A mission that is particularly close to our heart is to teach students that Mathematics and Statistics can also be fun. We all know that having to decipher mathematical formulas and to solve complicated problems are not exactly the most favorite activities by students. In the case of Statistics, this problem is accentuated by a sort of marginality of this subject within the usual Mathematics programs, which makes it generally little known and often misunderstood. However, we believe that there are several ways to involve and excite students, thanks to alternative teaching methods and to the development of finalized application projects. The pair Statistics-Sport is perfect for this purpose, as well highlighted by Guthrie Donald in the review, appeared in the prestigious Journal of the American Statistical Association, of the book by Antonio Mussino, “Statistics and Sports: not just numbers”. The importance of the issue is also evidenced by the interest given to it at the recent MIT SLOAN Sports Analytics Conference, probably the most important international event in the sector, which takes place annually from 2006 in Boston, MA.
From the point of view of the teaching method, it is possible to organize multidisciplinary experiments (involving teachers of Mathematics, Statistics, Computer Science, Sports Science), while from the point of view of the application projects to developed with the students, we can identify a wide range of different specific objectives (analysis of the performances of teams and athletes, monitoring over time, study of attitudes towards sport, analysis of the psychological profile of athletes, …).
In this Project (in Italian) we describe three different teaching experiments that can be carried out as part of a school educational path on Analytics, designed for upper secondary school. Of course it is possible, starting from these ideas, to adapt the work paths and to design new Projects connected with any sport and suitable for any level of education. The three experiments differ from each other for the type of work and the necessary tools (methodological and IT), and ultimately for the skills they are able to develop. For each experiment we describe the main steps to be taken.