How COVID-19 is Increasing NFL Injuries and What Teams Can Do About It

By Mike Compton | Sport Science Consultant | Fusion Sport 

With Pro Bowl stars like Cowboys quarterback Dak Prescott, 49ers defensive end Nick Bosa, and Giants running back Saquon Barkley who were ruled out for the last of the season and almost 300 others that were on the IR list, the spotlight has swung back onto injury rates in the NFL. For several years, the biggest question has been whether training and playing on artificial turf is increasing the incidence of injury. But with COVID-19 shortening the offseason and protocols that were still in place during the race to the Super Bowl, the focus switched to determining what kind of impact the pandemic is having on the injury rate. In this article, I’ll explore the latest research and suggest ways in which data-driven injury surveillance can help coaches, staff, and athletes adapt to the durability challenges presented by COVID.

A PRO FOOTBALL INJURY OVERVIEW

While he was the coach of the Houston Oilers, Jerry Glanville made the quip that NFL doesn’t stand for “National Football League” but rather “Not For Long.” This isn’t merely anecdotal is backed up by the data. An ESPN story that sourced information from the NFL Players stated that the average career length in pro football is just 3.3 years.[1]

One of the reasons for this lack of longevity is the unique demands placed on NFL players’ bodies. In addition to dealing with the acute loads created by running fast, jumping high, and cutting quickly, athletes are also hit hard by bodies that are bigger, stronger, and faster than ever before. As a result, there is a significant incidence of both non-contact and contact injuries. Per a review conducted at University of Buffalo’s Jacobs School of Medicine and Biomedical Sciences,[2]

Though the amount of lower body injuries during the 2019 season remained steady and the number of ACL and MCL tears declined, the start of the current season saw a surge in soft tissue-related incidents.[3] As one Yahoo Sports article rightly put it when looking at this trend through the lens of the pandemic, “There appears to be a direct correlation between the lack of a typical offseason program and the increased soft-tissue injury rate.”[4]

LEARNING LESSONS FROM THE 2011 NFL LOCKOUT

While there is no historical precedent for a pandemic impacting pro sports, we can look back to 2011 and find another case of the NFL preseason being cut short. In that instance, it wasn’t a virus outbreak that impacted pro football but rather a 132-day labor dispute. This included a five-week lockout, during which players and staff couldn’t enter team facilities.

Putting this into context, that’s the equivalent of missing the final month-long block (or microcycle) of a training mesocycle in a team’s periodization plan. Such a shortcut would lead to athletes finding it difficult to achieve the performance goals set before beginning such a cycle. In the case of the NFL lockout and, more recently, the abbreviated NFL offseason that began in the midst of the pandemic, the ripple effect went far beyond strength and conditioning. In both cases, players also had limited access to medical and performance staff, as well as resources like sports psychologists, nutritionists/dieticians, and athletic trainers.

We can glean some valuable insights from an editorial published in the Journal of Orthopaedic & Sports Physical Therapy that investigated the negative impact of the 2011 lockout. The authors revealed that there would typically be between one and three Achilles tendon tears among NFL players during the six- week period that includes training camp and preseason training. Yet during the lockout-shortened season, this number skyrocketed to 10 Achilles tears in the first 12 days of training camp and two more in the subsequent 17 days.[5]

While this four-fold increase is shocking, it’s not all that surprising. A connective tissue such as the Achilles tendon has to bear a load that’s up to five times a player’s body weight. In a sport like pro football in which players are repeatedly jumping, landing, accelerating, and changing directions, such connective tissues are subjected to high acute loads in quick succession. Under normal circumstances in which they’ve had a full preseason to prepare for the rigors of the 16-game regular season schedule and the playoffs, this might not be a problem. But removing a significant chunk of this period because of the lockout prevented NFL players from building up sufficient tolerance to the forces they create when jumping and running and those they’re subjected to during explosive movement during practices and competition.

While we don’t yet have a full data set for the current NFL season or the benefit of studies examining this information in detail, I’d expect the pattern observed following the 2011 lockout to repeat itself when we look back on the COVID-19-impacted 2020-2021 season. If we just focus on the Achilles, there were already 15 tears or ruptures in the NFL by the end of October 2020 – three more than observed during the 2011 increase.[6]

USING TECHNOLOGY TO IMPROVE INJURY SURVEILLANCE AND LOAD MONITORING

One of the main reasons that history is repeating itself in NFL injury rates following the same upward trajectory during the pandemic as after the 2011 lockout is that tendons, ligaments, and other connective tissues take longer to strengthen than muscles. This is why cutting out a multi-week block from players’ preparation is having a particularly significant impact upon injuries to these supporting structures this season. It’s arguable that when we look back at the numbers in hindsight, we’ll also notice a spike in contact-related injuries, as teams have been unable to expose their players to enough collisions during practice to ready them for the level of contact they experience during games.

The authors of a study published in The Journal of Strength and Conditioning Research that focused on college football injuries noted that “players who are heavily relied upon for achievement of team success are exposed to a greater volume of physically demanding practice session drills and scrimmage plays.” As such, an NFL team’s starters need to build up a greater load tolerance, to ensure their bodies can weather the storm.[7]

That being said, overemphasizing certain qualities like speed, strength, and power – even in a sport like football that requires them. Depending on a player’s load tolerance, the quality of their sleep, and other factors, it can take 48 to 72 hours for their central nervous system (CNS) to fully bounce back after competition or a training session that involves a lot of plyometrics, Olympic lifting, and/or sprinting, according to a study released via Medicine ts & Exercise [8] the CNS is still compromised, athletes’ coordination and neuromuscular activation decreases, increasing their injury risk. the CNS is still compromised, athletes’ coordination and neuromuscular activation decreases, increasing their injury risk.

Beyond simply spacing out high-intensity sessions, there are a couple of physical tests athletes could participate in to demonstrate whether they’ve recovered fully or not. An Australian research team found that using a force plate to measure athletes’ countermovement jumping can help distinguish between metabolic and neuromuscular fatigue.[9] If a team doesn’t have access to force plate technology, they could measure players’ grip strength before and after high-load training, which research shows is another indicator of CNS recovery.

Entering the results in an athlete management system like Smartabase will allow staff to collate the information, see it displayed in a graphical format, and overlay injury data. In doing so, they can better understand how the combination of competition and training loads are impacting player durability and make more informed choices about what to keep the same and what to change going forward. This becomes particularly important when there are uncontrollable and unexpected scheduling changes due to factors like the pandemic.

Example Smartabase Injury Surveillance Dashboard 

Adding some subjective measures to your athlete monitoring can also help better gauge player recovery and make on-the-fly programming alterations that reduce injury risk. For example, after a game or series of demanding practices, a performance director and their staff could pay particularly close attention to any variance in the rate of perceived exertion (RPE) that each player self-reports through the Smartabase Kiosk app. If there’s a dramatic change in how they feel – say they rate their RPE during a game or training session as a nine afterward when it’d usually be a five or six – this could be a sign that their central nervous system has been overtaxed without adequate opportunity to recover.

If this pattern is repeated across a certain position group (like the receiver corps or offensive linebackers) or throughout the squad, then it might be wise to lower the intensity, density, or duration of the next practice to allow more complete recovery. The same could be said of how well rested players feel on a scale of one to 10. While objective measurements like sleep scores and heart rate variability can tell us a lot, we also have to trust that athletes know their own bodies and adjust training plans accordingly so they don’t get pushed too far and increase their chance of getting hurt. This can be particularly beneficial when normally static KPIs like acute to chronic load ratio are disrupted by external events like COVID-19.

For more information on injury surveillance using the Smartabase Athlete Management System you can contact the Fusion Sport team here

About the Author

Mike Compton is a Principal Sport Science Consultant for Fusion Sport USA. As a former Division 1 College Basketball Strength Coach Mike has a strong knowledge of collegiate sport and a passion for applied data analytics for performance optimization.

 

References and resources:

 

[1] John Keim, “With Average NFL Career 3.3 years, Players Motivated to Complete MBA Program,” ESPN, July 29, 2016, available online at https://www.espn.com/blog/nflnation/post/_/id/207780/current-and-former-nfl-players-in-the-drivers-seat-after-completing-mba-program.

[2] Melissa A. Kluczynski et al, “A Systematic Review of the Orthopaedic Literature Involving National Football League Players,” Orthopaedic Journal of Sports Medicine, August 2019, available online at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6702781/.

[3] Judy Battista, “NFL Reveals 2019 Injury Data, Hopeful Rule Changes are Working,” NFL.com, January 23, 2020, available online at https://www.nfl.com/news/nfl-reveals-2019-injury-data-hopeful-rule-changes-are-working-0ap3000001098679.

[4] Eric Edholm, “Why So Many NFL Injuries This Season? One Sports-Medicine Doctor Thinks He Knows Why,” Yahoo Sports, October 30, 2020, available online at https://www.yahoo.com/now/why-so-many-nfl-injuries-this-season-one-sportsmedicine-doctor-thinks-he-knows-why-141643231.html.

[5] Gregory D. Myer et al, “Did the NFL Lockout Expose the Achilles Heel of Competitive Sports?” Journal of Orthopaedic & Sports Physical Therapy, October 1, 2011, available online at https://www.jospt.org/doi/full/10.2519/jospt.2011.0107.

[6] Eric Edholm, “Why So Many NFL Injuries This Season? One Sports-Medicine Doctor Thinks He Knows Why,” Yahoo Sports.

[7] Gary B. Wilkerson et al, “Utilization of Practice Session Average Inertial Load to Quantify College Football Injury Risk,” The Journal of Strength and Conditioning Research, September 2016, available online at https://journals.lww.com/nsca-jscr/fulltext/2016/09000/utilization_of_practice_session_average_inertial.1.aspx.

[8] Kevin Thomas et al, “Neuromuscular Fatigue and Recovery After Heavy Resistance, Jump, and Sprint Training,” Medicine & Science in Sports & Exercise, December 2018, available online at https://pubmed.ncbi.nlm.nih.gov/30067591/.

[9] Paul Pao-Yen Wu, “Predicting Fatigue Using Countermovement Jump Force-Time Signatures: PCA Can Distinguish Neuromuscular Versus Metabolic Fatigue,” PLOS ONE, July 10, 2019, available online at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6619745/.

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