Data Analytics in Sports Technology

By Loren Straub, Principal, Bowery Capital

Loren Straub, Principal, Bowery Capital

How Analytics Is Changing the Field of Sports?

It’s no secret that the growth of machine learning has the potential to revolutionise the sports world. One of the biggest areas wehave been viewing that change is in analytics. From real-time performance evaluation to ROI advertising analysis, new startups have been helping virtually all interested parties in the sports world make data-driven decisions. Here are some of the largest trends we’ve been paying attention to and what they mean.

First, Talent Acquisition & Performance Enhancement

From the NHL to the NFL and everywhere in between, we have all heard stories of late round draft picks rising to stardom. Tom Brady is no doubt the most notable example. The fact that he is the NFL’s best player across virtually all metrics is astonishing when you recall that he was the 199th pick of the 2000 draft. As machine learning has been applied to the sports business, startups have developed a way to solve this problem. Brooklyn Dynamics has developed an AI platform directed towards talent identification with customers ranging from MLB World Series champions to F1- racing teams. Impressively, the system has achieved a 97% accuracy rating in MLB and NFL drafts with forecasts including player comparisons, salary modelling, and even in-game scenario responses. Another great example is Sportlogiq which uses cameras to track the movement of players during games and produces an evaluation of their skills and potential. Currently used by 24 NHL teams, coaches leverage its information to improve their teams and evaluate opponents’ weaknesses.

Second, Injury Prevention

Arguably the largest market inefficiency within pro-sports is player injury. Not only does it mean billions of dollars lost, but it can also result in a lifelong impact of the player. One company focused on solving this massive problem is Catapult. Founded in 2006, the company is now traded publicly on the Australian Exchange. Focused predominantly on wearable technology, Catapult offers a variety of products that can monitor over 1,000 data points per second and aggregate data on performance trends to produce actionable alerts about players at risk of injury. Another key player in injury protection is Kitman Labs. Headquartered in Ireland, Kitman Labs uses a software-only approach linking data to medical records and providing individualised alerts that they claim reduce season-ending injuries by 65%.

Third, Marketing Optimization

A 2014 McKinsey report found that one-third to one-half of U.S. companies don’t have a comprehensive system in place to measure sponsorship ROI. Enter companies like vBrand and Block Six Analytics. Isreal-based vBrand is an AI platform that identifies objects, brands, and logos in videos and images to calculate ROI from sponsorship. Block Six Analytics, through their proprietary, “Partnership Scoreboard,” lets teams, brands, and agencies measure and analyse value created through advertising. One example they tout is Pepsi which was able to compare value generation of two advertising proposals and make real-time changes to a digital advertising platform and extract maximum value.

Legacy problems within sports including but not limited to outdated talent acquisition standards, consistent player injury, and unclear sponsorship ROI made it a great candidate for machine learning. As that machine learning has improved, so too have the results and while it’s gone a long way, we believe there’s much more to come. We look forward to monitoring these trends within the sports industry and to keep our eyes peeled for the next key player.

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