Sports Analytics Innovation Summit 2014 San Francisco: Day 1 Highlights
Highlights from the presentations by Analytics leaders from San Francisco 49ers, United States Olympic Committee, and Chelsea FC on day 1 of Sports Analytics Innovation Summit 2014 in San Francisco.
Whether secretly or openly, sports organizations around the world are increasingly getting on board with analytics. Whether it's to identify an edge in performance from players or finding one away from the field of play, using data to inform decisions is becoming essential.
The Sports Analytics Innovation Summit (September 10 & 11, 2014) was organized by the Innovation Enterprise at San Francisco. From the bleeding edge of performance enhancement to fan engagement & business analysis, a wide spectrum of topics were discussed. Experts shared their thoughts on how analytics are constantly evolving the way the sports industry operates, in every sense.
We provide here a summary of selected talks along with the key takeaways.
Here are highlights from Day 1 (Wednesday, September 10, 2014):
Brian Hampton, Director, Football Administration & Analytics, San Francisco 49ers described the role of Analytics in Football through his talk "Implementation of Analytics: What Actually Benefits Teams". With 22 players involved and the specific goals of each play not always defined, football provides a challenge for analytics. The NFL anti-technology rule prevents the use of computers during games so that the best athletes and coaches, not the best software developers, determine the outcome. Decisions such as when to use a time-out, punt, try a two-point conversion, spike, kick a field goal on 1st down or kneel are the aspects of the game which can be measured and defined. These are also areas where a game or two each week is won or lost.
Through an interesting role playing example, he demonstrated what kind of Analytics go into making the crucial decisions in the game in order to maximize the chances of winning. Coaches often need to decide within seconds whether to go as per the advice from Analytics guy or go by their own instinct. No matter how promising Analytics might seem, if it does not work, it can easily get them fired.
Talking about the history of analytics in the NFL, he mentioned that the original draft trade value chart was a retrospective analysis of what had happened so far, and had nothing to do with strategy (or what gives you an optimal trade). More than 80% teams still use it today (though they would keep it secretive), even though the numbers on paper do not necessarily work well on the ground.
Analytics can be very useful to coaches for several purposes, such as Offense can have more refined goals for a given down/distance, and Defense can focus on decreasing the opponent’s chances of winning. However, there are also things where Analytics can hardly offer any advice to the coach, such as: besides gaining yards, what were the intentions of the play call?
Mounir Zok, Senior Sports Technologist, United States Olympic Committee gave a thought-provoking talk on "Using Data Correctly - How Do You Tell the Team?". 5 years ago, we were focusing on data collection tools and methodology. Today, this process is seamless; today, it is extremely easy to get hold of vital, physiological and activity data. Our present challenge is really about the system that holds the data together and to answer a very simple question: how might we help our clients/partners benefit from reliable and easy-to-understand information. Within this context, human-centered design and lean development principles can prove to be major assets. Mounir shared some stories from the US Olympic teams inspired by these assets.
Talking about future, he described "tactile internet" which will improve internet reaction time from 25 millisecond to 1 millisecond. This will make information transfer a commodity, and the innovation will be based on real-time execution of the learning from Analytics. 21st century will observe "Industrial Internet Revolution", where minds and machines operate collaboratively in a seamless manner.
Analyzing the performance of athletes in standardized environments is something of the past. Today, we need to capture performance in the natural field of play. Wearable technology is making an unprecedented impact on the field of sports.
To advance sports, Analytics must:
- Empathize with coaches and athletes - discover your users and learn as much as you can about them
- Define the real need - construct a point of view that is based on user needs and insights
- Ideate for the most optimal solution - brainstorm and come up with creative solutions
- Prototype & test - build a nimble cycle of technology development & begin testing with your users
Jo Clubb, Lead Sport Scientist, Chelsea FC shared her experience of applying Analytics to Soccer in her talk "Managing the 'Art' & 'Science' of Data Analytics in the English Premier League". The expansion of data collection and Sport Science in English football over the past few years has been unstoppable. The challenge to those working in it is to manage, interpret and communicate this information to colleagues in a valuable manner, whilst balancing with the ‘art’ of football. Jo presented case studies of some successful (and less successful) applications of data in this high pressure and unpredictable environment from the past five years and discussed the lessons that have been learnt.
As sports science has grown in influence, there is increased tension between managers and their backroom staff. Sports scientists want to dictate, believing that their data should be unquestionable. Analytics also needs to be used carefully, because improper or excessive use may stifle the enthusiasm of players. Performance in Soccer comprises of a lot of factors such as physical, tactical, emotional, psychological, technical and circumstances. The art and science of analytics impacts several aspects of the game including training analysis, fitness fatigue, physical profiling, youth development and injury rehabilitation.
She emphasized on the contextual, environmental and cultural factors that need to be considered along with Analytics, in order to drive towards the desired results. She concluded her talk saying that data can add value, but soft skills are as important as data itself.
Highlights from Day 2.
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