## 3 Results  
Our results showed that the 105 s and 90 s test durations produced non-significant differences in CP estimates when comparing the 3 MT and exponential functions (MONO \(p=0.24\), BI \(p=0.11\)). For W\({}^{\prime}\), 135 s and 90 s test durations yielded non-significant differences between the 3 MT and exponential functions (MONO \(p=0.23\), BI \(p=0.10\)). The model's goodness-of-fit, as assessed by the coefficient of determination (\(r^{2}\)), ranged from 0.40 to 0.97 for MONO and 0.44 to 0.98 for BI across all participants. The average \(r^{2}\) values were 0.88 \(\pm\) 0.08 for MONO and 0.91 \(\pm\) 0.07 for BI, indicating a high degree of model fit. Tests for interaction effects between sex and time duration were non-significant, indicating that time duration effects were not dependent on sex. However, significant main effects of sex were observed (\(p<0.01\) for both models), with males showing higher CP and W\({}^{\prime}\) values than females (CP: MONO, 84 W, \(p<0.01\); BI, 91 W, \(p<0.01\); W\({}^{\prime}\): MONO, 8.48 KJ, \(p<0.01\); BI, 7.21 KJ, \(p<0.01\)). In contrast, neither the main effect of sport (cycling vs. triathlon) nor its interaction with time duration was significant, suggesting that CP and W\({}^{\prime}\) estimates were consistent across sports and that sport type did not influence the relationship between test duration and these physiological parameters. Overall, these findings indicate that while sex significantly affects CP and W\({}^{\prime}\) values, the influence of test duration on these parameters is independent of sport type. This consistency supports the applicability of mono- and bi-exponential models for CP and W\({}^{\prime}\) assessments across diverse athletic populations. The estimates for CP and W\({}^{\prime}\) at all time intervals are summarized in Figures 2 and 3. Notably, mono- and bi-exponential models showed lower CP values for durations up to 90 s and 75 s time intervals, respectively, and higher W\({}^{\prime}\) values for time intervals shorter  
Figure 1: Comparison of observed and 60 s modeled power of a 3 MT. Observed power is represented by gray open circles, while modeled power (solid line) used the initial 60 s data (black open circle). The dashed horizontal line represents the CP calculated from 3 MT for comparison. BI function. Importantly, 95% of the data points fall within these limits, indicating that most CP and W\({}^{\prime}\) estimates are within a clinically acceptable range of agreement. Figure 4: Bland–Altman plots comparing \(CP_{3 MT}\) and MONO \(CP_{105}\) (**A**) and BI \(CP_{90}\) (**B**). The dashed lines represent the 95% limits of agreement, and the solid horizontal line represents the mean bias between the models. Mean bias represents the average difference between the two methods; a mean bias of zero suggests no systematic difference between the methods, while deviations from zero indicate a consistent overestimation or underestimation by one method compared to the other. Figure 5: [PERSON]–Altman plots comparing \(W^{\prime}_{3 MT}\) and MONO \(W^{\prime}_{135}\) (**A**) and BI \(W^{\prime}_{90}\) (**B**). The dashed lines represent the 95% limits of agreement, and the solid horizontal line represents the mean bias between the models. Mean bias represents the average difference between the two methods; a mean bias of zero suggests no systematic difference between the methods, while deviations from zero indicate a consistent overestimation or underestimation by one method compared to the other. In the slope analysis comparing the 3 MT with exponential functions (Figure 6), the regression shows that the slope of W\({}^{\prime}\) differs from one for BI (\(p\) = 0.01) but not for MONO (\(p\) = 0.28), indicating a minor deviation from perfect identity in the BI model. For CP, however, the slope is not significantly different from one in either function (MONO \(p\) = 0.53, BI \(p\) = 0.50, Figure 7), suggesting close agreement between methods for CP estimation.