Journal of Strength & Conditioning Research:
A Profile of a National Football League Team
Pryor, J. Luke1; Huggins, Robert A.1; Casa, Douglas J.1; Palmieri, Gerard A.2; Kraemer, William J.1; Maresh, Carl M.1
1Human Performance Laboratory, Korey Stringer Institute, Department of Kinesiology, University of Connecticut, Storrs, Connecticut; and
2The New York Football Giants, East Rutherford, New Jersey
Address correspondence to J. Luke Pryor, firstname.lastname@example.org.
Abstract: Pryor, JL, Huggins, RA, Casa, DJ, Palmieri, GA, Kraemer, WJ, and Maresh, CM. A profile of a National Football League team. J Strength Cond Res 28(1): 7–13, 2014—The purpose of this study was to document the physical profiles of players on the 2011 New York Giants (NYG) team and to make comparisons with the historical literature on previous National Football League (NFL) player profiles. In this study, height, body mass (BM), body fat percentage (BF%) using skinfold measurements, and several predicted 1 repetition maximal strength and power measures in 30 returning players from the 2011 NYG team, who recently won the Super Bowl, were collected. Players were grouped by position: running back, quarterback (QB), wide receiver (WR), tight end, offensive lineman (OL), defensive lineman (DL), linebacker (LB), and defensive back (DB). Pooled and weighted mean differences (NYG − NFL) and effect sizes were used to evaluate height, BM, and BF% comparisons of NYG to previous NFL studies from 1998 to 2009. The characteristics of the players as a group were: age, height, BM, BF%: 26 ± 2 years, 183.8 ± 9.0 cm, 144.9 ± 20.8 kg, 14.3 ± 5.5%, respectively. Comparisons highlight distinct position-specific dissimilarity in strength measures, BM, and BF%, which reflect current strength training, conditioning, and team play strategy. As expected, NYG positional differences were found for height (p ≤ 0.05), BM (p ≤ 0.037), BF% (p ≤ 0.048), bench press (p ≤ 0.048), inclined bench press (p ≤ 0.013), and squat (p ≤ 0.026). Anthropometrics profiles did not significantly differ from previously published trends in NFL players indicating equity in physical characteristics over the past 13 years. However, NYG LBs, DLs, OLs, QBs, and WRs trended toward less BF% but generally similar BM compared with NFL players, suggesting greater lean BM in these positions. This study adds new players' data to prototypical position-specific databases that may be used as templates for comparison of players for draft selection or physical training.
Over the past 50 years, several authors have described anthropometry (e.g., height, body mass [BM], and body fat percentage [BF%]) and physical abilities of National Football League (NFL) players (12,13,18,26,29,32,33). Physical profiling is commonly used as a starting point to assess and compare players within positions and between playing divisions (e.g., National Collegiate Athletic Association Division I, II, III, and the NFL combine) (11,18,23). To our knowledge, no published study has documented the strength and body composition of players recently winning the Super Bowl.
Although strength, body composition, agility, speed, or jump characteristics are not direct measures of successful outcomes in football, they are believed to gauge the potential physical performance required to succeed at each position, and with NFL combine testing, they have been well documented (1,5,11,23,24). Therefore, the purpose of this study was to examine the anthropometric and strength characteristics of NFL players who recently participated in and won a Super Bowl to continue to develop a template for today's prototypical NFL player. A secondary purpose was to compare the anthropometric and strength attributes of these players with relevant NFL player profiles documented in the scientific literature.
Experimental Approach to the Problem
Anthropometric data were evaluated for returning players from the Super Bowl XLVI winning New York Giants (NYG) team at the beginning of the 2012 off-season training, 10 weeks after Super Bowl (April). Muscular strength and power measures were calculated from data obtained during the final week of a 1-month mesocycle designed to increase muscular strength (May) (4). The medical and strength and conditioning staff advised players to minimize physical and mental stress related to football for the first 4 weeks of the 10-week hiatus. For the remaining 6 weeks, players were advised to begin an individualized incremental periodized program with 2-week mesocycles, returning them to comparable competitive performance levels. Height, BM, BF%, and strength measures were collected and compared among different positions. Lastly, mean differences, effect size, and descriptive comparisons were used to evaluate and compare NYG with previous NFL literature.
Previous literature reporting data on NFL players commonly grouped seemingly similar positions together, for example tight ends (TEs) and linebackers (LBs) or wide receivers (WRs) and defensive backs (DBs). This method introduces a significant limitation when attempting to compare between positions. The position-specific break down within a combined position group is unknown; therefore, we only included player data from previous studies that did not categorize ≥2 positions together and followed the player groupings employed by a previous study of NFL players (18). Three published NFL studies from 1998 to 2009 (18,29,32) met these criteria and were used for comparison.
Thirty returning members from the Super Bowl XLVI winning NYG team volunteered for the study and completed testing as part of routine evaluations before NFL sanctioned off-season team practices. All risks and benefits were explained to the subject before the investigation. Before beginning, subjects signed an informed consent document that was approved by the University's institutional review board for use of human subjects in research. All subjects were free from injury at the time of testing.
One Repetition Maximum Estimation
The 1 repetition maximum (1RM) values were estimated from data obtained during the final week of a 1-month mesocycle designed to increase muscular strength (May, 2012) (4). The athletes performed the bench press, inclined bench press, back squat, and power clean workouts over the course of the last week. Because form can deteriorate rapidly with multiple RM testing (>5 repetitions) (25,27), low repetitions were selected for estimating strength training 1RM. The 1RM bench press, inclined bench press, and back squat were estimated from 5RM sets, whereas the 1RM power clean was estimated from a 2RM set. All 1RM estimations were calculated by dividing the highest weight performed for the designated repetitions in the workout (usually the last work set) by the highest percentage of the 1RM used for that workout. For example, if an athlete inclined bench pressed 136 kg (82% of 1RM) for 5 repetitions, then his estimated 1RM would be 165 kg. During all training sessions, athletes were instructed by the coaches to perform their best in preparation for the upcoming season.
The training sessions that were used to estimate 1RM values were recorded. Briefly, the bench press, inclined bench press, and back squat workout began with a standardized warm-up consisting of 8–10 repetitions at 50% of predicted 1RM, followed by a 1 × 3 (sets × repetitions) at 60%, and a 1 × 3 at 67% with 3 minutes of rest between sets. After another 3 minutes of rest, subjects completed 3 × 5 at 75–82% of their predicted 1RM with 3-minute rest periods between sets. The weight on the bar was increased with each set. The power clean workout consisted of a series of standardized warm-up sets to ensure proper form. These warm-up sets included a 1 × 2 at 67% of 1RM followed by a 1 × 2 at 77% with 3 minutes of rest between sets. After another 3 minutes of rest, a final 3 × 2 was performed from 82 to 87% of their predicted 1RM with 3-minute rest periods between sets. The weight on the bar was increased with each set. Athletes were free to increase the weight beyond the prescribed intensities, if capable of completing all the repetitions with good form. In this case, the strength and conditioning specialist then predicted the 1RM using the highest weight performed under the prescribed repetitions.
Height and BM were determined using a calibrated stadiometer and scale (Porta-Tronic 800, GE Systems Inc., Cape Coral, FL, USA), respectively. Body fat percentage was assessed with a Lange Caliper measuring the thigh, abdomen, and chest sites after the prescribed American College of Sports Medicine guidelines (2). All measures were recorded to the nearest 1.0 mm. If the initial 2 measurements were not within 2 mm, a third measure was obtained, and the 3 measurements were averaged before calculating body density and composition. The Jackson and Pollock (16) body composition formula was applied to calculate body density, and the Siri (28) equation determined BF%. The Siri equation is an accurate method of determining BF% in all NFL players except offensive linemen (OLs) and TEs, where BF% values were reportedly lower than hydrostatic weighing by approximately 3.3% (29). To limit intraobserver error, a single trained strength and conditioning specialist with over 15 years of 1RM estimation testing and body composition assessment experience on NFL players completed all skinfold measures.
A one-way analysis of variance with Tukey's post hoc compared mean differences between positions for strength and anthropometric measures for the NYG team. Next, we determined pooled and weighted mean values from 3 published NFL studies from 1998 to 2009 (18,29,32) for BM, BF%, and height and stratified results by position. Effect size was calculated as: (NYG − published NFL values)/pooled sample SD (10). We then compared NYG with NFL players to determine weighted mean differences (NYG − NFL) by position, related 95% confidence interval (CI), and overall effect. By convention, the magnitude of effect was interpreted as 0.2 as small, 0.5 as medium, and 0.8 as large (7). All analyses were completed with SPSS software (Version 21.0) and Microsoft Excel 2010 with an a priori alpha level of 0.05. Overall effect and weighted mean difference between NYG and NFL players was determined using a random effects model.
Player anthropometrics are reported in Table 1, whereas strength and power measures for inclined bench press, bench press, power clean, and squat are displayed in Figure 1. Effect size comparisons for BF%, height, and BM between NYG and NFL players between 1998 and 2009 are displayed in Table 2. Mean differences and the related 95% CI for height, BM, and BF% are reported in Figure 2. No significant overall effect was observed for BF% (Z = 1.22; p = 0.22), BM (Z = 0.73; p = 0.47), or height (Z = 0.42; p = 0.67) for NYG compared with previous NFL players from 1998 to 2009.
The purpose of this study was to describe and contrast the strength, power, and anthropometric characteristics of the 2011–2012 NYG and to compare these values with a cohort of NFL players between 1998 and 2009. To our knowledge, this is the first study to profile various strength and power measures and anthropometrics of team members recently winning a Super Bowl.
Several expected differences in NYG strength measures between positions were observed. Generally, OL squat and incline bench press significantly more than WRs and DBs, whereas DBs incline bench press less than LBs and defensive linemen (DL). The greatest difference in strength between positions was demonstrated in the bench press. Conversely, absolute power clean weight was not significantly different between positions. However, significance was observed when power clean was expressed relative to body weight (DB > OL and DL, LB > OL; p ≤ 0.044). The development of position-specific tasks and skillsets and the subsequent development of position-specific strength training regimens (5) are well known in American football (22,23) and together explain the discrepancies in absolute and relative strength measures between positions. For example, linemen require upper and lower body strength to execute charging, blocking, tackling, and in some cases (DL) pass coverage with superior speed of execution, force, and power (5,9,22,34). Conversely, speed, agility, and maneuverability are usually desired above strength in WRs and DBs (22). The relative lack of strength (particularly upper body) in WRs and DBs may be a decisive component in player-vs.-player success. For example, the ability of DBs to jam receivers at the line of scrimmage and tackle opponents, and similarly for WRs to avoid being jammed at the line of scrimmage and to stalk block opponents. This disparity in strength has been recognized by strength and conditioning coaches and improved over the past 3 decades. In 1984, Shields et al. (26) reported a 1RM bench press for DBs and WRs of 124.5 ± 26.0 kg vs. 131.8 ± 13.4 kg for the 2011 NYG. Similar improvements in strength have also been identified over time at the NFL combine (24).
The unique position-specific physical characteristics and skillsets that are a hallmark of American football (22,23) create distinct relationships between opposing positions. For example, our data and others (18,23,29,32) show that DL, in particular defensive ends, are usually smaller than OL. This size differential affords DL greater agility and speed (22,23) to bypass OL, tackle runners, assault quarterbacks, and provide pass coverage despite similarities in strength. Moreover, LB mirror RB in both size and strength as do WR and DB. Importantly, these opposing positions are not completely comparable among all physical metrics. Differences are observed in vertical jump, agility, and speed, and together with their respective unique skillsets provide position-specific diversity (22,23).
The paucity of strength and power measures reported among NFL players in the literature beyond NFL combine testing limits the ability to conclusively contrast our data with previous NFL players. Robbins et al. (23) found improvements in speed, height, weight, and 225-lbs bench press repetition in NFL combine players between 1999–2001 and 2008–2010. Likewise, our data show temporal gains in 1RM bench press ranging from 7.3 to 36.2 kg depending on position from those reported by Shields et al. (26). These improvements in strength may be because of players and strength and conditioning specialists becoming more knowledgeable about nutrition strategies focusing on macronutrient content and timing (31), nutraceutical and anabolic steroid use (15), year-round physical training (8), and the prevalence of professionally educated and trained strength and conditioning specialists.
Although the analysis of temporal body composition changes in NFL players has become recently popularized (3,18,24), the unique nature of our data warrants a similar analysis. Using the predictions by Anzell et al. (3) and the most recent NFL player data from Kraemer et al. (18) collected in 2003, the BF%, height, and BM for all NYG combined positions would be estimated as 15.5–17.4%, 186.5–187.7 cm, and 121.2–124.5 kg, respectively. Interestingly, NYG BF% (14.3%) and BM (112.2 kg) were below these predicted values suggesting improved body composition. Indeed, discernible trends are evident among magnitude-based comparisons of mean differences and effect sizes within several positions for BM and BF% (Figure 2) and support the notion of improved body composition over time in some positions (18,24), which differ from Anzell et al. (3) calculations. Notwithstanding these trends in body composition, our data indicate that over the past 13 years a general morphologic consistency within positions. These findings empirically support and extend the work of previous studies evaluating NFL player anthropometrics (18,23).
Both players and strength and conditioning coaches recognize the importance of, and are become more knowledgeable about, improving body composition and lean BM because of the health and physical performance consequences. For example, reductions in speed (e.g., 5-, 15-, and 40-yard dash), power, muscular endurance, reaction times, and overall movement efficiency were all associated with higher BF% (6,22). Increased lean BM is also positively associated with muscular strength (21). Several studies have demonstrated that physical performance measures (e.g., strength, power, speed, and agility) predict successful players (1,5,11), however, our data and others (18,23) support the notion of intraposition equality in physical characteristics among NFL players over the last few decades. Given the overall similarity in physical performance measures and body composition, it is unlikely that these metrics explain success in the NFL. Perhaps, it is more likely that these characteristics in combination with proper conditioning contribute in part to the high level of competitiveness within the league.
Beyond body composition and performance, several publications have observed high BM indexes in football players (particularly linemen) suggesting obesity and consequently increased cardiometabolic disease risk (14,15,30,31,32). It is important to note that BM index cannot distinguish between lean mass and fat mass, especially in athletes, limiting utility in correlating disease risk in this population (20). As opposed to sedentary men of similar BM, improved body composition and substantial physical activity has been shown to mitigate the effect of a large body size in all-cause and cardiovascular disease mortality (19). Moreover, our data demonstrate a trend towards a reduction in BF% (except TEs and running backs) and reduced or similar BM (except in TEs and DL) compared with NFL players from 1998 to 2009. These trends suggest increases in lean BM, and together represent positive risk factors for global cardiometabolic disease risk (17,32). Importantly, the improvements in morphology and physical activity levels do not categorically remove all cardiometabolic risk from this population, but they do represent an important factor warranting future investigation.
We recognize the limitations of this study. Firstly, player data were collected 10 weeks after the Super Bowl allowing for the potential of body composition, power, and strength changes. However, after 4 weeks, players were advised by the strength and conditioning staff to begin a periodized strength and conditioning program, this training regimen mitigated the decay of physical characteristics. For example, in an analysis of a smaller subset (n = 19) of returning players, 1RM bench press was not different from 1RM testing that occur at the end of the regular season vs. 10 weeks after the Super Bowl (mean difference [kg]; 95% CI = −1.55; −11.9,5.1; p = 0.409). The methodological differences among studies in the determination of %BF should be considered and interpreted with some degree of caution as the association between technologies (skinfold calipers [present study], hydrostatic weighing (29), and air displacement plethysmography [18, 32]) is comparable for most, but not all positions (18,29). Lastly, some players did not return to the NYG after the 2011 Super Bowl because of contractual changes and could not be included in the study limiting complete profiling of the NYG team that participated in Super Bowl XLVI.
Our study adds new players' data to prototypical position-specific databases that may be used as templates for comparison of players for draft selection or physical training. Anthropometric profiles did not dramatically differ over the past 13 years indicating homogeneous physical characteristics of players, although trends toward improved body composition in some positions were discernible and likely reflect changes in nutritional and training regimens. Given the anthropometric equity among NFL players, it appears that these physical characteristics have little association with successful outcomes in the NFL. However, the temporal consistency of the physical characteristics suggests that there are preferred or acceptable position-specific anthropometrics. This trend is likely explained by the relationships between position-specific demands and skillsets, prerequisite morphology and physical abilities, and the potential to succeed (1,5,6,11,21–23). We continue to develop a template for what the prototypical NFL player looks like in today's game.
The authors thank all of the athletes for their participation in the study. The authors also thank the graduate and undergraduate students who assisted in data collection. The authors have no conflicts of interest to report.
1. Allerheiligen B, Arce H, Arthur M, Chu D, Vermeil A, Lilja L, Semenick D, Ward B, Woicik M. Coaches' roundtable: Testing for football. Strength Cond J 5: 12–19, 1983.
2. American College of Sports Medicine. ACSM's Guidelines for Exercise Testing and Prescription (8th ed.). New York: Lippincott, Williams, and Watkins, 2006.
3. Anzell AR, Potteiger JA, Kraemer WJ, Otieno S. Changes in height, body weight, and body composition in American football players from 1942 to 2011. J Strength Cond Res 27: 277–284, 2013.
4. Baechle TR, Earle RW. Essentials of Strength Training and Conditioning. Champaign, IL: Human Kinetics Publishers, 2008.
5. Black W, Roundy E. Comparisons of size, strength, speed, and power in NCAA division 1-A football players. J Strength Cond Res 8: 80–85, 1994.
6. Brechue WF, Mayhew JL, Piper FC. Characteristics of sprint performance in college football players. J Strength Cond Res 24: 1169–1178, 2010.
7. Cohen J. Statistical Power Analysis for the Behavioral Sciences. Hillsdale, NJ: Lawrence Erlbaum, 1988.
8. Ebben WP, Blackard DO. Strength and conditioning practice of National Football League strength and conditioning coaches. J Strength Cond Res 15: 48–58, 2001.
9. Elam RP, Barth BI. The relationship between tibial nerve conduction velocity and selected strength and power variables in college football lineman. J Sports Med Phys Fitness 26: 398–405, 1986.
10. Fritz CO, Morris PE, Richler JJ. Effect size estimates: Current use, calculations, and interpretation. J Exp Psychol Gen 141: 2, 2012.
11. Fry AC, Kraemer WJ. Physical performance characteristics of American collegiate football players. J Strength Cond Res 5: 126–138, 1991.
12. Gettman LR. Fitness changes in professional football players during preseason conditioning. Phys Sports Med 92-96: 99–101, 1987.
13. Gleim G. The profiling of professional football players. Clin Sports Med 3: 185, 1984.
14. Harp JB, Hecht L. Obesity in the National Football League. JAMA 293: 1061–1062, 2005.
15. Hoffman JR, Kraemer WJ, Bhasin S, Storer T, Ratamess NA, Haff GG, Willoughby DS, Rogol AD. Position stand on androgen and human growth hormone use. J Strength Cond Res 23: S1–S59, 2009.
16. Jackson AS, Pollock ML. Practical assessment of body composition. Physician Sports Med 13: 76–90, 1985.
17. Janiszewski PM, Ross R. The utility of physical activity in the management of global cardiometabolic risk. Obesity (Silver Spring) 17: S3–S14, 2012.
18. Kraemer WJ, Torine JC, Silvestre R, French DN, Ratamess NA, Spiering BA, Hatfield DL, Vingren JL, Volek JS. Body size and composition of National Football League players. J Strength Cond Res 19: 485–489, 2005.
19. Lee DC, Blair SN, Jackson AS. Cardiorespiratory fitness, body composition, and all-cause and cardiovascular disease mortality in men. Am J Clin Nutr 69: 373–380, 1999.
20. Malina RM. Body composition in athletes: Assessment and estimated fatness. Clin Sports Med 26: 37, 2007.
21. Maughan R, Watson J, Weir J. Muscle strength and cross-sectional area in man: A comparison of strength-trained and untrained subjects. Br J Sports Med 18: 149–157, 1984.
22. Pincivero DM, Bompa TO. A physiological review of American football. Sports Med 23: 247, 1997.
23. Robbins DW. Positional physical characteristics of players drafted into the National Football League. J Strength Cond Res 25: 2661–2667, 2011.
24. Robbins DW, Goodale TL, Kuzmits FE, Adams AJ. Changes in the athletic profile of elite college American football players. J Strength Cond Res 27: 861–874, 2013.
25. Ross A, Leveritt M, Riek S. Neural influences on sprint running: Training adaptations and acute responses. Sports Med 31: 409–425, 2001.
26. Shields CL, Whitney FE, Zomar VD. Exercise performance of professional football players. Am J Sports Med 12: 455–459, 1984.
27. Sigward SM, Powers CM. The influence of gender on knee kinematics, kinetics and muscle activation patterns during side-step cutting. Clin Biomech (Bristol, Avon) 21: 41–48, 2006.
28. Siri WE. Body composition from fluid spaces and density: Analysis of methods. Brozek J., Henschel A., eds. Washington, DC: National Academy of Sciences, 1961. pp. 223–244.
29. Snow TK, Millard-Stafford M, Rosskopf LB. Body composition profile of NFL football players. J Strength Cond Res 12: 146–149, 1998.
30. Steffes GD, Megura AE, Adams J, Claytor RP, Ward RM, Horn TS, Potteiger JA. Prevalence of metabolic syndrome risk factors in high school and NCAA division I football players. J Strength Cond Res 27: 1749–1757, 2013.
31. Tarnopolsky MA. Building muscle: Nutrition to maximize bulk and strength adaptations to resistance exercise training. Eur J Sport Sci 8: 67–76, 2008.
32. Tucker AM, Vogel RA, Lincoln AE, Dunn RE, Ahrensfield DC, Allen TW, Castle LW, Heyer RA, Pellman EJ, Strollo PJ Jr. Prevalence of cardiovascular disease risk factors among National Football League players. JAMA 301: 2111–2119, 2009.
33. Wilmore J, Parr R, Haskell W, Costill D, Milburn L, Kerlan R. Football pros' strengths—And CV weakness—Charted. Phys Sports Med 4: 45–54, 1976.
34. Yessis MA. Strength and power training program for football linemen. Strength Cond J 5: 30–36, 1983.
body composition; BMI; strength training; position; NFL; American football
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