Grip Strength Symmetries in Division I College Baseball Pitchers and Hitters

Integrating strength and conditioning coaches and programs for baseball athletes has yielded positive performance outcomes for both hitting and throwing. Among a variety of baseball-specific testing batter, grip strength has shown to significantly correlate with increased swing and throwing velocity. However, no investigations have examined grip strength asymmetries for hitters and pitchers. PURPOSE: The purpose of this study was to examine differences between right and left arm grip strength of baseball pitchers and hitters. METHODS: Division I collegiate baseball players (n = 45, height. (183.52 ± 11.77 cm) weight. (85.96 ± 17.73 kg.) performed dominate and non-dominate maximal grip strength at position specific arm and forearm orientation utilizing the Jamar Hydraulic Hand Dynamometer. Hitters (n = 22) performed grip strength assessments at 90-degree elbow flexion, neutral forearm orientation (NDN). Pitchers (n = 23) performed grip strength assessments at 90-degree elbow flexion, pronated forearm orientation (NDP). Three attempts were permitted to exert maximal force, recorded in kilograms (kg) – highest exerted force was recorded and used for analysis. An independent samples t-test (p \u3c .05) was employed to assess dominate and non-dominate grip strength differences. RESULT: The results indicated no significant differences between pitchers’ dominate NDP (57.39 ± 7.49 kg) and non-dominate NDP (56.0 ± 7.63 kg), t(44) = .624, p = .966. Likewise, hitters presented no significant difference between dominate NDN (60.68 ± 10.15 kg) and non-dominate NDN (55.27 ± 11.31 kg) t(42) = 1.669, p = .264. CONCLUSION: Contrary to common belief, these results suggest baseball players do not present significant grip strength asymmetries. While baseball skills (i.e., throwing, hitting) require adequate grip strength to produce favorable performances outcomes, these single arm/hand movements do not place baseball players in a concerning asymmetrical grip strength state. Utilization of both hands during hitting provides reasonable explanations for the results of hitters. For pitchers, glove movement and skill, along with typical strength and conditioning may contribute to improvements in non-dominate grip strength. Furthermore, these results suggest equivalent bilateral strength may be a necessity of collegiate baseball players

Correlation Between Grip Strength at Various Arm Orientations and Hitting Performance Metrics of Division I Collegiate Baseball Players

Dominate and non-dominate grip strength (GS) significantly correlated with bat speed (BS) in the sport of baseball. Various arm orientations occur throughout the swing; moreover, additional metrics beyond BS are indicative of baseball hitting performance. The correlation between various GS and hitting outcomes have not been empirically examined. PURPOSE: The aim of the current investigation was to examine the relationship of GS at various arm angles to various hitting performance metrics. METHODS: Division I collegiate baseball players (n = 17; height: 180.92 ± 5.61 cm; weight: 82.1 ± 11.12 kg) performed dominate and non-dominate maximal GS at five different arm and forearm orientations utilizing the Jamar Hydraulic Hand Dynamometer: 90-degree elbow flexion with (1) neutral (NDN), (2) supinated (NDS), and (3) pronated (NDP) forearm placement, as well as 120-degree elbow extension with 90-degree shoulder abduction with (4) supinated (AS) and (5) neutral (AN) forearm grips. At each angle, three attempts were permitted to exert maximal force, recorded in kg. Hitting metrics were gathered via Blast Motion Bat Sensors and Yakkertek Ball-Tracking System - metrics included: BS, peak hand speed (PHS), vertical bat angle (VBA), time to contact (TTC), attack angle (AA), power (PW), on plane efficiency (OPE), plane score (PS), rotational acceleration (RA), early connection (EC), connection at impact (CAI), as well as average exit-velocity (AEV), peak exit-velocity (PEV), hard hit percentage (HHP), damage percentage (DP), and average launch angle (ALA). A Pearson product-moment correlation coefficient (p \u3c .05) was employed to assess the relationship between GS and hitting performance. RESULT: Positive significant correlations were recognized between the following variables: dominate NDN and HHP (r = .559, p = .02), DP (r = .647, p = .007), and BS (r = .515, p = .034); non-dominate NDP and HHP (r = .497, p = .042), DP (r = .664, p = .005), and TTC (r = .519, p = .033); and non-dominate NDS and DP (r = .770, p \u3c .001), PS (r = .515, p = .035), OPE (r = .510, p = .036). A negative significant relationship was identified between non-dominate NDS and EC (r = -.629, p = -.007), and CAI (r = -.587, p = -.013). CONCLUSION: Supporting previous investigations, these results suggest dominate NDN, non-dominate NDP, and non-dominate NDS yielded the greatest influence on hitting performance among the tested GS positions; thus, potentially providing coaches with arm orientation specific GS training recommendation for baseball hitters

Sex Specific Difference in Rate of Perceived Exertion During Fatigue Induced Resistance Training

While previously literature clearly articulates the OMNI Scale of Perceived Exertion (RPE) as a quality tool for identifying resistance training perceived difficulty, sex-specific RPE differences during fatigue induced resistance training still remain unclear. PURPOSE: The aim of the current investigation was to examine the difference in male and female intrasession and session RPE (sRPE) during fatiguing upper and lower body resistance exercise. METHODS: Fourteen resistance trained individuals (7 males, 7 females, age = 20.93 ± 1.54, height = 68.07 ± 4.16 cm, weight = 78.33 ± 12.86 kg) performed 5 sessions of resistance training. Session 1 involved familiarization of the RPE scales, anthropometric and skinfold measurements, and 1-repetition maximum (1RM) testing of barbell back squat (SQ) and barbell bench press (BP). Sessions 2-5 participants completed a dynamic warm up followed by 1 set of as many repetitions as possible (AMRAP) at 85% 1RM on SQ and BP, with 10 min rest between exercises. Intrasession RPE was recorded immediately after AMRAP set completion for SQ and BP. To simulate a typical resistance training routine, 4 sets of accessory lifts were performed following BP AMRAP sets. Session RPE was recorded 30 min after completion of each session. Between sessions rest incrementally declined (72, 48, 24, and 6 h) to elicit fatigue. A 2 (sex) x 2 (exercise) x 4 (session) mixed factorial ANOVA was employed to examine sex-specific responses to upper and lower body fatigue induced resistance training. A 2 (sex) x 4 (session) factorial ANOVA was used to assess sRPE sex differences. Alpha level set at p \u3c .05. RESULTS: There was no significant main effect or interaction revealed (F (2,27) = 4.467, p = .021). However, a medium effect size was established between sexes during session 1 squat average intrasession RPE (d= -0.33) and session 4 sRPE (d = -0.32). A large effect size was found between males and females in session 3 sRPE (d = -3.31). Intrasession RPE and sRPE were collapsed and female reported substantially lower sRPE than males (d = .49); however, a small magnitude (d = -.18) of difference or no difference was identified between sexes for intrasession RPE. CONCLUSION: In conclusion, these findings suggest that female possess greater fatigue resistance during lower body exercises when assessed utilizing intrasession RPE. Moreover, males and females differ in their perception of exertion as intersession recovery periods decline, illustrated by decreased sRPE reported by females upon completion of sessions 3 and 4 compared to men. These data also indicated intrasession RPE does not markedly vary between sexes; however, retrospectively (sRPE), females appear to be less effected by fatigue induced exercise or females’ recollection of difficulty diminished post exercise. In conclusion, RPE should be interpreted and utilized differently for males and females

Establishing a Predictive Equation for Anaerobic Capacity Utilizing the 300-yard Shuttle Field Test

Anaerobic capacity can be tested through the Running-based Anaerobic Sprint Test (RAST), Wingate test (gold standard), and the 300-yard shuttle. While each testing is recognized as a valid method of assessing anaerobic capacity, previous investigations found no significant correlation between Wingate test and time to completion of 300-yard shuttle test. The insignificant relationship found between the 300-yard shuttle times and the Wingate outputs insinuate a need for further research investigating the correlations between these two anaerobic tests. PURPOSE: The aim of this study was to determine the influence of 300-yard shuttle measures on anaerobic capacity obtained via the Wingate test. METHODS: Twenty-two Division I softball players (20.41 +1.50 yr) completed two anaerobic testing sessions. Session 1 consisted of the 30s all out Wingate test. Sessions 2 was completed 48 hours following session 1 and involved the performance of two 300-yard shuttle run tests separated with 5 minutes rest. The Wingate test data included: anaerobic peak power (PP), average power (AP), power drop (PD), power drop per second (PD/s), maximal speed (MS), and power at maximal speed (PMS). The recorded 300-yard shuttle measures were time and kinetic energy factor (K-factor) (new anaerobic variable) for both attempts, as well as average time and average K-factor. K-factor during the 300-yard shuttle was calculated by utilizing the mass of participants multiplied by speed (distance divided by time elapsed) squared. A backwards stepwise multiple linear regression was employed to examine the influence of 300-yard shuttle on anaerobic capacity measure obtained via Wingate test. RESULTS: Statistical analysis identified the second 300-yard shuttle attempt time (S300) predicting AP as the model of best fit, which S300 explaining 32.7% of the variance of AP; furthermore, generating the following predictive equation: AP = 9.91 – (.049 x S300). Secondly, 84.2% of the variance in PD was explained by Average K-factor (AKF), establishing PD = -.85 + (.098 x AKF) as a predictive equation. Lastly, AKF, also, predicted 84.3% of the variance in PD/s: PD/s = -.028 + (.003 x AKF). CONCLUSION: An aspect of these finding contradicted preview investigations, as the S300 was recognized as a significant predictor of AP, suggesting faster 300-yard shuttle performance may increase AP. The positive significant correlation between the AKF and Wingate PD and PD/s suggest higher AKF may influence greater measures of PD and PD/s. These finding appear to support that calculating K-factor provides a richer understanding of field tested (300-yard shuttle) anaerobic capacity

Sex-Specific Pre-Session PRS Difference between Bouts of Fatiguing Resistance Training

The perceived recovery status (PRS) scale, a valid psychophysiological tool, provides a scalar representation of varying levels of an individualized recovery status before or during various modes of exercise. Previous investigations recognize females as more fatigue resilient, quantified via the PRS scale, than males during repeated sprint performance. To the best of our knowledge, no investigations have examined the sex-specific PRS responses during multi-session resistance training. PURPOSE: The purpose of this study was to compare male and female PRS scores for multi-session fatiguing resistance training with incremental decline intersession recovery periods. METHODS: Subjects consisted of 14 trained males (n = 7) and females (n = 7) that participated in five resistance training sessions. Session 1 consisted of one repetition maximum (1RM) testing for barbell back squat (SQ) and barbell bench press (BP); additionally, during session 1, subjects were given standardized instructions explaining how to interpret the PRS scale (familiarization). PRS was collected prior to each training session. Seventy-two hours after session 1, participants completed a standardized dynamic warm up, followed by a comprehensive, fatiguing resistance training session that began with 3 sets of 55%, 65%, and 75% 1RM, followed by 1 set of as many repetitions as possible (AMRAP) at 85% 1RM for SQ. Ten minutes of recovery was provided upon completion of SQ, before completing the same 4 set routine for BP. Upon 5-minute rest, participants completed 4 set of 2 repetitions in reserve (RIR) for barbell reverse lunge, barbell shoulder press, and barbell bent-over row in circuit format with 90 seconds rest between circuits. In order, 72hrs, 48hrs, 24hrs, and 6hrs rest periods were assigned as intersession recovery. A 2 (sex) x 4 (session) mixed factorial ANOVA was used to determine the sex-specific responses to resistance training. RESULTS: No significant main effect was revealed between males and females PRS scores across sets. However, a statistically significant main effect of PRS scores was illustrated across sets [F (2.323, 27.875) =19.363, pCONCLUSION: These results suggest males and females globally recover similarly from fatigue induced resistance training. However, these data also suggest optimal intersession recovery duration may differ between the sexes – males reported significantly less recovered 48hr after training (between set 2 and 3), while female recovery decline after 48hr was an insignificant change; thus, aligning with previous reports of greater fatigue resilience appearing in females versus males

The Relationship between 60-yard sprint, 30-yard sprint, Standardized Base Stealing Sprint, and Offensive Baseball Performance

Athletic performance testing protocols strive to accurately predicting or gain better understanding of an athlete’s performance within a particular sport or game. Regarding baseball, Wolfe and colleagues (2012) examined the predictive validity of the 60-yard shuttle run on pitching performance and concluded that strikeouts and innings pitched were significantly related to elevated kinetic energy factors of pitchers obtained from the shuttle run performance. Concerning for baseball position players, the 60-yard sprint (60YS) is traditionally utilized to showcase “baseball speed”, with minimal empirical evident supporting predictability to baseball specific performance outcomes. PURPOSE: The aim of the current investigation was to have examine the relationship between 60YS and offensive baseball performance outcomes, as well as the 30-yard sprint (30YS) test, and newly created standardized 1st to 2nd sprint (STS) test relationship to offensive baseball performance outcomes. METHODS: Division I baseball position players (n = 17; height: 180.92 ± 5.61 cm; weight: 82.1 ± 11.12 kg) performed three sprinting tests: 60YS, 30YS, and STS. Each test was recorded using the Brower Timing Gate System, with sprint time recorded in second. All testing was completed prior to the first game of the team’s college baseball season. Offensive baseball performance measures were recorded throughout 61 regular season games. The following baseball performance data was collected from the university’s official NCAA game performance website: total stolen bases (SB), stole base attempts (AT), stolen base percentage (SBP), at bats (AB), hits (H), doubles (DB), triples (TR), homeruns (HR), runs (R), base-on-balls (BB), hit by pitch (HBP), on base percentage (OBP), slugging percentage (SLP), touched bases (TB), runs batted in (RBI), and batting average (AVE). Pearson’s product-moment correlation (p \u3c .05) was employed to examine the correlation between sprint tests and offensive baseball performance. RESULTS: The statistical analysis revealed significant correlations between STS (p = .002, r = -.762), 30 yd sprint (p = .048, r = -.556), and 60 yd sprint (p = .038, r = -.578) and SB. Additionally, a significant correlation was identified between OBP and STS (p = .022, r = -.625), 30YS (p = .027, r = -.609), and 60YS (p = .020, r = -.633). Aside from these two baseball performance metrics, 30YS and 60YS had no significant correlation with baseball performance. However, STS, additionally, significantly (p \u3c .05) correlated with AT, AB, H, TR, HR, R, BB, SLP, TB, RBI, and AVE. CONCLUSION: The STS, 30YS, and 60YS had a significant relationship with offensive baseball performance. However, the results of 30YS and 60YS only correlated with two offensive measures, while STS had a significant correlation with all but 3 offensive performance metrics. These findings suggest STS may be a more relevant measure for predicting offensive baseball performance than the traditional 30YS and 60YS tests

Differences in Assistance Exercise Volume-Load Prescription during Fatigue Induced Resistance Training

The common purpose of assistance lift application within resistance training is to prevent injury of sport-specific predisposed musculature by strengthening a specific muscle or muscle group. The integration of assistance exercises within standard resistance training is frequently observed, showcasing a high ecological validity of assistance exercises. However, specific prescription of assistance exercises has received little empirical examination. PURPOSE: Therefore, the purpose of the current investigation was to examine changes in assistance lift performance due to fatigue induced resistance training. METHODS: Fourteen resistance trained individuals (male = 7, female = 7, age = 20.93 ± 1.54, ht = 68.07 ± 4.16 cm, wt = 78.33 ± 12.86 kg) participated in 5 resistance training sessions. Session 1 consisted of anthropometric and skinfold testing, one repetition maximum (1RM) testing for barbell back squat (SQ) and barbell bench press (BP), and familiarization of assistance lifts. Session 2-5, involved a standardized dynamic warm up and a comprehensive resistance training session comprising 3 sets of 5 repetitions at 55%, 65%, and 75% 1RM, followed by 1 repetition maximum set at 85% 1RM for SQ and BP, ten minutes passive rest between exercises. Upon 5-minute rest, participants completed 4 sets of 2 repetitions-in-reserve for 3 assistance exercises (barbell reverse lunge [RL], barbell shoulder press [SP], and barbell bent-over row [BR]) in circuit format with 90s rest between circuits. Weight lifted and repetitions completed were recorded and combined as volume-load for each assistance lift. Total session volume-load was the sum of volume-load of all assistance exercises. In order, 72, 48, 24, and 6 h rest periods were assigned as between session recovery intentionally decreasing in time to elicit fatigue. A 3 (exercise) x 4 (session) mixed factorial ANOVA was used to determine difference in assistance lift volume-load. RESULTS: Due to the data violating assumptions of sphericity (p \u3c .001) ANOVA test statistics are estimated using the Greenhouse-Geisser method. There is a significant main effect for assistance exercise volume-load (p \u3c .001). There is no significant interaction between session volume-load (p = .846). Bonferroni post hoc expressed significant differences between all assistance exercises within all sessions, except, RL and SP during session 2 (p = .476) and RL and SP during session 4 (p = .130). CONCLUSION: These data suggest assistance exercises are inherently different and exercise specific prescriptions should be established for assistance lifts. While there was no significant interaction, Cohen\u27s d analysis indicated a medium effect size between cumulative session volume-load of session 1 and session 3 (d = .28), as well as session 1 and session 4 (d = .29). These magnitudinal differences support assistance lift prescription modulation based on fatigue. Furthermore, research examining load, volume, and intensity prescriptions necessitates further investigation to ensure resistance training prescriptions adhere to the principle of specificity

Difference in Intrasession Rate of Perceived Exertion during Resistance Training Designed to Achieve Different Physiological Adaptations

The OMNI RPE scale (1 – 10 scale), specifically session RPE (sRPE), is recognized as a validated tool for assessing internal stress for upper- and lower-body resistance training exercises. While RPE is prevalent within the resistance training research, to the best of our knowledge, no study has investigated training goals specific (i.e., strength, power, hypertrophy, endurance) intrasession RPE measures. PURPOSE: Therefore, the aim of the current investigation was to examine differences in intrasession RPE across 4 distinct resistance training sessions for upper- and lower-body exercise. METHODS: Participants (age 20.64 ± 1.29 yrs; ht 169.95 ± 5.26 cm; wt 77.27 ± 8.37 kg; male = 8; female = 3) with 6 months of resistance training experience performed 5 resistance training sessions. Session 1 consisted of one-repetition-maximum (1RM) testing for the barbell bench press (BP) and barbell back squat (SQ) and served as a familiarization session for the OMNI RPE scale. In randomized session order, sessions 2 – 5 were structured to achieve 4 different training adaptations: strength - 6 sets of 2 repetitions at 90% 1RM (3-minute rest between sets), power - 6 sets of 3 repetitions at 80% 1RM (3-minute rest between sets), hypertrophy - 4 sets of 8 repetitions at 70% 1RM (90s rest between sets), and endurance - 3 sets of 15 at 55% 1RM (30s rest between sets). Rate of Perceived Exertion was assessed immediately after the completion of each set (intrasession RPE) and 30 minutes after session completion (sRPE). A 2 (exercise) x 4 (training mode) Mixed Factorial ANOVA (p \u3c .05) was employed to explore the difference in average intrasession RPE for SQ and BP. A One-way ANOVA (p \u3c .05) was used to assess sRPE differences between training modes. RESULTS: A significant main effect (p \u3c .001) was observed between average SQ and BP intrasession RPE. Bonferroni post-hoc tests identified significant RPE difference between endurance and hypertrophy (7.15 ± 2.15; 5.80 ± 1.90; p = .004), endurance and power (7.15 ± 2.15; 5.01 ± 1.44; p \u3c .001), and strength and power (6.469 ± 1.56; 5.015 ± 1.44; p = \u3c .001) for SQ. Additionally, a significant difference in RPE for BP was identified between endurance and hypertrophy (6.93 ± 2.34; 5.59 ± 2.21; p = .016), endurance and power (6.93 ± 2.34; 4.39 ± 1.41; p = \u3c.001), hypertrophy and power (5.59 ± 2.21;4.39 ± 1.41; p = .009), and strength and power (5.96 ± 1.92; 4.39 ± 1.41; p \u3c .001). CONCLUSION: In support of previous reports, these data suggesting training mode and musculature effect RPE. Specifically, higher RPE was achieved during endurance training and when activating the lower extremities. Opposingly, power training was perceived as the least exerting mode of training. Alternative to standard repetition prescription, these established training goal specific RPE averages may serve as an intrasession modulator by utilizing RPE as an exercise set termination target

The Influence of Various Grip Strength Orientations on Throwing Velocity of Division I Baseball Pitchers

Baseball specific testing battery includes various assessments designed to produce a performance profile of baseball players. Among these tests, the grip strength (GS) assessment has shown reliability in predicting one aspect of pitching performance, pitch velocity. However, various arm orientations occur throughout the pitch, and to the best of our knowledge, no study has investigated the relationship between various grip strength arm orientations and pitch velocity. PURPOSE: Therefore, the purpose of this study was to examine the influence of grip strength at various arm orientations on baseball pitching velocity. METHODS: Twenty-one collegiate Division I baseball pitchers (mean ± SD, age = 21.1 ± 1.8, height = 187.3 ± 5.0 cm, weight = 92.6 ± 8.9 kg) volunteered as participants for this investigation. Using the Jamar Hydraulic Hand Dynamometer, pitchers completed three attempts to exert maximal GS in kilograms (kg) at the following dominate arm position: 90-degree elbow flexion with neutral (NDN), supinated (NDS), and pronated (NDP) forearm placement, as well as 120-degree elbow extension with 90-degree shoulder abduction with supinated (AS) and neutral (AN) forearm grips. Average pitching velocity (APV) was collected via Yakkertek Ball-Tracking System across the fall intersquad season consisting of 20 games. Participant inclusion criteria required a minimum of five pitched innings or 100 total pitches. A backwards multiple linear regression (p \u3c .05) was run to assess the influence of GS on APV. RESULTS: The regression results recognized AS to statistically influence APV, f(1,21) = 8.178, p \u3c .05, r2 = .280. These results suggest AS accounts for 28% of the variance in APV, yielding the following predictive equation: APV = 70.251 + 0.253(NDP). CONCLUSION: The result of this investigation supports previous investigation - GS significantly influences pitching velocity. Moreover, specifically, as 120-degree elbow extension with 90-degree shoulder abduction with supinated GS contributes the greatest influence on APV over other arm orientations. At pitch release and throughout the follow-through phase of the pitching motion, shoulder abduction, elbow angle, and forearm supination appear constant within all pitch variations (i.e. fastball, curveball, change-up) with slight variance between pitchers, respectively. These stride phase through arm acceleration phase biomechanics may explain the influence of AS strength on pitch velocity. Furthermore, strength and conditioning specialist, sport scientists, and coaches should greatly considerate AS GS when testing, training, and tracking baseball pitchers