Foreword
I am delighted that the Clyde Street blog will host three guest posts written by Jamie Coles.
I was introduced to Jamie during his undergraduate course at Cardiff Met. He is now a Masters student in performance analysis and is exploring practitioner effectiveness. I have followed Jamie’s work with great interest.
One of the aims of the guest posts is to share with you, and invite your participation in, a survey Jamie has compiled. Link.
Jamie’s first post in the series asks ‘What Makes the Perfect Sport Performance Analyst?’.
What Makes the Perfect Sport Performance Analyst?
#PerformanceAnalystLearning #EducationToConsultation #RelevanceToIntelligence
Introduction
What makes the perfect sport performance analyst or practitioner is a three part blog series, which explores the learning journey of practitioners and the skills that are associated with effective practice. The introductory blog, explores the skills and learning journey of a practitioner, that leads onto a second post that is associated with a research project exploring the qualities, behaviours and characteristics that are associated with effective practice. With the final blog, publishing the results of the research.
Placing emphasis on the what makes the perfect sport performance analyst blog. On Monday I – humbly – joined a group of the UK’S most sophisticated thinkers of all things data visualisations for a half a day conference at Oxford University. The break out sessions were fantastic, and the number of people in each allowed for outstanding, expert driven, discussions. The best discussions focused on issues related to teaching data science by Sir Nigel Shadbolt, which inevitably led to a discussion on the skills needed to be a fully perfect data scientist. Consequently, the discussion sent me off on a number of directions. One that was of particular interest was the suggestion of what skills are required to make the perfect performance analyst. I see enormous space and opportunities here for the performance analysis and sport analytics community to leverage discussion and cross – pollinate surrounding this topical debate. In doing so, I’ll open proceedings talking about the personification horizon surrounding practitioners learning, and the misconnected depositories of sport performance analytics that transcends difficulty into to a connected framework for the industry to explore. Concluding, with the exploration of the modern intertwined discipline strands of Sport Performance Analytics and the contemporary skillset for the sport analytics community to explore on what makes the perfect performance analyst.
Personification horizon of practitioner learning
The personification of practitioner learning, has been highlighted that practitioner development occurs in a variety of internal, unmediated and mediated learning situations and contexts. This learning environment contains a variety of mediums for the practitioner to engage with and through deliberate reflection. By engaging in this process, practitioners develop their overall skillset of a practitioner and continue their evolution learning journey from a newcomer to an innovator within the field.
Being inspired, by the proposition of unmediated learning situations and the digital learning concepts of sport performance analytics practitioners, which has been explored by Keith Lyons (here). The growing power of digital platforms has allowed the empowerment of perpetual self improvement within the industry, allowing individuals to learn skill orientations to path personal productivity and professional attributes in an ever changing field. Allowing, professionals a “digital self – awareness, self – reflection, self – perspective footprint” of the industry in the following ways:
- Biography and professional context
- Practice development
- Core concepts and key ideas
- Continuing professional learning
- Observations and evaluation industry leaders
- Mentorship
Given this creative plurality and changing landscape, the network age, ultimately within our industry has created opportunities and discrete mini networks to exist within the field, to continuously discover new ideas, new thinking and new resources relevant to the industry and profession. But importantly, offers industry professionals to connect, curate, discuss the industry practice, and as such, allows transfer knowledge realism within the industry media to support the lifelong learning journey of the sport performance analytics community.
Rather, than the traditionalist view of talking about competitive advantage avenues or bridging the different theoretical principles +/ literature gap into the the performance analytics discipline, which often has narrow and restrictive dialogue.
These resentments are growing for community sharing. However, I can’t help noticing after the pockets of great content being published, the lack of engagement and reciprocal altruism to cross – pollinate viewpoints and practice ideas. Also, the lack of media content, which is truly relevant to field based practice and skills within industry media. Also industry sharing platforms to connect, curate and discuss industry practice realism from all corners of the world. For example, exploring relevant industry skills, topics, modes of methodology, technology podcasts/conversations and resources. I must applaud Rob Carroll (here), Josh Bryan (here), Chad Murphy (here), Keith Lyons (here), Darrell Cobner and Cardiff CPA (here) distributing content and industry present +/ past practitioners Sam Robertson (here), Brain Prestige (here) and Peter Clark (here). I understand that there can be reluctance to contribute, couple with restrictions imposed by pursuing competitive advantage and organisation to prevent interaction. Inauspiciously, this the very nature of the elite sport industry. At this point one must question – if the sport science (i.e. Jo Clubb and Mladen Jveckavic) and strength and conditioning (i.e. historic performance) domains can offer this exact virtual media in the same elite competitive environment, why can’t the sport analytics industry adopt similar virtual media for the sport analytics community to explore.
To some extent, these horizons reflect the current narrowness of broadcasting literature and broader stress of challenging times ahead. But in other respects, they mirror fundamental similarities and challenges between the landscape of sports performance analytics and other sports science domains. In doing so, there no reason not experiencing the lifelong learning journey of sport performance analytics together, exploring and discussing the new, and improving the old would be more beneficial and progressive for the industry, rather than working within the silos that is currently prominent in the industry. Conceptually, as sport performance analytics is so diverse, ultimately, within our industry, not one person, department, organisations and league has all the answers, thereby there is plenty of room for groups to co – exist independently in the learning habitat to support the lifelong learning journey of the sport performance analytics community.
Darrell Cobner offered a fantastic final personification for the current sport performance analytics community to aid the current and future lifelong learning journey horizon of sport performance analytics.
Ultimately, within our industry, we are all leaders and we are all followers. There is no real hierarchy, just a series of groups with their own agendas/ambitions with many more shores to discover and bridges to build, but there is plenty of room for groups to co-exist independently in the habitat. Just try not to leave yourself marooned…
Misconnected Depositories and Personification of Sport Performance Analytics
Unarguably in today’s hyper competitive marketplace, performance analysis plays an indispensable role for organisations that seek to personalise experience and create value from available data. Analysing performance through just video and descriptive statistics without integrating the scope of large datasets would be considered a sublime concept in contemporary 
practice. Now, and in the future, the obsessive application of large – scale data to understand unique user needs and desires will form the key basis of competitive advantage for sporting organisations. Transcendentally, this will leash new waves of innovation, discipline methodology and job transformation and productivity.
Presciently, multiple job descriptions and explanations are encrypted with confusion of the same role, which make it harder for students, practitioners and the community to clearly understand what a performance analyst +/ practitioner is and does. Frankly speaking, creating distorted expectations from sporting organisations towards a practitioner’s role, and provides little focal serenity for practitioners /+ students to develop personal career expertise. This dysfunction is not helped by the inconclusive terms “Performance Analysis” and “Sport Analytics”. As both terms “Performance Analysis” and “Sport Analytics” are a bit of a misnomer, this has lead to an utter lack of agreement on what a curriculum on this subject would like, and has lead onto an imbalance on skills being learnt in academia institutes. The difficulty in defining these practice skills is that the split between substance and methodology is ambiguous, and as such it is unclear how to distinguish among industry experts, the integration and overlapping of differing subject domains and skills into Sport performance analytics.
What is clear, however, is that one needs to learn a lot as they as aspire to become a fully component practitioner. One thing is for sure; you cannot become a practitioner overnight. It’s a journey, for sure a challenging one. But how do you go about becoming one? Where to start? When do you start seeing light at the end of the tunnel? What is the learning roadmap? What tools and techniques do I need to know? How will you know when you have achieved your goal?
The Lifelong learning Journey to be a Successful Practitioner
Unfortunately, simply enumerating text and tutorials does not untangle the knots. Therefore, in an effort to simplify the discussion, and simply the lifelong learning journey of the sport performance analytics. I have modestly attempted at creating a learning plan that one can use in this becoming a sport performance analytics practitioners. I took inspiration from the Venn clock and metro maps, and used it to explore skills of a practitioners and to depict the learning path. I have organised the Venn clock as a clean and simplified as possible, to use as an infrastructure for the community to brainstorm and articulate ideas as an avenue for to explore. As a starter pack I have designed the learning clock in to the following domains:
- Skills
- Fundamentals
- PA Software
- Excel
- Video Production
- Visual Analytics
- Statistics
- Programming
- Machine Learning
- R – Programming
- Theory
- What’s Next?
In order, to follow the path the Venn Clock I have created a learning Metromap, with a simplistic pathway to follow, challenge and explore. Please don’t use it as an assumptive checklist; but instead as an evolving learning journey to supplement the journey of lifelong learning of Sport Performance Analytics. In introducing, the Metromap learning journey. I have organised the overall plan into the following domains:
- Skills
- Fundamentals
- PA Software
- Excel
- Video Production
- Visual Analytics
- Statistics
- Programming
- Machine Learning
- Text Mining
- Data Ingestion
- Data Munging
- R – Programming
- Sport Performance Analytics Theory
Each domain is represented as a “metro line”, with the stations depicting the topics you learn, relearn, and understand in a progressive fashion. The idea is you pick a line, catch a train and go through all the stations (topics) till you reach the final destination (or) switch to the next line. I have progressively marked each station (line) 1 through 13 to indicates the order in which to travel. You can use this as an individual learning plan to identify the areas you must want to develop and acquire the skills. You can if you wish just work your way around the MetroMap, but don’t feel constrained to do this in order. One great things about Sport Performance Analytics is that people come to it from all walks of life. If you already understand one of the section, simply skip it. Likewise, don’t be surprised if you find yourself going back to stations more than once.
Final Remarks
Such waves of innovation and new avenues have just begun to ripple out in the industry. As a consequence, there are innumerable exciting application of Sport Performance Analytics, limited only by our imagination. Thereby, an individual’s lifelong journey of Sport Performance Analytics is critical.
I hope this brief illustration has provided exposure into what the perfect sport analytics practitioner is and what it takes to get there. By considering these avenues and questions at a high level I hope it brings some clarity to the hurdles mentioned earlier in the article. I am sure I have overlooked many important skills, qualities and domains to challenge my thoughts. As always I welcome any and all comments.
As a resonance, I see enormous opportunity for the community to open conversation surrounding and spark challenges into what does it take to be a perfect sport performance analytics practitioner. As a community by connecting and sharing thoughts we can shape and transform practice. As a folksonomy to support this sharing. I have chosen #SportPerformanceAnalyticsLearning #EducationToConsultation. I hope to provide a series of blogs that introduce the thoughts, opinions and perceptions of academics, practitioners and consultants to this roundtable of discussion.
Thanks for reading!
Jamie
