This project investigates the impact of biological characteristics on advancements in Olympic running performance. Through rigorous data analysis, we explore how factors such as height, weight, and geographical location contribute to athletes' success in various running events.
We utilized two datasets of historic Olympic medal winners from 1896-2016 obtained from Kaggle, which include attributes like athlete's height, weight, country, and event time. The data underwent extensive cleaning to address missing values and to refine the focus on running disciplines.
https://www.kaggle.com/datasets/heesoo37/120-years-of-olympic-history-athletes-and-results
https://www.kaggle.com/datasets/jayrav13/olympic-track-field-results
Our analysis revealed correlations between an athlete's physical characteristics and the distances they run. Taller athletes tend to excel in shorter distances, while lighter athletes perform better in long-distance events. Geographical analysis highlighted that countries often specialize in events that align with their physiological and environmental strengths.
We identified two different types of runners in terms of BMI: 100m and 200m sprint, and all the other longer diciplines. We observed a trend of specialization over time, with sprinters becoming more muscular, indicative of the explosive power required for short distances, and long-distance runners exhibiting lower body mass indexes (BMIs), advantageous for endurance.
The project underscores the significance of biological factors in athletic performance. By leveraging data analytics, we offer insights into the evolution of athletic specialization in Olympic running events.
Group 1 Course: AM 10 AUT 23