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.
Saltiamo tra i numeri – Auhors: Manuel Martini
Più di un gioco – Auhors: Canale Manuel, Munaretto Antonio, Scanagatta Elvira, Chowdhury Shad Enthisar Rahman
Lega Basket A – Statistics – Auhors: Marco Nicola Ivetic, Girardin Pietro, Maria Contin, Marco Illesi
Atletica leggera: allenamenti e gare diventano dati – Auhors: Alberto Spezzapria
Facciamo canestro – Auhors: De Rossi Edoardo, Lazzari Giacomo, Milenković Cristina
Formula 1 /Formula E – Auhors: Antonio Kuo Terng Primultini, Riccardo Zattra
Calcio e Statistica – Auhors: Giovanni Dal Molin, Enrico Rizzi, Paramesh Remigi, Gioele Schiavo
Tra matematica e Premier League – Auhors: Tommaso Nichele; Luigi Matteo Figatti; Giovanni Leon; Kevin Ballotta
La Statistica della pallacanestro – Auhors: Bonollo Federico, Gandioli Giulio, Giuriato Luca, Pizzato Martina, Rigon Alberto
Calcio e Statistica – Auhors: Andrea Moscheni, Matteo Parise, Lorenzo Luigi Scarsella, Leonardo Perozzo
Sport Analytics – Auhors: Cappellotto Andrea, Dal Santo Francesco, Dal Zotto Giorgio, Piccione Jacopo Pedro, Pizzato Eva
Statistica in Pole – Auhors: Bellinaso Marco, Bergamo Tommaso, Bonato Edoardo, Bortoliero Daniele
3 Stagioni di Inter a confronto – Auhors: Maino Camilla, Martini Marta, Tommaso Trevisan
OLIMPIA MILANO vs. VIRTUS BOLOGNA – Auhors: Balbo Giovanni, De Antoni Lorenzo, Vaccaro Luca
L’Italia in pista– Auhors: Brunello Enrico, Di Sciacca Michele, Haireche Rafik, Pastori Pietro
Abstract: Sports has the potential to integrate with different scientific subjects, including materials science and engineering, making it an ideal approach to enhance the students’ affinity toward sustainable education in science, technology, engineering, and mathematics (STEM). Amid gradual educational reformations in the state of Qatar, a distinctive STEM program titled, “Science in Sports” (SIS) was launched to investigate STEM integrated learning in secondary school students. The participant students, 248 students (112 females and 136 males) from 15 different government-operated (public) secondary schools, from rural and urban areas, were given STEM workshops on one of the sports materials, during this pilot study, resultantly challenging them to engineer a sports product. The study employed a mixed-method study in which quantitative approaches were applied to analyze the program effectiveness, with a t-test statistical analysis performed over data collected from a period of five continuous years from 2012 to 2017 in five different cycles. A more dominant data collection included pre and post surveys, substantiating observations of the program facilitator and their schoolteachers were included in this research and development (R&D) study to review the student learning behavior for a qualitative approach. Moreover, the results of the strength, weakness, opportunities, and threats (SWOT) analysis provided an overview of the program’s effectiveness in implicating the engagement of the students in exhibiting their prototypical skills in engineering sports products along with STEM literacy. Apart from understanding the scientific concepts/principles applied in simple sports applications, student attitudes toward STEM fields augmented, as witnessed by the student productivity.
Abstract: As of 2019, sports analytics has grown to be a $780 million industry. Many organizations and institutions contribute to the field through research in exercise science, optimization of in-game decision making, sports marketing, business performance, and sports compliance fields. We propose an open, interdisciplinary approach to sports analytics within institutes of higher education to work across many fields and provide opportunities to diverse members within the community, enable research and communication across fields, serve the surrounding community, and ethically use data.
Abstract: The fusion of sports and analytics has not only revolutionized the way professional basketball is played, coached, and managed; it also has the potential to revolutionize the way we educate the next generation. Sports analytics can provide a rigorous, yet tangible application of math and statistics in which youth perform data gathering and analysis directly linked to their own improved on–court performance. This allows students who are not traditionally engaged in STEM (Science, Technology, Engineering, andMathematics) to be intrinsically motivated to use STEM concepts as a tool for basketball training. We hypothesized that once STEM has shown applicability towards improving their own basketball skills, it would also become more attractive as a career path.Here we provide preliminary data consistent with that hypothesis that shows that these clinics increase athletes selfperception of knowledge and interest in STEM. This approach can be integrated within the sports organization’s existing youth programs to promote STEM education as a public good, and can be replicated in other educational communities, both formal and informal.
Abstract: The adolescents of our society are showing a declining interest in the disciplines of math and science. Science carries an almost negative perception amongst the youth of today. This phenomenon is especially apparent in my community: Albany, New York. Our goal was to spark interest in STEM fields within inner city kids. We related sports-a very popular topic with the kids-to science. This showed them that science is fun when you can apply it to something you’re interested in. Our personal motivations for doing this stemmed from a want to give back to our community. We wanted to make the wonders of science readily available to kids coming up through the local public school systems. Ultimately, we wanted to make our community a better place when we were finished.