Strength and Conditioning of Athletes

by 

Tom McCullough MEd.

Davis, D.S., B. Barnette, J. Kiger, J. Mirasola, and S. Young. Physical characteristics that predict functional performance in Division I college football players. J. Strength Cond. Res. 18(1):115–120. 2004.

ABSTRACT.

Strength and conditioning professionals who work with collegiate football players focus much of their time and effort on developing programs to enhance athletic performance. Although there has been much speculation, there is little scientific evidence to suggest which combination of physical characteristics best predicts athletic performance in this population. The purpose of this investigation was to examine the relationship among 6 physical characteristics and 3 functional measures in college football players. Data were gathered on 46 NCAA Division I college football players. The 3 response variables were 36.6-m sprint, 18.3-m shuttle run, and vertical jump. The 6 regressor variables were height, weight, percentage of body fat, hamstring length, bench press, and hang clean. A stepwise multiple regression analysis was performed to screen for variables that predict physical performance. Regression analysis revealed clear prediction models for the 36.6-m sprint and 18.3- m shuttle run.The results of this investigation will help strength and conditioning specialists better understand the variables that predict athletic performance in Division I college football players.

I remember when I did my oral thesis in grad school my head of the department kept questioning me about why the variables I was testing in relation to physical characteristics of a D-I football team were of any importance. Honestly I had no answer except that is what I was taught and that is what I kept reading in the NSCA journals. In fact, I got a little angry that he kept asking me to prove the value of these testing attributes. Years later I understand his questioning and have to ask the same.

For years, these physical and functional variables have been used with minimal scientific evidence to support their contribution to predicting a player’s functional ability and performance on the field. Researchers have validate their studies by testing athletes that have been selected to be at D-I, D-II and D-III levels based on how they performed in these tests. Body weight, body fat, height, bench press, squats, power clean, 40y sprint, pro-agility (5-10-5) shuttle and vertical jump have all been previously used minimal scientific evidence to support their contribution to predicting a player’s functional ability and performance on the field by coaches the collegiate and pro levels.

In the Davis et. al (2004) study these factors were investigated to determine the relationship among 6 physical characteristics and 3 functional measures in college football players. Data were gathered on 46 NCAA Division I college football players. The 3 response variables were 36.6-m sprint (40y), 18.3-m (5-10-) shuttle run, and vertical jump. The 6 regressor variables were height, weight, percentage of body fat, hamstring length, bench press, and hang clean.

The 40 yard sprint has been used in most sports to determine straight ahead all out speed, the shuttle determines the athletes ability to change directions and accelerate and decelerate. The vertical jump has always been thought of a big predictor of lower body power and we all know that a bigger athlete at a lower body weight is preferable to many sports. The hang clean, well many in strength and conditioning believe the Olympic lifts are the key to any athletes success showing full body explosiveness. This particular study wanted to also see if hamstring length has any relevance and the bench press......most S&C coaches will tell you that it is a useless lift because no athlete competes on their backs.

After all of the testing was done and statistics run interestingly enough, none of the regressor variables were found to be predictors of vertical jump. WHAT???? You think this might have changed if they used squats? If it did does it even matter? Does having a good vertical mean you are going to be a good athlete or does it mean good athletes genetically have good verticals?

Intuitively, one might expect a strong positive relationship to exist between hang clean and vertical jump, since both activities require a similar explosive contraction of the back and lower-extremity extensors. However, the results of this investigation support the findings of Misner et al.(1988), who concluded that leg press strength and mean peak muscle power did not correlate with vertical jump performance.

The Davis et. al. study suggests that bench press, hang clean, body weight, and hamstring length when used together are good predictors of speed and agility in Division I college football players. Of the 4 significant regressor variables, body weight demonstrated the strongest relationship to both 36.6-m sprint and 18.3- m shuttle run time.

Ok, so that is common sense that the more body weight an athlete has the slower they will be and the harder it is for the to change directions quickly. Doesn't take research to prove this one. However, I do have a problem when strength coaches try to come up with data that predicts performance on the field. Coaches watch hours of games and game tape and still have a hard time predicting whether a high school athlete will perform well at the next level.

Davis et. al. determined the hang clean was found to be a good predictor of both the 36.6-m sprint and 18.3-m shuttle run. Since hang clean requires tremendous power output, it was not surprising to the authors that it had a strong relationship to 18.3-m shuttle run. Obviously since the hang clean needs a strong lower body, speed is affected. No big shock here. Had the squat been included I am sure the significance would have been quite a bit stronger.

As with hang clean, bench press (believe it or not) also showed a significant relationship to both 36.6-m sprint and 18.3-m shuttle run. It is not fully understood why such a relationship exists; however, it is hypothesized that it may be due to an increased ability to perform arm swing and aid in both direction change and force generation, which are required in the 18.3-m shuttle run. Arm swing? Are you kidding? Perhaps this study is telling us that both the hang clean and the bench press are very weak predictors of speed and agility?

As for the vertical jump, it seems that this study and others are not finding that the vertical jump is such a good predictor of athletic performance? In fact other researchers, (Dowling, 1993; Aragon-vargas, 1997; Young, 1999) have reported little or no relationship between lower-extremity muscular force production and vertical jump performance. So it may be apparent that my head of the department had some very good reasoning for questioning my research when I placed importance on the vertical jump as a determinant of lower body power and ultimately performance of athletes on the field. What I also find significant in vertical jumping ability was body weight and body fat. As body weight goes up, naturally vertical jump distance goes down, which is an inverse relationship. Body fat on the other hand, has a direct relationship with vertical jump. The less body fat one has the easier it is to jump.

ARAGON-VARGAS, L.F., AND M.M. GROSS. Kinesiological factors in vertical jump performance: Differences among individuals. J. Appl. Biomech. 13:24–44. 1997.

Abstract

The purpose of this study was to examine the changes in both the coordination patterns of segmental actions and the dynamics of vertical jumping that accompany changes in vertical jump performance (VJP) occurring from trial to trial in single subjects. Ground reaction forces and Video data were analyzed for 50 maximal vertical jumps for 8 subjects. It was possible to predict VJP from whole-body or even segmental kinematics and kinetics in spite of the small jump performance variability. Best whole body models included peak and average mechanical power, propulsion time, and peak negative impulse. Best segmental models included coordination variables and a few joint torques and powers. Contrary to expectations, VJP was lower for trials with a proximal-to-distal sequence of joint reversals.

DOWLING, J.J., AND L. VAMOS. Identification of kinetic and temporal factors related to vertical jump performance. J. Appl. Biomech. 9:95–110. 1993.

Abstract
Subjects performed maximum vertical jumps on a force platform to reveal whether resulting force-time curves could identify characteristics of good performances. Instantaneous power-time curves were also derived from the force-time curves. Eighteen temporal and kinetic variables were calculated from the force- and power-time curves and were compared with the takeoff velocities and maximum heights via correlation and multiple regression. The large variability in the patterns of force application between the subjects made it difficult to identify important characteristics of a good performance. Maximum positive power was found to be an excellent single predictor of height, but the best three-predictor model, not including maximum power, could only explain 66.2% of the height variance. A high maximum force 2 body weights) was found to be necessary but not sufficient for a good performance. Some subjects had low jumps in spite of generating high peak forces, which indicated that the pattern of force application was more important than strength.

YOUNG, W., G. WILSON, AND C. BYRNE. Relationship between strength qualities and performance in standing and run-up vertical jumps. J. Sport Med. Phys. Fitness. 39:285–293. 1999.

Abstract
BACKGROUND:The purpose of this investigation was to determine the relationships between the strength qualities of the leg extensor musculature and performance in vertical jumps (VJ) performed from a standing position and a run-up.
METHODS:Twenty-nine males with experience in jumping activities were tested for vertical jumping capacities with a standing VJ (double leg takeoff) and run-up jumps from a 1, 3, 5 and 7 stride approach (single leg takeoff). The speed-strength and maximum strength qualities of the leg extensors were assessed by tests involving concentric, stretch-shortening cycle (SSC) and isometric muscular actions. Pearson's correlations and stepwise multiple regression was performed to describe the relationships with jumping performance.
RESULTS:The speed-strength tests correlated significantly with both jump types (r = 0.55-0.82), but maximum strength did not. A drop jump test considered to measure reactive strength correlated more strongly with the run-up jump than the standing VJ. The standing VJ was best predicted by a low stretch load SSC test, whereas the run-up jump was best predicted by a model that also including the test of reactive strength.
CONCLUSION:The role of maximum strength in jumping performance was not clear but speed-strength qualities were considered important. It was concluded that reactive strength is relatively more important for jumping from a run-up than for the standing VJ, and this should be reflected by appropriate training methods and test protocols for the assessment of athletes who jump.

McLeod et al.(1983) examined the relationship between body composition and vertical jump ability in high school athletes. They found that vertical jump height decreased sharply as percentage of body fat increased above 10% in men and 19% in women. Additionally, they found that vertical jump height showed a positive correlation with percentage of body fat up to 10% in men.

MCLEOD, W.D., S.C. HUNTER, AND B. ETCHISON. Performance measurement and percent body fat in the high school athlete.Am. J. Sport Med. 11:390–397. 1983.

Abstract
Standards for performance have been derived from the preseason assessment of the high school athlete. The performance of 3,174 athletes during five performance tests was measured. The tests included dips, sit-ups, and pull-ups, in addition to grip strength measurement and vertical jump capability. Measurements were converted to the amount of work done or force developed. Nondimensional ratios were determined using the tables and empirical equations presented in this paper. These quantities were then compared to the percent body fat. The average performance of the athletes as determined by the testing procedures described herein decreases dramatically as the body fat increases above 10% in males and 19% in females.

Conclusion:  While it is nice to be able to collect as much data as you can when you train athletes, being able to predict performance on the playing field is like betting on horses. You are not going to know what athletes can really do until you see them actually perform on the playing field. That is why position coaches spend so much time watching game tape and seeing actually performances. The job of a strength coach from there seems to be to get the athletes a position coach recruits as big, as strong and as fast as possible. This is done by training these physical attributes in the gym and letting the athletes and position coaches teach them how to use the improved attributes on the playing field. Just because knowledge has been handed down for year after year doesn't mean there is any validity to it. As we have just seen for years, these variables have been used with minimal scientific evidence to support their contribution to predicting a player’s functional ability and performance on the field. None of them really seem to have any validity in predicting an athletes functional ability or performance on the playing field. A quick analyzation of what muscles are used in sport and all the strength coach has to do is strengthen those muscles. Absolute strength methods and dynamic strength methods will surely help any athlete to take advantage of what nature gave them. Instead of spending so much time trying to turn S&C into a rocket science and justifying jobs, learn to build bigger, stronger athletes and don't be afraid to try simpler, new methods if they are available.