Strength and power development have been demonstrated to either indirectly or directly improve athletic performance, building the foundation for all other athletic qualities (11,19,32). Training for strength elicits several physiological adaptations that contribute to increased athletic performance (11,19,32). These adaptations include an increase in muscle fiber size, muscular strength, the rate of force development, anaerobic power, and fat-free mass (11,19,32), leading to the development of critical elements specific to any and all athletic movements such as flexibility, balance, coordination, and the ability of an athlete to produce force and power (11,19,31,32). Increases in power and force outputs are likely to benefit many sports, including those involving a ball striking component (10,18,33).
Golf is classified as an intermittent sport that combines moderately paced walking, standing in a golf posture, and ball striking (31). Maximal swing speed has been shown to be directly proportional to the distance a golf ball will travel (9,39) and is influenced by the body's ability to transfer force to the golf ball (5,15,34,38). Golf is generally considered a sport of technique and strategy rather than a sport reliant on physical fitness, despite substantial research showing high levels of muscle activity and power throughout the golf swing (5,10,12,17,24–26,30,35,38). Research has demonstrated that strength, power, and flexibility are related to club head speed (CHS), potentially resulting in a significant increase in drive distance (5,9,17,22,24,27,30,36,38,39). An analysis by Fradkin et al. (9) found that CHS was highly correlated (r = 0.95) with overall golf performance. Thompson et al. (34) found that an 8-week progressive functional strength training program increased CHS in older golfers. Additionally, traditional measures of lower body power, including the squat jump (ICC = 0.96) and countermovement jump (ICC = 0.98), have been found to correlate strongly with CHS (27). Thus, it is reasonable to conclude that muscular strength and power play an important role in CHS. Not only is resistance training used to maintain performance and avoid injury in professional golfers (24,36), it is also used to increase performance by improving rotational power (31). Therefore, when planning a strength program for golf, the objectives should be designed to improve the golfer's muscular strength and power (9,10,12,17,20,22,24,26,30,35,38).
The primary purpose of this study was to determine the effects of a golf-specific strength and power-focused resistance training program on CHS. The secondary purpose of this study was to assess the relationships between CHS and vertical countermovement jump (CMJ), squat (SQ), deadlift (DL), and power clean (PC) performance. It was hypothesized that improving strength via the SQ and DL, and explosive power via the PC and CMJ, would result in significant improvements in CHS.
Experimental Approach to the Problem
This study involved an 8-week intervention where participants were stratified by sex and then randomly placed into a control or intervention group. Six of the participants (n = 3 male, n = 3 female) were placed in the control group, which completed an 8-week resistance training program focusing on low-load, unilateral, and rotational resistance training typical of many collegiate golfers (Table 1). The other 6 participants (n = 3 male, n = 3 female) performed an 8-week strength and power training program with an emphasis on high-load, bilateral, weightlifting, and powerlifting movements (Tables 2 and 3). Both groups continued to participate in the teams' regular golf practice. The 8-week strength and power training program emphasized strength and power adaptations by targeting intensities, volume, and exercise selections that result in strength and power adaptations (11,19).
The study was approved by the Adams State University Institutional Review Board before any testing. All subjects voluntarily agreed to participate and signed the informed consent forms. The participants consisted of 6 male and 6 female NCAA Division II collegiate golfers aged 18–23 years old (mean ± SD; 20.3 ± 1.5 years). Baseline descriptive data are summarized in Table 4. All subjects had 1–5 years (2.67 ± 1.37 years) of weekly resistance training experience, were free from any musculoskeletal injuries for at least 3 months before the study, and had a minimum of 1 year of collegiate golf experience.
After participants were assigned to either the control or intervention group, they underwent baseline testing consisting of CHS measured by a vertical computerized photo-sensing timer (BatMaxx 5500; Technasport, Lakeville, MN, USA), a device that measures the amount of time a moving object takes to pass through 2 laser beams to 2 sensors (13). The photo-sensing times have been found to have a mean test–retest reliability of r > 0.89 (13). Countermovement jump height was measured via contact mat (Just Jump, Probotics Inc., Huntsville, AL, USA) (21). The contact mat calculates vertical jump height by measuring the time between ground contacts from takeoff to landing. Despite systematically overestimating vertical jump height, contact mats has been found to have nearly perfect correlations to 3-camera motion capture (r = 0.97, +0.5 ± 0.12 cm) (21) and force plates (r = 0.99, +1.55 ± 0.02 cm) (29). One-repetition max (1RM) testing for PC, BS, and DL was conducted according to the National Strength and Conditioning Association's (NSCA) testing protocol (12).
Club Head Speed and Vertical Jump Assessment
Participants were instructed to use their natural swing with maximal effort before the CHS measurement. Each participant was allowed 3 practice swings followed by a self-selected rest period of 2–5 minutes. The participants then performed 3 maximal effort swings with 2 minutes of rest between attempts. The average of the 3 swing velocities and peak swing velocity, defined as the highest recorded swing velocity, were recorded for analysis. Five minutes after the final swing, the participants began the CMJ testing protocol. To adequately prepare the tissues of the lower leg and potentiate jump performance, each participant was instructed to complete ankle hops for 2 sets of 10 repetitions (2). The participants stood in front of the jump mat until instructed to step onto the device. Participants then performed a maximal effort countermovement jump before landing on the mat. Each jump was performed while positioning the hands on the hips to minimize the contribution of the upper extremities and to increase reliability (23). Each participant was given 3 attempts separated by 2 minutes of rest. Both peak CMJ height and an average height of the 3 CMJ's performed were used for the statistical analysis.
Maximal Strength Assessment
Forty-eight hours later, the participants performed a 1RM testing battery of, in order, the PC, SQ, and DL. The protocol established by the NSCA (2) and also used by Alvarez et al. (1) was as follows: 5–10 repetitions with a light resistance, 5 repetitions at 60%, 3 repetitions at 75%, 2 repetitions at 85%, 1 repetition at 90%, and 1 repetition at 95% of predicted 1RM. After the specific warm-up protocol was completed, participants were given a maximum of 4 attempts to achieve their 1RM (1,2). Each movement followed the same protocol and was separated by a 5-minute rest between exercises (1,2). All attempts were separated by 3 to 5 minutes of rest and monitored by an experienced strength and conditioning coach.
The participants then proceeded to undergo an 8-week resistance training program. The intervention group performed a golf-specific, high-load strength, and power resistance training intervention (Tables 2 and 3). The control group performed a low-load training program (Table 1). The participants trained 3 days a week, with at least 1 day of recovery separating each training session. Scheduled team training took place on the Monday, Wednesday, and Friday of each week. If a session(s) was missed, the participant(s) was allowed to complete it on the following day. After the 8-week intervention, participants were given 72 hours to rest before beginning the postintervention testing, which followed the same procedures as the baseline testing.
Results are expressed as mean ± SD. The statistical analyses were performed using the 2016 SPSS Version 24 (IBM Corporation, Armonk, NY, USA) statistical analysis software. Assumptions were checked visually with normality and residual plots, and the Levene's test for variance homogeneity. The intraclass correlation coefficient (ICC) using a 2-way random effects model and 95% confidence intervals (CI) was computed to evaluate the reliability of CHS assessed with the photo-sensing device within each testing session along with the standard error of the mean (SEM) and coefficient of variation (CV) (37). The ICC for baseline testing CHS was 0.91 (95% CI [0.79–0.97]), SEM = 6.36 km·h−1, and CV = 3.9%. The ICC for posttesting CHS was 0.96 (95% CI [0.90–0.99]), SEM = 4.44 km·h−1, and CV = 2.7%. Reliability metrics for CHS trials during both sessions indicated acceptable reliability. Two-tailed dependent t-tests were used to determine within-group changes (baseline to posttest) for both the control and intervention group for each dependent variable. A nonparametric Wilcoxon signed-rank test was used for variables violating assumptions. Difference scores were computed for each variable by subtracting the pretest value from the posttest value. Differences between the control and intervention group were evaluated by 2-tailed independent t-tests. For variables that violated assumptions, independent samples Mann–Whitney U-tests were used to evaluate differences between the control and intervention group. Because of the limited sample size, Hedge's effect sizes (ES) were calculated to measure the magnitude of practical effect (6). As recommended by Rhea (28), effect sizes were interpreted as: trivial <0.35, small = 0.35–0.80, medium = 0.80–1.50, and large >1.50. Hedge's g ≥ 0.35 was considered to be a practically important difference. Correlation analysis was performed for dependent variables using a Pearson (r) product–moment correlation test. Correlation coefficients of 0.1, 0.3, 0.5, 0.7 and 0.9 were considered small, moderate, large, very large and nearly perfect, respectively (14). A probability level of p ≤ 0.05 was considered statistically significant. For parametric tests, 95% CI of the sample mean difference is reported; for non-parametric tests, 95% CI around the sample median is reported.
Despite minor illnesses and scheduling issues causing 3 participants to undertake an altered training schedule, all participants (n = 12) fully completed each training session. Although the intervention group scored higher on most variables at baseline, no statistically significant differences were found between groups for any variable (Table 4, p > 0.05).
The pretest and posttest results for the control and intervention group are shown in Tables 5 and 6. The control group exhibited no statistically significant changes from baseline to posttest for all dependent variables, except for a decrease in average CHS (p = 0.028, 95% CI [−13.41, −0.054], ES = 0.20). The intervention group displayed a significant increase in average CHS (p = 0.024, 95% CI [1.01, 9.43], ES = 0.38), 1RM back squat (p = 0.036, 95% CI [1.60, 32.42], ES = 0.39), 1RM deadlift (p = 0.005, 95% CI [6.59, 22.14], ES = 0.32), 1RM clean (p = 0.003, 95% CI [7.21, 21.16], ES = 0.67), average CMJ (p = 0.012, 95% CI [1.83, 9.35], ES = 0.56), and peak CMJ (p = 0.009, 95% CI [2.12, 9.31], ES = 0.55).
There were statistically significant differences in outcomes of strength, power, and CHS between the control and intervention groups (Tables 5, 6 and Figure 1). Compared with the control group, the intervention group's change scores were significantly higher for average CHS (p = 0.005, 95% CI [−18.91, −4.51], ES = 2.02), 1RM back squat (p = 0.026, 95% CI [−14.23, 1.02], ES = 1.11), 1RM power clean (p = 0.031, 95% CI [−16.06, −0.96], ES = 1.34), average CMJ (p = 0.024, 95% CI [−9.65, −0.86], ES = 1.42), and peak CMJ (p = 0.019, 95% CI [−10.34, −1.17], ES = 1.49). No statistically significant results were found between groups for change in peak CHS (p = 0.12, 95% CI [−18.04, 2.54], ES = 0.89) or change in 1RM deadlift (p = 0.087, 95% CI [−17.26, 1.39], ES = 1.01) despite moderate effect sizes.
Correlation analysis revealed significant positive associations with posttest measures of CHS and strength and power indicators in this study (Table 7). Both peak and average CHS had moderate to large correlations with 1RM back squat (r = 0.64, p = 0.025 and r = 0.67, p = 0.016, respectively). Additionally, peak and average CHS were moderately correlated with 1RM deadlift (r = 0.54 and 0.57, respectively) although these correlations were not quite statistically significant (p = 0.068 and 0.054, respectively). Similarly, average and peak CHS had very large correlations with 1RM clean (r = 0.70, p = 0.012 and r = 0.72, p = 0.008, respectively), average CMJ (r = 0.73, p = 0.007, and r = 0.77, p = 0.004, respectively), and peak CMJ (r = 0.72, p = 0.009 and r = 0.76, p = 0.004, respectively).
The purpose of this study was to examine if an 8-week strength and power resistance training program would result in greater increases in CHS compared with a generic resistance training protocol in collegiate golfers. The present study demonstrated a significantly higher change in average CHS in the strength and power group when compared to the control group. Additionally, results display large to very large correlations between CHS and the barbell exercises BS (r = 0.64, p = 0.025) and PC (r = 0.70, p = 0.016). Because of the greater increases in strength and CHS evidenced by the intervention group compared with the control group, the data from the current study support the hypothesis that the implementation of a barbell-focused resistance training program is associated with an increase in CHS.
These findings are supported by Fletcher and Hartwell (7) who examined the effects of an 8-week combined weights and plyometric training program on golf drive performance. The intervention group participated in an 8-week strength training program with similar exercises, volumes, and intensities to the current study (7). Fletcher and Hartwell's (7) intervention group increased CHS by 1.5% resulting in an increased drive distance of 4.3%, whereas the control group increased CHS by 0.5%, but slightly decreased drive distance by 0.7%. The findings in the current study are also supported by Westcott et al.'s (39) research examining the effects of an 8-week generic strength and flexibility program on CHS, strength, and range of motion, whereas the control group only performed pretreatment and posttreatment measures of CHS, strength, and flexibility. After the 8-week intervention, the intervention group showed large increases (56%) in strength, yielding a 6.0% increase in CHS. The control group showed no change in CHS posting a 149.9 km·h−1 pretest score compared with 149.7 km·h−1 posttest score (39). Although the methods used to elicit strength and power in the current study differ from the existing literature, the focus on increasing strength and power remained consistent and ultimately resulted in statistically significant and practically meaningful improvements in CHS (3.2%, p = 0.024, ES = 0.38) with experienced athletes. Although the participants in Westcott et al.'s (39) study experienced a 6% increase in CHS compared with the 3.2% increase observed in the current study, it is important to note that the golfers included in Westcott's intervention group began with an average CHS of 132.6 km·h−1 compared with the baseline of 163.1 km·h−1 in the current study.
It was also an objective of the present study to examine if an increase in CMJ height would correlate with an increase in CHS, as CMJ height is a common measure of explosive ability. There were very large correlations between CMJ height and CHS which supports previous findings that jumping has a strong relationship with CHS (1,24,38). Research by Lewis et al. (24) found a very large correlation (r = 0.82, p ≤ 0.05) between performance in the squat jump and CHS in professional golfers. Lewis et al. (24) also discovered that the squat jump and the seated medicine-ball throw explained 74% of the variance in CHS between young (<30 years) and older (>30 years) golfers. Wells et al. (38) found that unilateral jump height with the dominant (r = 0.77, p ≤ 0.05) and nondominant leg (r = 0.73, p ≤ 0.05) are positively correlated with drive performance and CHS in male and female Canadian national golf team members. Therefore, improving jump performance by including explosive lower body exercises, such as plyometric or weightlifting movements, may be important in developing and maintaining CHS and thus driving performance.
Transfer of training is a factor that should be taken into consideration when implementing strength and power training in athletes, including golfers (1,40). Although strength and power improvements can be observed in only a few weeks, it may take much longer to see an improvement in sports performance (1,40). An 18-week training study by Alvarez et al. (1) found that, although strength and power measures improved significantly in only 6 weeks of training, it took an additional 6 weeks of golf-specific training to see an improvement in driving performance. Therefore, future studies may wish to examine the effect of different resistance training programs on the biomechanics of the golf swing by using motion capture, as a negative change in swing technique or range of motion could have unwanted effects on live golf performance (15,30,40).
Although the primary aim of this study was accomplished, there are several limitations and suggestions for future research. Firstly, the addition of a true control group that only participated in golf practices would have been ideal. However, when researching sports teams, a control group is often not practical since excluding some athletes from all resistance training may compromise the overall development of the team. Furthermore, finding NCAA or low handicap golfers is typically difficult (1,4), so it was decided not to further reduce the number of subjects in each group. Secondly, total volume and load were not equated between the 2 groups in the study. Therefore, it is possible that the larger increase in strength and CHS experienced by the intervention group compared with the control group could have been due to the increased training load and not necessarily exercise selection (3,8). However, this limitation would be difficult to avoid as one of the well-accepted advantages to barbell training is increased muscular loading compared with dumbbells or bodyweight movements. It may have also been worthwhile to measure changes in grip strength from the 2 resistance training programs as grip strength has been found to increase CHS in skilled golfers (4,38). It is also important to point out that the strength testing variables of the PC, BS, and DL were only performed in training by the intervention group, and the CMJ was the only variable measured that was not directly trained by either group. Therefore, it would be logical that only the intervention group would improve in the barbell movements because of a learning effect. Additionally, including a midtest between strength and power phases would have allowed the researchers to extricate the effects of each block individually. Similarly, including a posttesting battery at a future date may have been useful. Although a majority of trainees have been found to completely recover from resistance training in under 72 hours, some individuals may require as many as 120 hours (16). Lastly, although the vertical photo-sensing device used to estimate bat speed has been found to be highly reliable (13), it has not been previously used to estimate CHS via the golf swing. Therefore, caution should be exercised when directly comparing CHS in the current study with previous or future research. Although a reliability study was not purposely conducted, the ICC, SEM, and CV were calculated within each testing session and revealed good reliability metrics with high ICC and low CV. Our results suggest the photo-sensing device may have the ability to assess CHS during a golf swing consistently within a session.
Strength and conditioning professionals may be able to apply the findings from this study to determine the most efficient method in designing resistance programs for high-level golfers. The results of the current study have shown that incorporating heavy strength and power resistance training has a positive effect on CHS in experienced golfers. These results may provide a reference for designing resistance training for golf athletes. However, practitioners should also pay attention to factors other than strength and power. Although golf is generally considered a skill-based sport, a well-rounded program, including flexibility, balance, sport-specific movements, and technique, needs to be considered when designing a physical preparation program for golfers (1,10,24,26,30,38). Along with the aforementioned qualities, aiming to develop strength and power of the prime movers through weightlifting and powerlifting derivatives result in greater CHS, whereas an incomplete strength and conditioning program without significant overload and explosive movements can result in detrimental effects on performance.
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