Kinetic Energy Factors in Evaluation of Athletes by MLB Pitching

TECHNICAL NOTE

KINETIC ENERGY FACTORS ATHLETES JASON N. JONES,1 JOE W. PRIEST,2 1 3

AND

EVALUATION

DANIEL K. MARBLE,3

LifeStyleRx/ValleyCare Health System, Livermore, California; and 2Department of Health and Physical Education and Department of Math and Physics, Tarleton State University, Stephenville, Texas

ABSTRACT

INTRODUCTION

Jones, JN, Priest, JW, Marble, DK. Kinetic energy factors in evaluation of athletes. J Strength Cond Res 22(6): 2050– 2055, 2008—It is established that speed and agility are critical attributes of sports performance. Performance timing of runs during agility course testing can be used to estimate acceleration, speed, or quickness. The authors of this research effort also report the energy of motion, or kinetic energy of the athlete, which considers not only the speed but also the mass of the athlete. An electronic timer was used to determine total run times as well as split performance times during a new 60-yd ‘‘run-shuttle’’ test. This newly designed agility test takes advantage of the technological capabilities of a laser timing device. Separate times for each of four run segments were recorded and converted to average speeds (m s21) as well as a quantitative factor of merit defined as the ‘‘K-factor.’’ The purpose of this study was to describe the effects of training and to compare athletes and teams using measures of time, speed, and kinetic energy. Results of the analysis of total time on the 60-yd run-shuttle provided evidence of the effectiveness of the training programs. Split times of segments within the 60-yd runshuttle provided information not available from conventional agility tests. Average speeds and K-factors identified discriminating characteristics of otherwise similar athletes. Our findings support the conclusion that training programs and athletic performance may be evaluated using the 60-yd runshuttle with laser timer system. Coaches and trainers may find practical application of this technology for American football, soccer, basketball, baseball/softball, track and field, and field hockey.

KEY WORDS agility, performance, speed, K-factor

Address correspondence to Joe W. Priest, priest@tarleton.edu. 22(6)/2050–2055 Journal of Strength and Conditioning Research 2008 National Strength and Conditioning Association

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t is established that speed and agility play a crucial role in athletic performance. Also, the energy of motion is important in contact between athletes, implements, or objects. This kinetic energy is mathematically based on the agility and the mass of the athlete, and it can be transferred to other athletes (as in blocking and tackling in football), other objects (as in throwing a baseball or football), or indirectly through a bat (as in baseball) or a racquet (as in tennis or badminton). Kinetic energy of an athlete can be improved with training by either increasing the athlete’s ability to move (agility) and/or increasing his or her functional mass. Saltin and colleagues (9) demonstrated in 1976 that the training response to a conditioning program is highly specific; therefore, the performance test must closely resemble the activity (5). High-intensity exercise of short duration requires anaerobic fuel sources. Peak anaerobic performance usually occurs within 5–10 seconds of maximal effort. Thereafter, anaerobic power output gradually decreases as one becomes fatigued. Anaerobic capacity is defined as the total amount of power output for maximal exercise lasting up to 30 seconds (5,8). The Katch test (2) and the Wingate test (1) are routine performance tests that demonstrate that peak motor performance at high intensities varies greatly within the first few seconds, as do the anaerobic fuel sources (4). These performance tests on cycle ergometers are repeatable and specific to the ergometer on which they are performed (3,6), and, thus, they lack specificity to sports that require running leg power. The authors developed and provided measures of validity and reliability of a new 60-yd run-shuttle that measures agility during maximal performance of short duration. Manual, handheld timing devices allow measurement of speed. However, such devices are subject to human error and, therefore, provide inaccurate and unreliable information. Laser timing devices have become available and are capable of recording multiple times within the total time by repeated interruptions of a laser beam. These split times available from the laser timing provide information that is unavailable from conventional timers that capture only the total performance time. For instance, the total performance time of our 60-yd run-shuttle might suggest similar agility between two athletes. Split timing of segments of the run-shuttle can identify the

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wellness facility. Teams trained separately three times per week TABLE 1. Descriptive characteristics of the subjects. for 5 weeks in a competitive environment. Each workout conGroup Age (y) Height (m) Weight (kg) Sport sisted of a dynamic warm-up CGA 10.8 6 2.2 1.4 6 0.1 38.8 6 7.9 Gymnastics followed by timed rotations LS 11.1 6 2.4 1.6 6 0.1 45.3 6 5.9 Soccer through the power, speed, agility, GFB 16.2 6 1.2 1.81 6 0.07 87.8 6 16.1 Football and core strengthening stations. GBB 16.4 6 0.6 1.84 6 0.08 75.2 6 10.5 Basketball The power stations included two CGA = California Gymnastics Association; LS = Livermore Shock soccer; GFB = Granada to four sets of plyometric box Football; GBB = Granada Basketball. jumps, and quick jumps, power cleans, squats, and push press on the Vertimax (Genetic Potential, Inc., Tampa, Fla). The speed athlete who may have better agility in the initial 10 yd, and the stations included three to six sets of form running, resisted other athlete might have better agility in the final 20-yd sprinting, and jumps to sprint. The agility stations consisted of segment. These split-time data assist the coach and trainer in agility ladders and hurdles, box drills, 20- and 60-yd shuttles, evaluation of the attributes of the individual athlete and the and various sport-specific obstacle courses. The core team position or game situation for which he or she is best strengthening stations included three to four sets of lowersuited. In addition, pretraining and posttraining split times back, rectus abdominus, oblique, and hip-flexor exercises. provide the coach and trainer information about the Description of the New 60-yd Run-Shuttle Test effectiveness of a conditioning program. This test is different from the 60-yd shuttle commonly used by The purpose of the current research was to describe the the National Football League (7). The authors constructed effects of training on four teams and to evaluate athletes and a new 60-yd run-shuttle test to obtain more detailed compare teams using measures of time, speed, and kinetic information about athletic agility and to take advantage of energy. the split-timing capabilities of a new timing device. The METHODS distance in yards was selected to accommodate use of the American football field, where previous shuttle runs are Experimental Approach to the Problem commonly conducted. Performance data is then converted to To determine the agility of the athletes, a laser timing device the International System of Units for analysis and reporting. was used to provide split times during a shuttle run. Pre- and Runners started in one of two 3 3 3-ft taped areas on the posttraining total times on the agility test provided evidence floor on either side of the centerline of the shuttle. Subjects of the effectiveness of the training program. Calculated speeds began in either direction and then ran 5 yd over and 5 yd back and energy values from run-shuttle performance facilitated to the midline in segments 1 and 2, and 10 yd over and 10 yd individual and team comparisons and evaluations. back in segments 3 and 4. The total width of the shuttle path is Subjects 20 yd, and breadth is zero, which is expanded in Figure 1 to After institutional review board approval and signed informed clarify the segments. consent obtained from parents and/or guardians, young The Brower Speed-Trap II, a commercially available timing competitive athletes (n = 60) from the Bay Area in California device (see Figure 2), provided laser timing of criterion participated in testing and performance training. To represent measures. a variety of athletes, run-shuttle performance was compared The laser beam was positioned on two 100-cm-tall tripods within two similar groups of young female athletes perpendicular to and 2 m from both sides of the midline of the (California Gymnastics Association [CGA] and Livermore Shock soccer [LS]) and two similar groups of male high school team sport athletes (Granada Football [GFB] and Granada Basketball [GBB]). All athletes were previously active in their respective sports, and all were in the off-season during the time of the research activities. The physical characteristics of the subjects are shown in Table 1. Timing tests were conducted before and after 15 6 1 training sessions during a 5-week period. Exercise Conditioning Program

The primary author of this investigation completed all testing and performance training at an indoor hospital-based

Figure 1. Timed segments of the 60-yd run-shuttle. Arrows indicate direction of movement, position of the 4-in cones, and point of change of directions; Â¤ indicates point of laser beam interruption.

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Kinetic Energy Factors in Evaluation of Athletes

Figure 2. Component equipment of the laser timer, including the laser transmitter and receiver on extendable tripods, the sound generator that produced an audible buzzer on laser beam interruptions, and the remote data recorder and storage device held by the administrator.

shuttle path. Timing started on initial interruption of the beam (see Figure 3), and cumulative times were recorded at each point the athlete interrupted the laser beam at the run-shuttle midline. Performance times were recorded on interruption of the laser beam at 10, 20, 40, and 60 yd as the athlete ran back and forth on a straight line between the cones (see Figure 4). Athletes touched 4-in cones at each change of direction. Procedures

Reliability of the 60-yd run-shuttle obtained on test-retest from male (n = 23, age 21.0 6 2.3 years, height 1.82 6 0.08 m, weight 86.1 6 16.2 kg) and female athletes (n = 12, age 19.6 6 1.6 years, height 1.60 6 0.08 m, weight 54.4 6 4.0 kg) revealed a Pearson product-moment correlation of 0.96, p , 0.01.

Figure 4. Arrangement of the laser timer components for 60-yd run-shuttle test, scaled down for clarity.

Concurrent validity correlation between the new runshuttle and the standardized American Alliance of Health, Physical Education, Recreation, and Dance (AAHPERD) agility test was indicated by Pearson correlation (r = 0.93, p , 0.01). In the AAHPERD agility test, two parallel lines are placed on the floor 30 ft (9.14 m) apart. The student starts behind the first line, runs to the second line, picks up one wooden block, runs back to the first line, and places the wooden block behind the line. The student then runs back and picks up the second block, carrying it back across the first line (2). In the present study, the new 60-yd run-shuttle test was performed indoors on a hardwood floor in a controlled environment. The test administrator monitored the wireless handheld recorder that stored the split performance times. Because the shuttle segments were of different lengths, separate times for each of the four segments were recorded and converted to average speeds in meters per second, which produced common units for comparisons between segments. Determination of the average kinetic energy for each interval requires a detailed knowledge of the exact shape of the speed vs. time profile and cannot be calculated directly from split times. However, if it is assumed that the speed-time profile does not vary dramatically for various athletic groups, then it is possible to define an alternative factor of merit that is proportional to the athlete’s kinetic energy and that is easy to calculate. This parameter, which we call the K-factor, is reported in joules and defined as

1 M v2 2 where M (kg) is the athlete’s mass and V_ is the athlete’s average speed (m s21) for a given interval. Calculation of the K-factor provides a means for distinguishing between athletes with similar agility but different energy transfer capabilities attributable to their different masses. K ¼

Figure 3. Testing subject prepared to move to his right through the laser beam to initiate timing.

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Journal of Strength and Conditioning Research Statistical Analyses

All statistical procedures were performed using the Statistical Package for the Social Sciences (SPSS proprietary software version 14.0.1, SPSS Inc., Chicago, Ill) for Windows running on an XP Professional platform. The repeated-measures analysis of variance (ANOVA) procedure in the general linear model identified main effects and interactions of groups and segments of speed and K-factors. Univariate F values and Tukey honestly significant difference (HSD) post hoc analyses were used to make comparisons when significant main effects were identified. Data screening identified no violations of assumptions. Intraclass correlation was used for calculation of the reliability coefficient. The compare means procedure and paired t-tests identified pretest-to-posttest changes. A probability of less than 0.05 identified significance.

RESULTS Figure 5 shows that pretraining and posttraining times on the 60-yd run-shuttle demonstrated significant improvement in all four groups (p , 0.05) after 5 weeks of conditioning. The average improvement of teams CGA, LS, GFB, and GBB was 0.59 6 0.44, 0.38 6 0.25, 0.42 6 0.27, and 0.25 6 0.14 seconds, respectively. ANOVA of average posttest split segment speeds of the 60-yd run-shuttle demonstrated a significant main effect of segment (F[3, 168] = 480.4; p , 0.001) with significant group interaction (F[9,168] = 8.33; p , 0.001). Tukey HSD post hoc test identified a similar average speed for LS compared with GFB (p . 0.05). Pairwise comparisons between and among all other groups were different (p , 0.01, see Figure 6). Figure 7 shows generally increasing K-factor with successive segments in all groups, with the exception of CGA, which demonstrated a decrease K-factor from segment 3 to segment 4. ANOVA of average posttest split segment

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K-factors of the 60-yd run-shuttle demonstrated a significant main effect of segment (F[3, 168] = 385.3; p , 0.001) with significant group interaction (F[9,168] = 37.2; p , 0.001). Tukey HSD post hoc test identified similar average K-factors for GFB compared with GBB (p . 0.05). Pairwise comparisons between and among all other groups were different (p , 0.01, see Figure 7). The younger female team LS and the older male team GFB had similar average speeds at each of the four split segments (p . 0.05). However, calculation of average K-factors for these two groups revealed differences between the groups, with team GFB having a nearly twofold-greater energy of motion at all split segments compared with team LS. Although teams GFB and GBB had different average speeds at each segment (Figure 6), the distinction disappeared in the pairwise comparison of average K-factors for the two teams (similar at 489 6 70, 683 6 91, 887 6 145, and 942 6 136 J, for split segments 1â&#x20AC;&#x201C;4, respectively).

DISCUSSION Analysis of agility performance as determined by the new 60-yd run-shuttle provided information unavailable from conventional agility tests. Indications of anaerobic peak power, capacity, and fatigue afford the coach a better understanding of individual athletic assets and, therefore, better team construction. In the present study, changes in the pretraining to posttraining performance have demonstrated the effectiveness of a well-designed, well-administered 5-week conditioning program. The fact that not all athletes within the groups demonstrated improvements in all segments provides valuable insight into specific individual training needs. Some athletes that showed little improvement in segments 1 and 2 may need more high-intensity peak power conditioning, whereas others who did not improve in segments 3 and 4 may need additional anaerobic endurance training. This conclusion is supported by a recent study reporting deterioration of running mechanics coincident with the onset of blood lactate accumulation (10). Comparison of team agility performance revealed similarities among the young female and among the older male teams, obvious differences between the genders, and some unexpected similarities between the genders and differences among members of individual teams. Our findings support the use of the 60-yd run-shuttle with laser timer system as a general test of agility and as an evaluation of players at different positions and training programs for American football, soccer, basketball, baseball/softball, track and field, field hockey, and lacrosse.

PRACTICAL APPLICATIONS Figure 5. Pretest and posttest 60-yd run-shuttle times for all groups. Values are means 6 SD. *Indicates p , 0.001.

The coach has the responsibility to develop competitive skills in the athlete and to use those individual skills in assembling a team. The more informed a coach is, the better equipped he or she will be to accomplish both chores. Information VOLUME 22 | NUMBER 6 | NOVEMBER 2008 |

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Kinetic Energy Factors in Evaluation of Athletes and different average speeds for the male groups GFB and GBB, yet similar average speeds for the younger female LS and the older male GFB. This demonstrates how time alone may provide incomplete and misleading information. The average speeds found in successive split segments were indicative of running starts for segment 2 compared with segment 1, and for segment 4 compared with segment 3. In all groups, the second 10-yd segment was faster than the first. In three of the four groups, the final segment was the fastest. Analysis of individual split segment speeds identified that Figure 6. Average speeds for all groups during each split segment. Values are means 6 SD. *Indicates significant 12 of the 14 individuals in the (p , 0.01) difference from all other groups within each segment. CGA group recorded slower segment 4 speeds compared with segment 3. On teams LS, GFB, and GBB, four, three, and two individuals, respectively, obtained from the 60-yd run-shuttle provides critical information to the trainer and coach. For example, in the had slower segment 4 speeds compared with segment 3. present study, the group average speeds for the 60-yd runThese results suggest an anaerobic fatigue factor in particular shuttle might be expected to be similar between the female individuals of every team. Perhaps additional interval training groups and between the male groups and different between methods might be included in their training regimens aimed at improving anaerobic capacity. groups of different genders. However, our analysis identified The wide disparity in average K-factors between groups LS different average speeds for the female groups LS and CGA and CGA is attributable to a combination of larger mass (45.3 6 5.9 and 38.8 6 7.9 kg, respectively) and higher average speeds in three of the four split segments. The calculated average K-factors for the male athletes in teams GFB and GBB were similar, although they had different (p , 0.05) mass (GFB . GBB) and average speeds (GBB . GFB) within the 60-yd run-shuttle splits. Similarity in average speed might suggest similar athletic assets; however, with the calculation of K-factors, distinction between otherwise identical individuals assists the coach in identifying the sport or position in which an athlete may make the greatest team Figure 7. Calculated K-factors of all groups at each segment of the 60-yd run-shuttle. *Indicates significant contribution. For example, difference (p , 0.05) from CGA, GFB, and GBB. #Indicates significant difference from GFB and GBB. those athletes identified by

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Journal of Strength and Conditioning Research K-factors to have the greatest energy of motion have the greatest capacity for energy transfer (on contact with other athletes, or with the ball or projectile). Furthermore, this specific information also points out to the trainer the special conditioning needs of these identified individuals. Closer analysis of individual K-factors within shuttle segments on team GFB produce revealing information. The highest individual K-factor in segment 1 (583 J) was neither the biggest (eight teammates were heavier) nor the fastest athlete (three teammates were equal or faster). His energy of motion during 2.5 seconds of acceleration, deceleration, stop, change directions, acceleration suggests that this 1.78-m, 85-kg (or 5’10", 187 lb) athlete might excel at a position that requires the most explosive power. In football terms, perhaps he is the nose tackle or some other offensive or defensive lineman. This same athlete ranked sixth on his team in segment 2, eighth in segment 3, and fourth in segment 4. The athlete (1.80 m, 84.5 kg; or 5#11", 186 lb) who had the highest K-factor in the second segment was also among the fastest in that split segment. However, his first split segment time ranked 12th of the 15 athletes in GFB. This athlete ranked sixth in both segments 3 and 4. This suggests that his peak energy of motion occurs at about 5 seconds after a comparatively slow start and deteriorates on movement times . 5 seconds. In football terms, he may perform best as a linebacker where more movement is required to get to an impact point. The individual (1.80 m, 94.5 kg; or 5#11", 208 lb) with the highest K-factors in both segments 3 and 4 (1097 and 1164 J, respectively) was neither the biggest (seven teammates were heavier) nor the fastest (two and three athletes were faster, respectively) within these segments, but his energy of motion was superior. His K-factors in segments 1 and 2 ranked sixth and third, respectively, among team GFB. This athlete’s best contact-sport performance might be where maximal energy of motion is required after 5 seconds. In football terms, he may be the strong safety or some other position where more anaerobic endurance contributes to success at that position. Improvement in K-factor can be accomplished by either an increase in functional muscle mass or an increase in running speed. Furthermore, in some athletes who lose body mass with training, energy of motion may be maintained by replacing fat loss with muscle gain and/or increase in movement skills including speed and agility. Again, this information provides the watchful trainer with feedback that may be used to modify individual training regimens. Specifically, the K-factor can be used to identify training needs for particular individuals or even team positions that others may not need. Certainly, developing individual athletes and training programs and determining the effects of conditioning are complex matters. Conventional use of the stopwatch, scales, and tape measure provide important pieces of the puzzle, but determining the energy of motion adds a new dimension.

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Peak anaerobic power, capacity, and fatigue can be derived from other criterion measures such as cycle ergometry, but timing of the segments of the 60-yd run-shuttle has an advantage in the identification of running speed and energy patterns. Our findings support the use of the 60-yd run-shuttle with laser timer system for a general test of agility and for evaluation of training programs, as well as players at different positions for American football, soccer, basketball, baseball/softball, track and field, field hockey, and lacrosse. Future studies will provide additional information on the unique aspects of the run-shuttle and laser timer systems.

ACKNOWLEDGEMENTS The authors wish to acknowledge the inspiration of the late Dr. R. Don Hagan, as well as Drs. Joe Gillespie and Bob Newby for their assistance with data reduction and statistical treatment of the data. The results of the present study do not constitute endorsement of products used in the study by the authors or the NSCA. The authors were involved in the planning, purchase of the laser timer, execution, and publication of the research effort and had no other interest in, relationship to, or ownership of the Brower Timing Systems Company. This study was not a part of any funded grant. Two separate Speed-Trap II systems were purchased by the two facilities represented by the authors.

REFERENCES 1. Bar-Or, O. The Wingate Anaerobic Test: an update on methodology, reliability, and validity. Sports Med 4: 381, 1987. 2. Baumgartner, TA and Jackson, AS. Measurement for Evaluation in Physical Education and Exercise Science (5th ed.). Dubuque, Iowa: William C. Brown, Inc., 1995. 3. Bentley, DJ, McNaughton, LR, Thompson, D, Vleck, VE, and Batterham, AM. Peak power output, the lactate threshold, and time trial performance in cyclists. Med Sci Sports Exerc 33: 2077–2081, 2001. 4. Katch, VL. Kinetics of oxygen uptake and recovery for supramaximal work of short duration. Int Z Angew Physiol 31: 197, 1973. 5. McArdle, WD, Katch, FI, and Katch, VL. Exercise Physiology: Energy, Nutrition, and Human Performance (6th ed.). Philadelphia: Lippincott Williams & Wilkins, 2007. 6. McGawlay, K and Bishop, D. Reliability of 5 x 6-s maximal cycling repeated-sprint test in trained female team-sport athletes. Eur J Appl Physiol 98: 383–393, 2006. 7. McGee, KJ and Burkett, LN. The National Football League Combine: a reliable predictor of draft status? J Strength Cond Res 17: 6–11, 2003. 8. Nieman, DC. Exercise Testing and Prescription: A Health-Related Approach Mountain View, Calif: Mayfield Publishing Co., 1999. 9. Saltin, B, Nazar, K, Costill, DL, Stein, E, Jannson, E, Essen, B, and Gollnick, D. The nature of the training response: peripheral and central adaptations to one-legged exercise. Acta Physiol Scand 96: 289, 1976. 10. Shim, J, Acevedo, EO, Kraemer, RR, Haltom, RW, and Tryniecki, JL. Kinematic changes at intensities proximal to onset of lactate accumulation. J Sports Med Phys Fitness 43: 274–278, 2003.

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