The performance of the Hakamada Akasofu-Fry, version 2 (HAFv.2) numerical model, which provides predictions of solar shock arrival times at Earth, was subjected to a statistical study to investigate those solar/interplanetary circumstances under which the model performed well/poorly during key phases (rise/maximum/decay) of solar cycle 23. In addition to analyzing elements of the overall data set (584 selected events) associated with particular cycle phases, subsets were formed such that those events making up a particular sub-set showed common characteristics. The statistical significance of the results obtained using the various sets/subsets was generally very low and these results were not significant as compared with the hit by chance rate (50%). This implies a low level of confidence in the predictions of the model with no compelling result encouraging its use. However, the data suggested that the success rates of HAFv.2 were higher when the background solar wind speed at the time of shock initiation was relatively fast. Thus, in scenarios where the background solar wind speed is elevated and the calculated success rate significantly exceeds the rate by chance, the forecasts could provide potential value to the customer. With the composite statistics available for solar cycle 23, the calculated success rate at high solar wind speed, although clearly above 50%, was indicative rather than conclusive. The RMS error estimated for shock arrival times for every cycle phase and for the composite sample was in each case significantly better than would be expected for a random data set. Also, the parameter "Probability of Detection, yes" (PODy) which presents the Proportion of Yes observations that were correctly forecast (i.e. the ratio between the shocks correctly predicted and all the shocks observed), yielded values for the rise/maximum/decay phases of the cycle and using the composite sample of 0.85, 0.64, 0.79 and 0.77, respectively. The statistical results obtained through detailed analysis of the available data provided insights into how changing circumstances on the Sun and in interplanetary space can affect the performance of the model. Since shock arrival predictions are widely utilized in making commercially significant decisions re. protecting space assets, the present detailed archival studies can be useful in future operational decision making during solar cycle 24. It would be of added value in this context to use Briggs-Rupert methodology to estimate the cost to an operator of acting on an incorrect forecast.