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Computational modelling in biomechanics and specifically in sport performance has been constantly evolving and developing. However, frequently emphasis has been put sometimes complex modelling and sometimes extremely simplistic techniques that yield results impossible to validate and have little or no practical impact. An example of the former is modelling of cartilage as a multiphase continua and the latter is very evident in a number of publications devoted. However, the problems are normally attributed to modelling but they also lie in the provision of input and validation from both experiments and competition. The above point is illustrated by a practical example of a project on the scale of the propulsive force in swimming. The project relied on combination of computational modelling, experimental data collection including the construction of a robotic arm and data from competition level training sessions. As a result it is now known the level of forces involved in front crawl swimming, and will soon be possible to optimise the stroke trajectory in terms of maximum thrust generated. However, is this sufficient? The human being is not designed to swim so to talk about optimal stroke is ill-founded. Such "optimum" is dependent on physiological constrains and hence more multidisciplinary approach is needed. The problem with the analytical approach presented above is that it enhances the scientific knowledge and understanding but does not show the way ahead in terms of how practically this could be achieved. Currently strong emphasis is given to the rapid feedback provision for the athletes. But this has a lot of limitations as it is hardly rapid and depends on the individual interpretation of the data collected by coaches and technical staff. A parallel development and it up to now a separate one are the so called smart technologies, the best known examples of which are smart materials such as piezoelectric ones and memory shape alloys. Up to know mostly smart materials have been developed and used. They have the propensity to react to change in the environmental parameters. However, their response is limited to a small number of parameters. However, the more recent trend is towards "intelligent" technologies and materials that could offer a variety of responses and differentiate the factors contextually. The author believes that computers will be playing a more prominent role in this development. This is illustrated with some ongoing projects devoted to drug testing and individualised comfort. Possibilities for the use of these novel technologies in sport are discussed. The author strongly believes that such approaches should end the deeply flawed statistical approaches in very near future.