Sports Management: Data and Analytics

SummaryAs the world of professional sports has become more competitive than ever before, organisations and athletes must look for new ways to gain an advantage over their rivals. Data science is one of the most important areas of a lot of modern sports organisations for this very reason. In short, data analytics allow teams or athletes to make better use of their resources and talents, potentially helping them to beat the competition.Sports are often all about the smallest of margins, and if data analytics can help an athlete shave a few seconds off of their time or help a team discover top talent for cheaper, it can mean the difference between success and failure. In professional sports, revenues and profits are driven by success on the pitch, first and foremost. Athletes gain higher wages, and teams bring in more revenue from ticket sales and sponsorships, all of which can be affected by results on the pitch.Data analytics seeks to collect, record and study sports data in order to look for patterns, areas that can be improved on and specific advantages. The use of data has grown across lots of different industries over the past few decades. Computing power and improvements in how we capture and understand data have led to large companies setting up their own data analytics departments.Data analytics doesn't just help to identify strengths and weaknesses on the pitch but can also provide insights into how to improve a business through marketing and other means. With more modern businesses making the most of their data to address shortcomings and make the most out of their resources, sports businesses have been quick to follow.The potential for data analytics has only improved as the technology has gotten better, and today, sports organisations use a variety of techniques to improve performances on and off the pitch. This course aims to provide a foundation on the ideas and methods of sports data analytics, showing how data science can be applied to the sport