Introduction:
This blog post aims to challenge a prevalent view in sports analysis that prioritizes in-depth knowledge of the sport over expertise in analytics. It stems from a disagreement with a statement made by Dean Oliver at the Opta Forum and seeks to highlight the crucial role of analytics in today’s data-rich sports environment.
The Misconception:
During the Opta Forum, Dean Oliver emphasized the importance of “knowing the sport first, analytics second.” This statement implied that deep knowledge of a sport outweighs analytics expertise for effective performance analysis. However, I strongly disagree with this notion and voiced my disapproval on social media.
Changing Dynamics:
While it is essential for professionals in performance analysis to understand the intricacies of a sport, this knowledge alone is no longer sufficient in an analytics-driven era. Analytics is all about analyzing large amounts of data, including big data. Therefore, the primary requirement for effective data analysis is a comprehensive understanding and experience with advanced analytic techniques and tools. Such expertise is indispensable for efficient and meaningful analysis across various data sets.
The Role of Performance Analysts (PAs):
I am not advocating for the replacement of Performance Analysts (PAs) by data analysts/scientists. However, PAs should acknowledge that they are not fully equipped to exploit the vast amount of data available to them in today’s sports landscape. Their historical focus on video analysis has limited their familiarity with statistical analysis, hindering the broader adoption of analytics in team sports, particularly football.
Introducing the Performance Data Analyst (PDA):
To bridge the gap between performance analysis and analytics, I propose the introduction of a Performance Data Analyst (PDA) role within clubs. The PDA would spearhead the performance data analysis task and assist PAs in improving their data analysis skills. Unlike PAs, the PDA does not require an in-depth knowledge of the sport. Their interactions primarily involve PAs, coaching staff, and the head coach. Thus, the PDA’s role does not demand the same communication skills as a PA, as highlighted by Dean Oliver’s slide.
Challenges and Opportunities:
Unfortunately, my suggestion, which I presented at the ISPAS conference in Carlow, has faced resistance, including contempt from certain individuals. The reluctance to adopt this approach stems from PAs’ resistance to challenge their role as “analysts” and the scarcity of data analysts/scientists within the sports industry. Additionally, the lower salaries offered by sports clubs compared to business companies make it difficult to attract passionate data analysts/scientists. This point was eloquently discussed by Ben Alamar in an article I shared on my social media.
Conclusion:
In conclusion, I believe that expertise in analytics plays a fundamental role in sports analysis today. While knowledge of the sport remains important, it is imperative to recognize the significance of advanced analytic techniques and tools for efficient and effective data analysis. By integrating the role of a Performance Data Analyst (PDA) alongside traditional Performance Analysts (PAs), clubs can unlock the full potential of the wealth of data available to them. However, overcoming resistance and addressing the scarcity of data analysts/scientists in the sports industry are significant challenges that need to be addressed.
#analytics Since the NBA was first on analytics in the late 90’s – what chance for soccer? http://t.co/WCwvYELlEo pic.twitter.com/c8RghCttlM
— Johan (@soccerlogic) July 25, 2015
(Note: with the acronym PAs I am also referring in general to any member of the coaching staff who is involved in data analysis)