Paper written by Stephen Youkoski
The early equipment used in American Football consisted of an oddly-shaped pigskin ball, leather helmets and clothes that were essentially normal everyday clothes. This would continue for some time, but as American Football became more mainstream with the formation of professional leagues such as the NFL, AFL and USFL, a focus on player safety and training started to come into fruition. Certain aspects of the team uniforms and equipment started to become standardized and required. The main parts of the required equipment were cleats, pads for the legs, shoulder pads and helmets (NFL 27), which have all become staple pieces of equipment in the modern NFL and are still required in football games today. As technology developed in the world, the world of football developed with it. Technology has helped in improving the safety and training of football players through a variety of ways. Artificial intelligence, or AI for short, has played a key role in the development as well as computer simulations and tracking systems. Advancements in protective headgear, the prediction of injuries, and the identification of injuries have all been made because of technology.
“Injuries to the head and neck are the most frequent catastrophic sports injury, and head injuries are the most common direct athletic cause of death” (Cantu 1). Due to the nature of the game, football players often experience head injuries and the leather helmets of the past have done next-to-nothing to protect a players head. In 1943, the NFL regulated helmets akin to the modern style helmets players don now (Zeegers). Although there were small changes made to the helmet design throughout the years, there was nothing truly innovative in terms of player safety. However, more recent developments in computer simulation technology have completely changed the game, so to speak, in terms of upgrading the protective headgear.
In February of 2020, Professor Jonathan D. Mortensen and his team at the University of Utah published an article titled the Sensitivity analysis of muscle properties and impact parameters on head injury risk in American football. In their research, they used computer-simulated models in order to simulate various impacts players have/will experience(d) on their heads. Their models were able to simulate many factors related to head injuries. These include “muscle activation patterns, muscle force properties, neck posture during impact, and characteristics of the impact” (Mortenson 2). In other words, the simulations measure when and how muscles tense, different positions of the head and neck and the different ways another player could impact the head. Mortenson found which factors have higher injury risk than others and identified that “posture affects injury risk much more than the other factors” (Mortenson 7). Without the simulations, it would be much more difficult to identify what risk factors are most important to address for safety. The information provided from the simulations allows for the development of the headgear to be focused on what would be safest for the players.
The effects of this simulation and others that provide information on the headgear are already being implemented. On September 6th, 2021, NBC sports writer Peter King detailed the new helmet changes in his article NFL’s new position-specific helmets, rule changes, COVID-19 rules, former player deaths. As of week one of the 2021-2022 season, “at least six NFL starters wearing the first position-specific helmet ever made” (King). These six players were chosen to test the helmets throughout the season. The helmets were designed for players on the offensive and defensive lines. These helmets have “additional streamlined padding at the lineman’s forehead and hairline” (King). Lucas Patrick, one of the players who was selected to test the helmet, stated that he “loved it.” Stacked up to all of the other helmet types for linemen, the new helmets are the “second-best performing helmet out of the 20 approved for player use” (King). With such a small amount of time in between the new simulations and the helmet’s creation, the development of protective headgear is constantly being improved because of technology.
American football is one of the most physical sports, and due to this a plethora of different types of injuries are possible. According to Dr. Hayden P. Baker, a doctor of sports medicine, in just the first four weeks of the 2022-202l NFL season, over five hundred injuries were reported amongst all players. Baker had also studied the three seasons prior as well, boosting the total number of injuries over the first four weeks to over three thousand. Although this may seem like a small sample size compared to the twelve/thirteen games, the point is that injuries do occur. As the amount of injuries increases, the NFL needs a way in which to find out how these injuries will occur. They have found just that through the use of artificial intelligence (AI) and advanced tracking systems.
In order to combat mysterious injuries, the NFL has partnered with Amazon to develop what they have dubbed the “Digital Athlete.” This artificial player has the ability to “replicate infinite scenarios within the game environment,” per Allen Sills of the NFL’s Player Health and Safety division. The Digital Athlete can also include a multitude of various “position and environmental factors” (Sills). In other words, it can simulate a quarterback in the rain as well as a defensive tackle in one hundred degree fahrenheit weather. Prior to the invention of the Digital Athlete, we could only predict injuries that we have seen occur before in similar situations. However, with the addition of this AI, we can predict nearly every injury that could occur in a situation that we have seen before and ones that we haven’t.
Along with their Digital Athlete, the NFL has been using a collective system of tracking systems in order to predict injuries. The platform as a whole debuted in the 2015-2016 NFL regular season, which the NFL named “Next Generation Statistics” or NGS for short. NGS “provides real-time location data, speed, and acceleration for every player during every play on every inch of the field” (Sills). In order to achieve this, the NFL has placed trackers in each player’s shoulder pads, as well as tagging footballs themselves with trackers, all of which were player tested and do not affect the play of the game (NFL). The technology has been continuously improved since then and “more than 200 new data points are created on every play of every game” (NFL). This expansive extraction of continuous data allows for the NFL to predict when an injury occurs to a player. NGS can also be used to aid in safe player training. With all of the data at hand, teams can use the data to see how fast players are going, what speeds are safe and if the position of a football would be too dangerous for a player to attempt to catch.
When a player is injured on the field during a play, broadcasters often attempt to assess the injury and offer their takes on what it could be. These are not official assessments, but even after the players were taken into the stadium for further care, no official diagnosis was made because the teams lacked the technology and data to make that call. However, along with the prediction of injuries, technology is being developed in order to better understand and identify injuries.
Head injuries are one of the most common to occur in American Football, which is why there is such a heavy focus on the advancement of protective headgear for players. However, headgear is not the only thing technology has aided in. The identification of head injuries, mainly concussions and connected-neck injuries, has been a topic among researchers in recent years. One such researcher, Dr. Jason P. Mihalik and his team, used a system that put together a large sample of head injuries that occured and found all of the correlations and differences between every situation and then put them through a computer simulation to see the results (Mikalik 2555). Mikalik found that not every head injury could be handled in the same manner. Some injuries require “early treatments aimed to enhance recovery” while others needed a more relaxed approach (Mikalik 2555). Technology helps identify the injury and then what recovery plan would be most helpful.
Another common type of injuries that occur in American Football are lower-body injuries, specifically injuries that involve the ankle. Dr. W. Brent Lievers and his associate Dr. Peter F. Adamic studied the rate of ankle injuries among American Football players and discovered that “the rate of foot and ankle injuries was 15 per 10,000 athletic exposures” (Lievers 1). In order to find this, they used a computer program and system called QIRAM. Technology allowed for the rate of injury to be easily discovered. Lievers was able to successfully identify what the five highest risk injuries were, those being “ankle dislocations, syndesmotic sprains, lateral ankle ligament sprains, metatarsal fractures, and malleolus fractures” (Lievers 7). Being able to understand these injuries will help staff, players and coaches to “effectively focus their preventative interventions” and help in being able to identify them easier (Lievers 7). This will also help the players be able to train safely and eliminate risk of these injuries occurring.
In conclusion, technology has aided in improving football player training and safety in a variety of ways. Computer simulations have allowed for situational awareness and the ability to know what may happen in-game, as well as being able to effectively predict and better identify injuries that are going to occur and those that have already occurred. Artificial intelligence has helped create an artificial athlete that can replicate infinite possibilities that can occur during a game and what would happen to a player. Tracking systems have allowed for real-time statistics of a player and better preparation and film study for players so they know what is safe and what is not. Technology has helped the world of American Football evolve and change for the better.
Works Cited
Baker, Hayden P., et al. “The Injury Rate in National Football League Players Increased Following Cancellation of Preseason Games Because of COVID-19.” Arthroscopy, Sports Medicine, and Rehabilitation. Vol. 3, No. 4, Aug. 2021, pp. 1-8. https://doi.org/10.1016/j.asmr.2021.05.002, Accessed 24 Mar. 2022
Cantu, R.C. “Head injuries in sports.” British Journal of Sports Medicine. Vol. 30, 1996, pp. 289-296. http://dx.doi.org/10.1136/bjsm.30.4.289, Accessed 25 Mar. 2022.
King, Peter. “NFL’s new position-specific helmets, rule changes, COVID-19 rules, former player deaths.” NBC Sports, 06 Sep. 2021. https://sports.nbcsports.com/2021/09/06/nfls-new-position-specific-helmets-rule-changes-covid-19-rules-former-player-deaths/, Accessed 16 Mar. 2022
Lievers, W. Brent, Adamic, Peter F. “Incidence and Severity of Foot and Ankle Injuries in Men’s Collegiate American Football.” Orthopedic Journal of Sports Medicine, 04 May, 2015. https://journals-sagepub-com.wilkes.idm.oclc.org/doi/pdf/10.1177/2325967115581593, Accessed 17 Mar. 2022
Mihalik, Jason P, et al. “Do Head Injury Biomechanics Predict Concussion Clinical Recovery in College American Football Players?” Annals of Biomedical Engineering, Vol. 48, No. 11, Nov. 2020, pp. 2555–2565. https://www-proquest-com.wilkes.idm.oclc.org/docview/2471729477?pq-origsite=summon, Accessed 16 Mar. 2022
Mortenson, Jonathan D., Anita N. Vasavada, Andrew S. Merryweather. “Sensitivity analysis of muscle properties and impact parameters on head injury risk in American football.” Journal of Biomechanics, Vol. 100, 2020, pp. 1-10. https://www-sciencedirect-com.wilkes.idm.oclc.org/science/article/pii/S002192901930658X?via%3Dihub, Accessed 18 Mar. 2022
“NFL: Next Gen Stats.” NFL Football Operations, https://operations.nfl.com/gameday/technology/nfl-next-gen-stats/, Accessed 24 Mar. 2022.
“Rule 5 of the NFL Rule Book: Players, Substitutes, Equipment, General Rules.” The National Football League, https://static.nfl.com/static/content/public/image/rulebook/pdfs/8_Rule5_Players_Subs_Equip_GeneralRules.pdf, Accessed 24 Mar. 2022
Sills, Allen. “Using Artificial Intelligence to Advance Player Health and Safety.” NFL Player Health Safety, NFL, 05 Dec. 2019, https://www.nfl.com/playerhealthandsafety/equipment-and-innovation/aws-partnership/using-artificial-intelligence-to-advance-player-health-and-safety, Accessed 18 Mar. 2022
Zeegers, Madilyn. “History of the NFL Helmet.” Sportscasting, 27 Aug. 2019, https://www.sportscasting.com/history-of-the-nfl-helmet/, Accessed 24 Mar. 2022