curve comparison metric, CORA, to quantify error. These results demonstrate the algorithm accurately estimates 6DOF motion characteristics from 5DOF inputs sufficient for the purpose of performing basic biomechanical analyses of the impacts through FE modeling.

Purpose To examine the effects of subconcussive impacts resulting from a single season of youth (age range, 8-13 years) football on changes in specific white matter (WM) tracts as detected with diffusion-tensor imaging in the absence of clinically diagnosed concussions. Materials and Methods Head impact data were recorded by using the Head Impact Telemetry system and quantified as the combined-probability risk-weighted cumulative exposure (RWECP). Twenty-five male participants were evaluated for seasonal fractional anisotropy (FA) changes in specific WM tracts: the inferior fronto-occipital fasciculus (IFOF), inferior longitudinal fasciculus, and superior longitudinal fasciculus (SLF). Fiber tracts were segmented into a central core and two fiber terminals. The relationship between seasonal FA change in the whole fiber, central core, and the fiber terminals with RWECP was also investigated. Linear regression analysis was conducted to determine the association between RWECP and change in fiber tract FA during the season. Results There were statistically significant linear relationships between RWEcp and decreased FA in the whole (R2 = 0.433; P = .003), core (R2 = 0.3649; P = .007), and terminals (R2 = 0.5666; P < .001) of left IFOF. A trend toward statistical significance (P = .08) in right SLF was observed. A statistically significant correlation between decrease in FA of the right SLF terminal and RWECP was also observed (R2 = 0.2893; P = .028). Conclusion This study found a statistically significant relationship between head impact exposure and change of FA fractional anisotropy value of whole, core, and terminals of left IFOF and right SLF's terminals where WM and gray matter intersect, in the absence of a clinically diagnosed concussion. © RSNA, 2016.

ObjectiveThe objective of this pilot study was to characterize head impact exposure in a sample of youth boys' ice hockey using a novel instrumented mouthpiece, improving accuracy.BackgroundFrom 2010 to 2018 youth ice hockey saw a 15% increase in participation, despite growing concerns for concussion risk in contact sports. While contact sports with similar rates of concussion have been subjected to rigorous study, head impact exposure in youth ice hockey has been largely underexplored. Existing youth studies have utilized helmet-mounted sensors, which are associated with error due to poor coupling with the skull.Design/MethodsCustom mouthpieces containing a tri-axial accelerometer and gyroscope were fit to seven enrolled athletes, and monitored during practices and games throughout the season. Linear acceleration and rotational velocity of the head were recorded for 60 ms when 5 g was exceeded on any axis for at least 3 ms. Time-synchronized film was reviewed to identify the contact scenario and head contact. Summary statistics of kinematics were calculated by scenario and presence of head contact.ResultsA total of 465 events were recorded over 25 weeks. Of these events 25% involved head contact; 92% of all contact scenarios were board checks, falls, or ice checks. Events involving head contact (i.e., head impacts) had median [95th percentile] peak linear acceleration, rotational velocity, and angular acceleration of 8.1 [30.9] g, 7.9 [20.2] rad/s, and 614 [2673] rad/s2, respectively. Events not involving head contact had median [95th percentile] peak linear acceleration, rotational velocity, and angular acceleration of 6.6 [43.8] g, 6.5 [17.5] rad/s, and 455 [4115] rad/s2, respectively.ConclusionsThe majority of the recorded events could be classified as board checks, falls, or ice checks. Median peak kinematics were higher for head impacts than non-head impact events. In contrast, 95th percentile linear and angular accelerations were greater for impacts not involving head contact.

During normal participation in football, players are exposed to repetitive subconcussive head impacts, or impacts that do not result in signs and symptoms of concussion. To better understand the effects of repetitive subconcussive impacts, the biomechanics of on-field head impacts and resulting brain deformation need to be well characterized. The current study evaluates local brain response to typical youth football head impacts using the atlas-based brain model (ABM), an anatomically accurate brain finite element (FE) model. Head impact kinematic data were collected from three local youth football teams using the Head Impact Telemetry (HIT) System. The azimuth and elevation angles were used to identify impacts near six locations of interest, and low, moderate, and high acceleration magnitudes (5th, 50th, and 95th percentiles, respectively) were calculated from the grouped impacts for FE simulation. Strain response in the brain was evaluated by examining the range and peak maximum principal strain (MPS) values in each element. A total of 40,538 impacts from 119 individual athletes were analyzed. Impacts to the facemask resulted in 0.18 MPS for the high magnitude impact category. This was 1.5 times greater than the oblique impact location, which resulted in the lowest strain value of 0.12 for high magnitude impacts. Overall, higher strains resulted from a 95th percentile lateral impact (41.0g, 2556 rad/sec(2)) with two predominant axes of rotation than from a 95th percentile frontal impact (67.6g, 2641 rad/sec(2)) with a single predominant axis of rotation. These findings highlight the importance of accounting for directional dependence and relative contribution of axes of rotation when evaluating head impact response.

Sport-related head impacts are of increasing concern as early evidence has demonstrated a relationship between subconcussive head impact exposure (HIE) experienced in contact sports, such as football, and changes in pre-to post-season imaging and cognitive measures. Cumulative HIE is often measured with a single number that amounts to the total exposure measured over the season and does not give any indication as to how the exposure was accumulated, nor how it varies during the season. Therefore, the objective of this study was to compare HIE during preseason, the first and second halves of the regular season, and playoffs in a sample of youth football players (n = 119, ages 9–13). Athletes were divided into 1 of 4 exposure groups based on quartiles computed from the distribution of risk-weighted cumulative exposure (RWECP). The mean 95th percentile linear and rotational accelerations and impacts per session in practices and games were compared across 4 exposure groups and time frames using mixed effects models. Within games, the sample mean 95th percentile linear and rotational accelerations ranged from 47.2 g and 2,331.3 rad/s2 during preseason to 52.1 g and 2,533.4 rad/s2 during the second half of regular season. Mean impacts per practice increased from preseason to the second half of regular season and declined into playoffs among all exposure groups; however, the variation between time frames was not greater than 2 impacts per practice. Time of season had a significant effect on mean 95th percentile linear and rotational acceleration in games (both p = 0.01) but not on practice accelerations or impacts/session. Mean 95th percentile accelerations for games showed significant interaction effects between exposure group and season segment (linear p = 0.05 and rotational p = 0.04). The results of this study improve our understanding of in-season variations in youth football HIE and may inform important opportunities for future interventions.