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tokens: Table 6 shows a comparison of the jet half-opening angles derived from the best fits in this work with hydrodynamical modelling performed by Ryan et al. ( 2015 ) for four GRBs common to both studies. Our model produces systematically narrower jets (most likely caused by the model attempts to fit the early-time luminosity) that are partially consistent with Ryan et al. ( 2015 ) in errors (e.g. GRBs 051016B and 060614), and where they are not (e.g. GRB 061006), they are broadly consistent to ∼2σ–2.5σ. Table 6. Table showing the half-opening angles (in radians) for four GRBs, calculated from f B = 1 − cos (θ j ). θ j values are from the global best fits of this work (uncertainties are 95 per cent confidence interval); θ 0 values are from Ryan et al. ( 2015 ). Comparing our results with that of Gompertz et al. ( 2014 ), we can see the inclusion of fallback accretion within the propeller model allows for an improvement in fitting the ‘tail’ of the fading afterglow. This can be seen in GRBs 051227, 060614 and 061006, where Gompertz et al. ( 2014 ) did not produce such good fits to the tail. Hence, fallback accretion is a necessary addition to the propeller model in order to fully explain the energetics and morphologies of SGRBEEs. Additionally, the extended model handles variability and flares within the data much more naturally than Gompertz et al. ( 2014 ) and copes with the early-time luminosity detected by BAT. The parameters derived from the fits in Fig. 6 are presented in Table 7 . We find that the magnetic fields derived from the fits are in the moderate to high end of the parameter space and that the sample generally has slow initial spins. The slow initial spins are most likely due to the additional fallback spinning the magnetar up and, therefore, the constraints on high initial spin rates is relaxed. This has an impact on the value of the magnetic field derived as the fit moves along the correlation between B and P i discussed in Gompertz et al. ( 2014 ). The sample fits also tend to favour massive discs and narrow jet opening angles. This is most likely due to the model extracting as much of the available energy as possible to fit the high luminosities at early times in the light curve, data which was not included in the fits of Gompertz et al. ( 2014 ). The values of ε, δ, η dip and η prop are widely distributed throughout the parameter space. The derived parameters are consistent with predictions for a magnetar (Giacomazzo Perna 2013 ; Mereghetti, Pons Melatos 2015 ; Rea et al. 2015 ) and are also consistent with the results in Gompertz et al. ( 2014 ). Table 7. Parameters derived from the best global fits to the SGRBEE sample (bold values in Table 5 ). Reported errors are 95 per cent. Values marked with an [L] have reached a parameter limit; those marked with [F] were fixed during fitting. The values are also presented to indicate goodness of fit. We will now examine how increasing the number of free parameters affects the fits