Introduction

Vertical jump performance, recognized as a crucial functional metric for athletes (especially in team sports) complements the traditional use of isometric and isokinetic assessments for evaluating lower limb strength and power (especially in team sports)1,2. Tests like the squat jump (SJ), countermovement jump (CMJ), and drop jump (DJ) offer insights into lower extremity strength3, risk of injury4, and and neuromuscular fatigue5,6. To accurately measure these jumps, a variety of devices and technologies are employed, including force platforms, 3D video motion analysis, linear position transducers7, infrared cells8,9, and contact mats10. Among these devices, the force platform and 3D video motion analysis are considered the “gold standard” for vertical jump measurements8,9,11. Although the mentioned devices have higher levels of accuracy in vertical jump tests, they impose some limitations on athletes and trainers due to their expensiveness, low portability, generally requiring computer software and not being very practical to use outside the laboratory9,12. However, with the continuous development of technology, more practical and cheaper alternatives have emerged in recent years to evaluate vertical jump performance.

With the developments in mobile phone video technology and especially with the development of high frame rates and screen resolutions in smartphones, the use of smartphones and mobile applications in sports performance, health, and fitness tracking has increased13. However, in exercise and sports sciences, sports professionals need to have information about both the reliability and simultaneous validity of the technological device to be used before applying performance tests14. Unfortunately, manufacturers sometimes do not provide an analysis of the validity or reliability of their products, making it difficult for trainers to evaluate the meter and performance objectively and consciously15. The My Jump2 (rebranded to My Jump Lab) app, developed by Balsalobre-Fernandez is one of the most popular and pioneering mobile applications that measure vertical jump performance with the integration of high-speed cameras into mobile phones16. With this application, the moment of take-off and ground contact during the vertical jump is manually marked and the jump height is measured from the flight time. Past studies have examined the validity and reliability of the My Jump2 app in different populations17, different genders12,18 and different measurement methods12,18,19,20,21 and reported nearly perfect correlations. However, manually marking the moment of take-off and ground contact made the application slower than force platforms, infrared and contact mats. For this reason, a new version of the application called My Jump Lab was recently developed by Balsalobre-Fernandez22. With this version, vertical jump height is automatically measured without any marking of take-off and contact times. Another example of vertical jump applications is the IOS (Apple, Inc. Cupertino, CA, USA) Jump Power (Sweden, Stockholm, 2015) app developed by Sten Kaiser. Jump Power, which is very cheap, practical, and does not require any installation compared to laboratory equipment, automatically detects the jumper in front of the camera with its face detection feature and provides information about jump height (centimeter), average power (watt), average force (newton) and flight time (millisecond). However, to the authors’ knowledge, no research has been found that analyzes the concurrent validity and reliability of Jump Power to measure vertical jump actions. Due to the increasing usage rate of smartphone applications, it is important to analyze the accuracy of these applications to measure the variables related to physical performance. This research aims to examine the reliability, validity and usefulness of the Jump Power application in SJ and CMJ measurement in professional athletes by comparing it with the Optojump photoelectric cell system in measuring SJ, and CMJ the parameters of the jumps.

Methods

Experimental approach to the problem

This study was designed to investigate the reliability, validity, and usefulness of the Jump Power application by comparing it with the reliable and validated Optojump photoelectric cell system. Participants performed 3 SJ and CMJ on 3 days separated by 48 h. All vertical jump performances were recorded the OptoJump system (Optojump, Microgate, Bolzano, Italy) and the JumpPower app (Sweden, Stockholm, 2015).

Participants

Twenty-two soccer players (age, weight) volunteered to participate in the research. The participants were the players of the U21 team in the Turkish Spor Toto 1st League (Erzurumspor FK/Turkey). Participants (mean ± standard deviation [SD]; age = 20,73 ± 0,89 years; body mass = 74,39 ± 8.4 kg; body height = 1,76 ± 0.05 m). All participants were informed of the risks and benefits of the study before signing institutionally approved consent forms. (a) Not having any medical and orthopedic health problems that could affect jumping performance in the last three months, (b) having more than two years of competition and training experience, and c) making training over 8 h a week were determined as the criteria for participation in the research. The research adhered to the Declaration of Helsinki and was approved by Yalova University Ethics Committee (10/03/2023).

Procedures

All participants were familiarized with SJ and CMJ techniques one day before the tests, and correct technique applications were explained with video support. Before trials, participants carried out a standardized 10 min warm-up that consisted of lower-body dynamic stretches, jogging, skipping, and vertical jumps similar to jump test protocols. Then, each participant performed three SJ and three CMJ with the instruction to jump as high as possible. Each jump was separated by a 2 min passive rest period while 10 min separated each type of jump. The highest jump of each jump technique was taken into analysis18. This trial procedure was performed on three separate occasions (referred to as Session 1, Session 2, and Session 3), with 48 h intervals between each session. Since the athletes were on a 2-week league break, they did not participate in any training and exercise between the trials. All trials were completed at the same time of the day, in the same indoor venue and on the ground, with the athletes wearing the same shoes and clothes. The jumps were recorded concurrently via the Optojump system (Optojump, Microgate, Bolzano, Italy) and the JumpPower app installed on an iPhone 13 (Apple Inc., Cupertino, CA, USA) mobile phone. During the measurements, according to the instructions of the JumpPower app, the iPhone was placed 2 m away from the Optojump with a tripod and at the face level of the subjects. Optojump can measure power and force only in tests involving drop jumps and multiple jumps. Therefore, only jump height and flight time data were included in the analysis. Participants were measured by height (SECA, Hamburg, Germany) and body weight (InBody 770, Cerritos, CA, USA) before testing. On the day of the test, the room temperature was measured at 21 degrees Celsius, and the humidity level was 87%

Squat jump and countermovement jump performance

Participants performed all types of jumps with their hands on their hips (Akimbo). For the CMJ, participants started during the flight phase of the jump from a static standing position with their legs straight. During SJ, the participants were made to come to a position with their knees bent 90 degrees with the goniometer before jumping. Participants were instructed to jump as high as possible, which was encouraged by instructions for maximal effort during the jump23.

Optojump photoelectric cell system

The Optojump is a device that employs signal interruption technology to record flight time during the vertical jump. It is made up of a photoelectric cell transmitting and a receiving bar arranged in a parallel position24. 33 optical light-emitting diodes (LEDs) are installed in the bars. The continual exchange of information between the transmitting and receiving bars. The LEDs are spaced 3.125 cm apart and 0.3 cm above ground level. Compared to a force platform, the Optojump photoelectric cells technology has been demonstrated to predict vertical jump height with excellent intraclass correlation (ICC). (ICC = 0.99, 95% CI 0.97–0.99; P < 0.001)9,16. In addition to its reliability, the Optojump device has demonstrated substantial validity in various studies, establishing its effectiveness as a benchmark device. A nearly perfect correlation was found between force platform and Optojump (r = 0.99; 95% CI 0.098–0.99)25. In another study that examine the test–retest reliability, usefulness, and validity of Optojump, the device reported as reliable, and valid method of assessing the smallest worthwhile change in CMJ performance (ICCs > 0.80 and the CV ˂ 10%; SWC: 1.44, TE:1.04)26. These findings underscore that the Optojump not only provides reliable data but also accurate and consistent measurements across different testing conditions, thereby validating its use as a benchmark device in sports science research.

JumpPower app

JumpPower is a mobile application that predicts vertical jump actions with face detection using high-quality video recording and screen resolution on smartphones and tablets (IOS). According to the guide of the application, the smartphone or tablet is positioned 2 m away from the subject to be measured and at face level. The app calculates the jump height (cm) by measuring the difference between the person’s eye level before the jump and at the peak of the jump. JumpPower also calculates power (W) and force (N) outputs by tracking acceleration from the squat position to the peak of the jump using body weight data. In addition, the application, which can estimate the time of flight (ms), is not used in an environment where the face of the subject is not facing the camera and there is not enough light.

Statistical analyses

For reliability analysis, Coefficients of Variation Percent (%CV) were calculated using standard error/mean*100 formula,)38. The CV was classified as good (< 5%), as moderate (5–10%), and as poor (> 10%)38,39. The Correlation Coefficient (R2) was determined by utilizing the existence of heteroscedasticity between absolute differences and mean values on the Bland–Altman plot for validity. The differences between the data obtained from the app and the data obtained from the OptoJump device were analyzed by Bland–Altman analysis. Equivalence Independent Samples T-Test was used to analyze the difference between the measurements. MAPE (Mean Absolute Percent Error) values were used for the validity between the different use of App and OptoJump. Repeated measures ANOVA was used to differences between sessions. The relationship between the data obtained from the App and OptoJump was tested with Pearson analysis. These values were classified as follows; < 0.05: poor, 0.5– 0.75: moderate, 0.75–0.90: good, and 0.0.90: excellent. Significance level was evaluated as p < 0.05. Data analysis was performed using R studio based JASP software version 0.16 (JASP, University of Amsterdam, Netherlands) and SPSS software version 26.0 (SPSS, Inc., Chicago, IL, USA) program.

Results

Table 1 indicates the reliabilities of all the data, with CV% values for both CMJ and SJ exercises observed to be below the accepted threshold of 5% across all sessions. The results of the Equivalence Independent Samples T-Test used to analyze the differences between the measurements are presented in Table 2. All values measured from the application show statistically significant differences from the OptoJump device in both CMJ and SJ exercises (p < 0.001). It was determined that there were no statistically significant differences among the sessions. Detailed information regarding all values can be found in Table 3. Pearson correlation values for CMJ and SJ exercises are separately presented for all sessions in (Figs. 1–4). The correlations between App and OptoJump measurements ranged from moderate to good (r = 0.318–609). Figures 5–8 showcase Bland–Altman plots of the differences. Bias & Limits Point Value [Lower 95% CI and Upper 95% CI] is shown in Table 4. Also, mean absolute percent error (MAPE) was calculated between the app and OptoJump parameters. All parameters presented data with a correct prediction value below the 10% limit. The data were generally distributed between the lower and upper limits in the Bland–Altman graphs.

Table 1 Reliability of parameters.
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Table 2 Equivalence ındependent samples T-test.
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Table 3 ANOVA values for sessions variances.
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Fig. 1
figure 1

Scatter plots for CMJ-App Jump Height (cm) vs. CMJ-Optojump Jump Height (cm).

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Fig. 2
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Scatter plots for CMJ App Flight Time (ms) vs. CMJ-Optojump Flight Time (ms).

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Fig. 3
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Scatter plots for SJ-App Jump Height (cm) vs. SJ-Optojump Jump Height (cm).

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Fig. 4
figure 4

Scatter plots for SJ-App Flight Time (ms) vs. SJ-Optojump Flight Time (ms).

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Fig. 5
figure 5

Bland–Altman plots of the differences between the JumpPower App (App) and the Optojump CMJ height measurements. The short-dashed lines represent the upper and lower 95% limits of agreement (± 1.96 SD), the solid line represents the bias (Mean) and the dotted line represents the tendency (correlation) between the two variables.

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Fig. 6
figure 6

Bland–Altman plots of the differences between the JumpPower App (App) and the Optojump CMJ Flight Time measurements. The short-dashed lines represent the upper and lower 95% limits of agreement (± 1.96 SD), the solid line represents the bias (Mean) and the dotted line represents the tendency (correlation) between the two variables.

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Fig. 7
figure 7

Bland–Altman plots of the differences between the JumpPower App (App) and the Optojump SJ height measurements. The short-dashed lines represent the upper and lower 95% limits of agreement (± 1.96 SD), the solid line represents the bias (Mean) and the dotted line represents the tendency (correlation) between the two variables.

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Fig. 8
figure 8

Bland–Altman plots of the differences between the JumpPower App (App) and the Optojump SJ Flight Time measurements. The short-dashed lines represent the upper and lower 95% limits of agreement (± 1.96 SD), the solid line represents the bias (Mean) and the dotted line represents the tendency (correlation) between the two variables.

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Table 4 Bland–altman and mean absolute percent error values.
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Discussion

This study aimed to test the concurrent validity and reliability of Jump Power, an IOS application for measuring vertical jump (SJ and CMJ) performance, by comparing it with the previously validated Optojump. To the best of our knowledge, this study is the first study to test the validity and reliability of the Jump Power application. The main findings of this research indicate that the Jump Power app is a reliable but not valid tool for measuring vertical jump performance. When the two measurement devices were compared, significant differences were observed in terms of both CMJ and SJ jump height and flight time (p < 0.001) (Table 3). When testing whether Jump Power is a valid method for determining vertical jump height, the analysis showed a moderately positive correlation coefficient value between the two measurement methods [r: 0.47, p < 0.01]. When flight times were examined, Jump Power CMJ and Optojump CMJ were moderately positive [r: 0.318, p < 0.05]; There is a moderate positive significant relationship between Jump Power SJ and Optojump SJ flight times [r: 0.518, p < 0.01].

In addition to being affordable and portable, mobile applications have begun to be scientifically validated against gold-standard laboratory equipment that is difficult to access and expensive27. However, it seems that most of the mobile applications in the sports category are insufficient to provide data based on scientific evidence. For example, in a study on fitness applications, it was reported that only 20% of these applications scored higher than 50% in the quality assessment based on the guide of the American College of Sports Medicine28. Therefore, the suitability of the information used to perform the exercises in these applications is a situation that should be questioned.

Vertical jump performance is an important criterion for determining ability in sports such as football28, evaluating lower extremity strength29 and monitoring neuromuscular fatigue in athletes to prevent injuries30. Currently, technological methods such as camera-based equipment, contact platforms, infrared platforms, and accelerometer methods also offer valid and reliable jump height assessments. With the developments in technology, vertical jump evaluation practices reveal more practical alternatives compared to previous years12. One of these alternative applications is the My Jump 2 mobile application, which is used to evaluate athletic performance and has been the subject of many scientific studies in recent years due to the variety of data it contains.

The validity and reliability of the My Jump 2 application have been tested with different jumping actions, different populations (children, adolescents, adults, elderly, women, and men), different laboratory devices (force platform, 3D camera-based equipment, infrared platforms, contact platform) and the application within the application. It has demonstrated near-perfect validity (r = 0.97–0.99) and reliability (ICC: 0.99) in previous studies where it was examined across data types12,17,18,19,20,21,31,32,33,34. My Jump mobile application stands out as one of the most recommended applications by researchers for performance measurement. However, measurements of the Jump Power application gave less valid results compared to Optojump. These results may be due to the insufficient facial recognition system used by the application during measurement, which distinguishes this application from other applications in terms of software content.

Rapid advances in technologies such as digital cameras and portable devices and the increasing demand for security make facial recognition systems one of the priority biometric technologies35. Various facial recognition techniques have achieved remarkable success in well-controlled environments. However, these techniques tend to fail for various reasons, and to date, most face recognition algorithms have not achieved an optimal level of recognition accuracy due to these problems36,37. These problems include lighting, shadows on the face, changes in facial expression, and low resolution. It is thought that one or more of these reasons may be the reason why the Jump Power application gives less valid results compared to Optojump, or the algorithms used by the software do not work correctly38,39,40.

Another finding of our research shows that Jump Power is a reliable device. Internal consistency analysis was performed by making repeated measurements on the same participants on different days. The present results demonstrate that the Jump Power application is a reliable tool (CV < 5%) in assessing both CMJ and SJ vertical jump height.

Our research has some limitations. The sample group consists of male soccer players. Conducting future studies on this subject with different age groups, genders, and different populations may help evaluate this application in terms of validity and reliability in different populations. In addition, future studies can compare the Jump Power application with different laboratory-based vertical jumping devices (force platform, 3D camera, contact platform). This should be considered when interpreting the present results, as values are likely to vary between different laboratory-based vertical jump devices. Finally, the number of participants can be increased to strengthen statistical accuracy. More studies are needed to understand the findings more deeply regarding the validity and reliability of the Jump Power application.

These findings provide important information for coaches, sports scientists, and performance analysts who want to evaluate vertical jump in soccer players objectively and practically. It is important to take these limitations into account and choose alternative valid and reliable measurement methods when making decisions about the use of the application.

Conclusion

In conclusion, this study revealed that the Jump Power phone application is a reliable but not valid tool to measure vertical jump in soccer players. The JumpPower app is not valid to measure the vertical jump height in comparison to the Optojump, because its precision is low (50–60 Hz), the detection of the moment where the jump starts could be improved (i.e., algorithms and eyes’ detection) and the references used to measure the jump height were taken in different instants of the jump (i.e., the feet fully supported by the ground and the feet leaving the ground, respectively). However, the JumpPower app seems to be reliable to measure the vertical jump height, so further apps with a high frequency of video and advanced algorithms to detect the jumper’s face and the moment of the beginning of the jump could be developed.