Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6, 2324-2331 2024 Publisher: Learning Gate DOI: 10.55214/25768484.v8i6.2475 © 2024 by the authors; licensee Learning Gate © 2024 by the authors; licensee Learning Gate * Correspondence: abendo@ust.edu.al The improvement of biomechanical variables at Albanian Elite boxers Aida Bendo1*, Sead Bushati2, Marsida Bushati3 1Sports University of Tirana, Faculty of Physical Activity and Recreation, Department of Health and Movement, Street: “Muhamed Gjollesha”, 1001, Tirana, Albania; abendo@ust.edu.al (A.B.). 2Sports University of Tirana, Faculty of Movement Sciences, Department of Individual Sports, Street: “Muhamed Gjollesha”, 1001, Tirana, Albania; sbushati@ust.edu.al (S.B.) 3Sports University of Tirana, Institute of Scientific Research, Department of Sports Performance, Street: “Muhamed Gjollesha”, 1001, Tirana, Albania; mbushati@ust.edu.al (M.B.). Abstract: Boxing is a sport of self-defense art that utilizes compounds of muscle power, brain and conscience realistically and rationally. The speed required in boxer sports is very dominant in the speed of stimulating reaction of arms and legs when defending and responsive in attacking with a blow or kick. Reaction time is defined as the time elapsed between the stimulus and the response time to the stimulus, which is the determining factor in terms of performance level superiority in many sports branches and it is possible to improve it with training. The purpose of this study is to evaluate the effect of fit light training at elite Albanian boxers. The group in this study is consisted by 16 elite Albanian boxers, divided by an experimental group and a control group. At the experimental group, fit light training was used to collect data before and after training, while the basic boxing training was given to the control group. The paired samples t-test and the independent t-test were used to evaluate the data. The statistical significance at p<0.05 was set. The results have revealed that variables of, and in pretest data in control group were in similar levels, in the posttest data they were respectively: TR arm and leg higher and PF lower, for the experimental group. It can be concluded that the fit light training method is very effective and it is highly recommended to use widely for the training of all boxers, not only the elite ones. Keywords: Fit light training, Optojump, Punch frequency, Time reaction. 1. Introduction Boxer is a branch of martial sports that originated from Indonesia and almost the same as other martial sports. It is also a sport of self-defense art that utilizes compounds of muscle power, brain and conscience realistically and rationally. In the implementation of this sport, it takes several elements of the main physical conditions, namely anaerobic endurance, strength, speed, accuracy, and mental elements that include courage and tenacity. The speed required in boxer sports is very dominant in the speed of stimulating reaction of arms and legs when defending and responsive in attacking with a blow or kick [1]. The quality of the kick depends on the power component to get the power of the punch and kick, while the quality of the reaction ability of the athlete depends on arousing the speed of the move to hit and kick to get the value. Given the importance of arm and leg reactions, one of the exercises that can increase reaction speed and agility is Speed, Agility and Quickness (SAQ) [2]. Reaction speed is the time interval between the stimuli from outside the response with the response [3]. Boxers apply active and passive warm-up activities to improve performance parameters. As a result of these activities, they can improve existing performance parameters such as agility, anaerobic power, vertical jump, flexibility, reaction time [4; 5]. It is known that reaction time, which is of great importance in terms of athlete performance is one of the most difficult sports performance parameters to 2325 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 2324-2331, 2024 DOI: 10.55214/25768484.v8i6.2475 © 2024 by the authors; licensee Learning Gate develop. Reaction time performance in Athletes may vary according to the sport branch in terms of development. Especially in combat sports such as boxing reaction time is of such great importance that it can directly or indirectly affect the outcome of the competition. Reaction time is defined as the time elapsed between the stimulus and the response time to the stimulus [6]. The stimuli that will enable the athletes to take action can be visual, auditory and tactile. The prominent stimuli in combat sports; are visual and tactile stimuli [7]. Especially, visual reaction time is the determining factor in terms of performance level superiority in many sports branches and it is possible to improve it with training. Vision is an important sense for controlling balance. The visual system provides peoples with information about environment displayed as a result of the reflection of light from objects [8]. Vision is a critical part of human body balance which is used to gather information about the orientation of the body in space [9]. Postural orientation is the ability to maintain the relationships between different segments of the human body and its environment [10], while postural stability is the ability to maintain the position of the body within the base of support [11; 12]. Maintaining postural balance involves complex coordination & integration of multiple sensory motor & biomechanical components [8]. Most effective programs emphasize several common components, including plyometric and proprioceptive training in combination with biomechanical parameters and technical training [13]. Proprioception training was very effective in reducing sway indexes at athletes, in order to improvement and to increase the balance condition and sport performances [14]. here have been studies on reaction time performance for many years, and it has been reported that physical training can shorten reaction time in most of these studies [3; 15; 16]. It is known that boxing, which is one of the competitive and challenging sports branches, is a complex sport activity and requires the presence of various functional features (Opto jump device), [17]. Muscle strength, speed, coordination, balance, high anaerobic and aerobic power and reaction time are important factors that play a role in athlete performance. As a result of boxing training, it is aimed to improve the aerobic power, muscle strength and endurance, flexibility, coordination and reaction times of the athletes [9]. The purpose of this study is to evaluate the effect of fit light training at elite Albanian boxers, and how it affects the improvement of biomechanical variables in them. 2. Methodology 2.1. Study Design This research is an experimental study using pretest and posttest control group design. The group in this study is consisted by an experimental group and a control group. At the experimental group, fit light training was used to collect data before and after training. Basic boxing training was given to the control group and the pretest and posttest data were gathered, which were used to compare with the results taken from the experimental group. 2.2. Participants This group involved 16 elite Albanian boxers, aged between 21.78 ± 4.08 years old, weight 84.97 ± 12.55 (kg), height 1.84 ± 0.72 (m) and Body Mass Index (BMI) 25.4 ± 3.96 (kg/m2), respectively. The recruited sample was based as consideration, namely elite boxers, part of the Albanian National Boxing team, who were actively regularly in boxing training for at least over 10 years. Written consent was obtained from the participant’s whose involvement in study was voluntary. 2.3. Instrument and Protocols Fit light – can be used as a training system that help the athletes to strengthen the connections between the brain and the body as well as to improve the development of reaction speed. The methods used are: Program sequence, run programmed sequence, Hand/eye co- ordination. Opto-jump –through an optical system with two tracks, receiver (R )X and transmitter (T )X , as well as with the help of two cameras, which are very important for the evaluation of movement, in addition to numerical data. All 2326 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 2324-2331, 2024 DOI: 10.55214/25768484.v8i6.2475 © 2024 by the authors; licensee Learning Gate the data were recorded and performed in opto jump device, Biomechanics Laboratory of Sports University of Tirana, [17]. 2.4. Procedure The procedure in this study is consisted by three stages: 2.4.1. Stage 1- Pretest Measurements In this phase, the pretest data of biomechanical variables for both groups experimental and control group were collected, with the hypotheses that the pretest data of the two groups data didn’t have a significant difference on average values. 2.4.2. Stage 2- Training Methods This stage includes: (1) both groups have a warm up protocol: a 5 min self-paced run followed by 5 min of active all body limbs, stretching and specific movements. At the end of warm up period, an interval of 5 rested was applied. (2-a) The experimental group is given, the fit light training (2-a), while the basic boxing training (2-b) was used to the control group. The duration of experiment was 12 weeks. The frequency of training is 3 times a week, 90 min each training session. 2.4.3. Stage 3- Posttest Measurements The data post-test for both groups was collected after two different training methods, and they were used to undergo through statistical procedures. 2.5 Statistical Analysis The data analysis techniques include: A variance homogeneity test was applied in order to test the similarity of variance in the pretest and posttest, experimental and control group. The homogeneity test used Levine’s test with t-test [18]. The paired samples t-test and the independent t-test were used to evaluate the data. Pretest and posttest data were used to identify the variations in the Biomechanical variables in a paired samples t-test in each group. Then all the data collected were compared using the independent samples t-test. All the data were analyzed using the statistical program SPSS version 20, with a significance level of 5% (p < 0.05). 3. Results Table 1 gives the descriptive statistics of anthropometric data for experimental and control group. As it can see from this table, the respective values for every parameter are approximately similar for age and height, with very small changes between other parameters, but not significant changes. Table 1. Descriptive statistics of anthropometric data for experimental and control group. Parameter Mean ± SD exp. group Min. value exp. group Max. value exp. group Mean ±SD contr. group Min. value contr. group Max. value contr. group Age (years) 21.77±4.086 18.00 28.00 21.00±4.246 18.00 27.00 Height (m) 1.84±0.72 1.75 1.94 1.83±0.07 1.75 1.93 Weight (kg) 84.97±12.55 70.50 112.10 80.08±8.85 70.50 91.20 BMI(kg/m2) 25.42±3.96 20.52 34.20 23.84±2.71 20.50 27.50 The biomechanical variables of reaction time (RT) for upper limb (arms), reaction time (RT) for lower limbs (legs) are measured in second; and punch frequency (PF), which presents the number of punches/secs, within each group of study: the experimental group and control group, taken from measurements during three rounds x 3 minutes in pretest and posttest data. Table 2 shows the results 2327 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 2324-2331, 2024 DOI: 10.55214/25768484.v8i6.2475 © 2024 by the authors; licensee Learning Gate of paired samples t-test within each group in terms of means of three rounds for pretest and posttest data for both groups: experimental and control group. Table 2. Pair of variables comparison within group of pretest and posttest data for experimental and control groups. Parameter (within groups) Group Pretest mean Posttes t mean Percentage of change T- value Sig. p-value TR Arm Experimental 0.6205 0.4944 20.32% 12.173 0.000 TR Arm Control 0.6182 0.5779 6.51% 7.314 0.000 FreqP Experimental 1.3369 1.6462 18.79% 20.121 0.000 FreqP Control 1.3461 1.4086 4.43% 7.058 0.152 TR Leg Experimental 0.6215 0.5102 17.94% 4.124 0.000 TR Leg Control 0.6195 0.5797 6.42% 5.401 0.000 Table 3 shows the results of paired samples t-test between experimental group and control group in terms of means of three rounds for pretest and posttest data for both groups. Table 3. Pair of variables comparison of pretest and posttest measurements for experimental and control groups. Pair of variables (between groups) Data test Mean experimental Mean control Percentage of change T-value Sig. p-value TR Arm Pretest 0.6205 0.6182 0.37% 1.070 0.297 TR Arm Posttest 0.4944 0.5779 14.45% -3.672 0.001 FreqP Pretest 1.3369 1.3461 0.68% 2.406 0.254 FreqP Posttest 1.6462 1.4086 14.43% -3.365 0.000 TR Leg Pretest 0.6215 0.6195 0.32% -2.682 0.131 TR Leg Posttest 0.5102 0.5797 11.98% -1.061 0.001 Table 4 reports the independent samples t-test results for the pretest and posttest data for experimental and control group. Table 4. Independent samples t-test for the posttest data for Experimental and control groups. Parameter Levine’s test sig. Mean experimental Mean control Percentage of change T-value Sig. p-value TR Arm 0.275 0.4944 0.5779 14.45% 0.562 0.000 FreqP 0.100 1.6462 1.4086 14.43% -3.443 0.001 TR Leg 0.305 0.5102 0.5797 11.98% -2.125 0.039 2328 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 2324-2331, 2024 DOI: 10.55214/25768484.v8i6.2475 © 2024 by the authors; licensee Learning Gate 4. Discussion Based on the results for the biomechanical variables reaction time ( TR Arm ) for upper limb, reaction time ( TR Leg ) for lower limbs and punch frequency ( FreqP ) between two groups, experimental and control group, taken from each phase of measurements, and their respective rounds. From the comparisons of results of table 2 for the pair of variables within group of pretest and posttest data for experimental and control groups, it can be concluded that for: Pair 1: The comparison of TR Arm parameters in pretest – posttest data experimental group. The control analysis of TR Arm variable for experimental group in pretest – posttest data, varies considerably, respectively with a mean value of 0.6205 and 0.0499 and they are accompanied with a standard error mean (0.0156 and 0.0513), statistically the same. However, the confidence interval CI, ( 95% = ) of reaction time values differentiation is:  0.01976;0.02779 and t-test value t(7)=12.173; p<0.05 indicate a good improvement in statistical terms of the test performed for experimental group. Pair 2: The comparison of TR Arm parameters in pretest – posttest data control group. Table 2 shows a difference of the mean of TR Arm parameter for control group, as a considerable SD. The control analysis of paired t-test shows that there is a difference that is indicated by the respective values: t(7)=7.314 and p< 0.05, statistically significant. It should be that CI interval is not very wide:  0.0935;0.01665 , as a result of the standard error mean, 0.01762 and 0.01802 respectively. Pair 3: The comparison of FreqP parameters in pretest – posttest data experimental group. Statistically, punch frequency pretest data is larger than posttest data, thus the respective values 1.3369 and 1.6462 increase considerably after training phase and this is statistically significant: t(7)=20.121; p<0.05. However, the standard error mean for the selection is a little bit higher (0.04635) pretest than the value (0.04224) posttest value of the mean value after training, and it is made evident from the effect of fit light training. Pair 4: The comparison of FreqP parameters in pretest and post-test data control group. For the control group, t-test analysis of punch frequency variable shows that there is no essential difference in terms of mean value of this parameter, but it is noticed a considerable SD value. The t-test values: t(7)=7.058 and p=0.152 > 0.05, confirm that there is no statistical significance at this control group. It should be highlighted that the CI ( 95% = ), proves to be wide  0.07665;0.13964 and this is a result of the standard error mean. Pair 5: The comparison of TR Leg parameters in pretest – posttest data experimental group. Comparing the results for TR Leg variable at experimental group, it is observed that the mean values pretest and posttest have changed from 0.6215 to 0.5102, with the respective standard error mean (0.0119; 0.01334), statistically the same. The CI confidence interval values differentiation is:  0.00873;0.02608 , t(7)=4.124 and p<0.05, shows a good improvement of TR Leg for this experimental group, after fit light training method. Pair 6: The comparison of TR Leg parameters in pretest – posttest data control group. Analysis results for the same variable TR Leg at control group, revealed respectively the mean values: 0.6195 and 0.5797 for pretest and posttest measurements. These values are accompanied by standard error means: (0.01019; 0.00953) statistically the same. The respective t-test values: t(7)=5.401 and p<0.05 indicate a 2329 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 2324-2331, 2024 DOI: 10.55214/25768484.v8i6.2475 © 2024 by the authors; licensee Learning Gate statistical significant result. Meantime, the CI interval for the control group  0.00711;0.01585 shows slight differences as a result of standard mean. From the comparisons of results of table 3 for the pair of variables between groups of pretest and posttest data for experimental and control groups, it can be concluded that for: Pair 1: The comparison of TR Armparameters in pretest data experimental –control group. In table 3, it is not observed a noticeable difference of the mean of TR Arm pretest data of experimental and control group, 0.6205 and 0.6182, practically the same. The control t-test analysis shows that there is no essential difference between the differences of TR Arm parameter, as indicated by the respective values: t(7)=1.070 and p=0.297 > 0.05. This is proven by the CI interval to be very wide:  0.002212;0.7012− , as a result of the standard error mean. Pair 2: The comparison of TR Arm parameters in posttest data experimental –control group. Whereas posttest data shows that mean values of TR Arm for experimental – control group are respectively: 0.4944 and 0.5779, which are smaller than the ones pretest results, which were 0.6205 and 0.6182. Yet these values are statistically different after posttest, since the statistical findings show t(7)=- 3.672; p=0.001<0.05 and for the reason that TR Arm of experimental group is smaller than TR Arm of control group. Pair 3: The comparison of FreqP parameters in pretest data experimental –control group. In pretest conditions, punch frequency FreqP parameter seems to be the same for both groups: 1.3369 and 1.3461, without any noticeable difference. The t-test analysis, t=2.406 and p=0.254>0.05, shows that there is not any difference of this parameter. The CI ( 95% = ) results that this interval is very wide  0.2194;0.2732 , as a result of the standard error mean. Pair 4: The comparison of FreqP parameters in posttest data experimental –control group. Statistically, FreqP variable posttest data indicate that they are larger than FreqP pretest, so this variable increase considerably after training period, this is statistically distinct, even though the respective values are taken after training phase in posttest measurements for the both groups. The mean values are respectively: 1.6462 and 1.4086, quite different from those taken from pretest measurements: 1.3363 and 1.3461, respectively. The analysis paired t-test results: t(7)=-3.365; p<0.05, indicate a good improvement in statistical terms of the posttest after training phase. However, the standard error mean for the selection in pretest data is considerably higher than posttest data, which is proven by the very wide of CI,  0.36220; 0.10225− − . Pair 5: The comparison of TR Leg parameters in pretest data experimental –control group. The pretest data for TR Leg parameter gives the man values: 0.6215 and 0.6195 for experimental and control groups, which show no essential difference between them. This is proven by the t-test results respectively: t(7)=-2.682 and p=0.131>0.05, statistically non-significant. These mean values are accompanied with a standard error mean (0.038 and 0.048), statistically the same. This result is shown also by the CI value interval  0.0693;0.0639 , without any noticeable difference. Pair 6: The comparison of TR Leg parameters in posttest data experimental –control group. Whereas after training phase, it is observed that the posttests mean values of TR Leg of experimental and control group are respectively: 0.5102 and 0.5797. These values are smaller than the pretest mean 2330 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 2324-2331, 2024 DOI: 10.55214/25768484.v8i6.2475 © 2024 by the authors; licensee Learning Gate values, which were (0.6215 and 0.6195), CI ( 95% = ). TR leg variable is seen to be changed after training phase in posttest data, with these values: t(7)=-1.061, p=0.001<0.05, since TR Leg of experimental group is statistically lower than TR Leg of control group. However, it should be highlighted than the CI interval ( 95% = ) is proven to be wide,  0.06155;0.0813− , as a result of the standard error mean. From the independent samples t-test in table 4, it can be verified whether the Levene’s test is significant. Since the significance value p=0.275>0.05, this means that the equal variances is not significant, this implies that equal variances assumed. The mean score of the reaction time TR Arm for the elite boxers of experimental group is 0.49 (SD=0.78) and that of the control group was 0.58 (SD=0.05). This difference was statistically significant: t(7)=0.562; p<0.05. Regarding to the punching frequency ( FreqP ) variable, the Levene’s test result p=0.100>0.050, non-significant, equal variances assumed. The FreqP parameter for experimental group is reported as follow: mean value 1.65 (SD=0.04) for experimental group and 1.41 (SD=0.061) for the control group. In this way, the difference was statistically significant, because t(7)=-3.443, p=0.001<0.05, statistically significant. For the last variable TR Leg , results of Levene’s test p=0.305>0.050, show that it is no significant and it implies that equal variances assumed. The value reported in means for experimental group: 0.51 (SD=0.07) and for the control group: 0.58 (SD=0.43). The respective values from t-test results, t(7)=- 2.125 and p=0.03 <0.05, confirm that the differences between two groups are statistically significant. 5. Conclusion The biomechanical analysis points out significant statistical changes in one of the more important sport disciplines of movement, such is boxing. The results have revealed that variables of TR Arm , TR Leg and FreqP in pretest data in control group were in similar levels, in the posttest data they were respectively: TR Arm and TR arm and TR Leg higher and FreqP lower, for the experimental group. It can be concluded that the fit light training method is very effective and it is highly recommended to use widely for the training of all boxers, not only the elite ones. The conclusions from the results of this study are: applying fit light method in elite Albanian boxers, a high intensity sport competition was very effective in: reducing reaction time of arm and legs, increasing punch frequency, for the boxing players of our national team. In other words, applying fit light training method, is very effective in improving TR Arm , TR Leg and FreqP . The results of this study are expected to be useful for coaches of boxing and other sport disciplines such as: kick boxing, wrestling, and also in all sports that require a faster reaction time to improve sports results and performance. 5.1. Limitations of the Study However, there are some limitations, which need to be validated for the future researches. These limitations include: the size of the sample used, so it is necessary to involve a wider sample size, including boxers, kick boxers, and wrestling of different ages and weights, in order to see the results over a longer period of time and to reduce comparisons between them. Kouadio, Y. “Personal Development Workshops and their Impact on Girls' Self-Confidence in Côte d'Ivoire”, West African Journal of Psychology33(1) (2020) 45-59. Copyright: © 2024 by the authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). https://creativecommons.org/licenses/by/4.0/ 2331 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 2324-2331, 2024 DOI: 10.55214/25768484.v8i6.2475 © 2024 by the authors; licensee Learning Gate References [1] Imran Akhmad, Amir S. Rahma, D and Dodi, Y. S,. The Influence of SAQ on Speed and Agility for Futsal Young Athletes on X-Trail 14 Futsal Academy. International Journal of Science and Research (IJSR). 8(12), (2019), 933-936, https://www.ijsr.net/archive/v8i12/ART20203413.pdf [2] Johnson P, Bujjibabu M. Effect of Plyometric and Speed Agility and Quickness (SAQ) on Speed and Agility of Male Football Players. Asian Journal of Physical Education and Computer Science in Sport. 7(1), (2012), 26-30. DOI: 10.13189/saj.2020.080503 [3] Magill R. A. David I.A. Motor Learning and Control. Concepts and Applications 12e, McGrawhillmedical. (2021). https://accessphysiotherapy.mhmedical.com/book.aspx?bookID=3082#256572757 [4] Eken Özgü. The Acute Effect of Different Specific Warm-up Intensity on One Repeat Maximum Squat Performance on Basketball Players. Pedagogy of Physical Culture and Sport. Vol. 25(5), (2121), 313–18. https://doi.org/10.15561/26649837.2021.0506. [5] Bayer R, Özgür E. Some Anaerobic Performance Variations from Morning to Evening: Massage Affects Performance and Diurnal Variation. Política E Gestão Educacional, São Paulo State University. 25(3), (2021), 2459– 2474https://doi.org/10.22633/rpge.v25i2.15914 [6] Spirduso, Waneen W. Reaction and Movement Time as a Function of Age and Physical Activity Level. Journal of Gerontology. 30(4), (1975), 435–440. https://doi.org/10.1093/geronj/30.4.435 [7] Kocak U. Z, Unver B, Derya O. A comparison of injury risk screening tools in Turkish young elite male handball players based on field positions. Turk Fizyoterapi Ve Rehabilitasyon Dergisi. 31(2), (2020), 163-170. https://doi.org/10.21653/tjpr.583463. [8] Bendo Aida. The effect of proprioception training in biomechanical parameters. Dissertation thesis. (2015), 28-33. https://upt.al/images/stories/menu/Diseracioni%20Aida%20Bendo.pdf [9] Bendo A, Skënderi Dh, Veveçka A. Effect of vision and orientation in human balance. Journal of Multidisciplinary Engineering Science and Technology (JMEST). 1(5), (2014), 336-341. https://www.jmest.org/wp- content/uploads/JMESTN42350275.pdf [10] Muhammad H.B.S, Hosni H, Mohd S.A, Muhamad N. M, Fatin A. A. R. Effects of Plyometric Training on Speed and Agility among Recreational Football Players. International Journal of Human Movement and Sports Sciences. 8(5), (2020), 174 – 180. https://doi.org10.13189/saj.2020.080503. [11] [11] Hoda S, Farid B, Bijan F, Sanaz R. Dynamic stability training improves standing balance control in neuropathic patients with type 2 diabetes. Journal of Rehabilitation Research & Development. 48(7), (2011), 775-786. https://doi.org/10.1682/jrrd.2010.08.0160 [12] Shumway C. A, Marjorie H. W. Motor Control. Theory and Practical Applications. Williams & Wilkins, Baltimore. (1995), 119- 142; 357-376. https://search.worldcat.org/title/30894139 [13] Wang Y, Yu-tien T, Tzuhui A. T, I-Tsun Ch, Alex J.Y. L. The effect of neuromuscular training on limits of stability in female individuals. World Academy of Science, Engineering and Technology. 7(7), (2013), 381-384. doi.org/10.5281/zenodo.1087069 [14] Bendo A., Agolli L., Kasa A. Analysis of Biomechanical Parameters on IL_EO and 1L_EC Tests on 10-14 Years Old Players of Tirana FC. International Journal of Human Movement and Sports Sciences. 11(3), (2023), 564 – 571. https://doi.org/10.13189/saj.2023.110308. [15] Gürses V. V, Okan K. The Relationship between Reaction Time and 60 M Performance in Elite Athletes. Journal of Education and Training Studies. 6(12), (2019), 64. https://doi.org/10.11114/jets.v6i12a.3931. [16] Nevzat D, Zühal K, İsmail I. Comparison of Visual Simple Reaction Time Performances of Boxers and Wrestlers. Pakistan Journal of Medical and Health Sciences. 16(2), (2022), 467–469. https://doi.org/10.53350/pjmhs22162467 [17] Opto jump device. http://www.optojump.com/what-is-optojump.aspx [18] Griffiths M. Basic Quantitative Methods. Computer exercises & Reference Information. (2011-12), 37-39. https://www.ijsr.net/archive/v8i12/ART20203413.pdf http://dx.doi.org/10.13189/saj.2020.080503 https://accessphysiotherapy.mhmedical.com/book.aspx?bookID=3082#256572757 https://doi.org/10.15561/26649837.2021.0506 https://doi.org/10.22633/rpge.v25i2.15914 https://doi.org/10.1093/geronj/30.4.435 https://doi.org/10.21653/tjpr.583463 https://upt.al/images/stories/menu/Diseracioni%20Aida%20Bendo.pdf https://www.jmest.org/wp-content/uploads/JMESTN42350275.pdf https://www.jmest.org/wp-content/uploads/JMESTN42350275.pdf https://doi.org10.13189/saj.2020.080503 https://doi.org/10.1682/jrrd.2010.08.0160 https://search.worldcat.org/title/30894139 https://doi.org/10.5281/zenodo.1087069 https://doi.org/10.13189/saj.2023.110308 https://doi.org/10.11114/jets.v6i12a.3931 https://doi.org/10.53350/pjmhs22162467 http://www.optojump.com/what-is-optojump.aspx