## 2 Materials and Methods
### Data Processing and Analysis  
The Vertec data were measured in inches and converted to centimeters, with VJ height calculated by subtracting the baseline reach height from the measured jump height for each trial. The Jumpster app automatically provides users with a calculated VJ height in inches, which was also converted into centimeters; no additional calculations were necessary by the study team for the Jumpster app data. An overall failure rate for the mobile app (i.e., trials where no usable data were obtained) was also calculated across all participants and trials and presented as a percentage (total failed trials over total trials).  
Only device-matched trials were used for the analysis, where trials with missing data for either measurement tool were discarded entirely. Data for both measurement tools were independently assessed for normality using the Shapiro-Wilk test. Next, descriptive statistics were calculated for the participant age, height, weight, maximum Vertec jump height, and maximum Jumpster jump height. Independent samples [PERSON]'s \(t\)-tests were also conducted for these variables to assess possible differences between men and women.  
As previously outlined, several analysis tools are helpful in determining the validity and reliability of different measures or devices ([PERSON] et al., 2018; [PERSON] et al., 2018). Our assessment of validity began by measuring the relationship between the measured jump heights captured with both the Vertec and the Jumpster using a correlation analysis and visually comparing the line of equality to the calculated regression line. The relative orientation of both lines provides additional insights into the validity of any significant relationship. Next, a tolerance analysis (similar to a Bland-Altman analysis) accounting for intraparticipant correlations in the model structure was conducted to assess possible measurement bias between the two tools using the SimplyAgree package (version 0.2.0) in RStudio (version 2024.04.1 + 748; Posit Software, PBC, Boston, MA, USA) ([PERSON] et al., 2018; [PERSON] et al., 2018). To provide contextually-relevant absolute bounds of measurement error, we also established acceptable limits of variability based on our calculated standard error of the measure (SEM) for the Vertec data (outlined below) and overlaid these results on a Bland-Altman styled plot as another means of assessing overall tool validity [31].  
Reliability was first assessed in absolute terms by calculating the 95% predictive intervals (PI\({}_{95}\)s) and tolerance limits (TL\({}_{95}\)s) between the two measures (similar to Bland-Altman limits of agreement \(\pm\)95% CI) [33; 34]. Additional assessments of absolute reliability were also conducted by calculating the SEM and coefficient of variation (CV) for both tools using mean square error estimations, again with the SimplyAgree package [33; 35]. Finally, relative reliability was assessed by estimating the intraclass correlation coefficient and 95% confidence intervals between the Vertec and the Jumpster app, based on a 2-way random effects, mean rating, absolute agreement model (ICC 2,K) [33; 35; 36]. This was also calculated using the mean square error estimations in the SimplyAgree package. All data were analyzed using RStudio (\(\alpha\) = 0.05).