{"id":8228,"date":"2022-02-17T10:00:00","date_gmt":"2022-02-17T10:00:00","guid":{"rendered":"https:\/\/leadersinsport.com\/performance-institute\/?post_type=article&p=8228"},"modified":"2025-12-15T05:11:40","modified_gmt":"2025-12-15T05:11:40","slug":"the-pivotal-role-that-ai-can-play-in-managing-data-fatigue-in-sport","status":"publish","type":"article","link":"https:\/\/leadersinsport.com\/performance-institute\/articles\/the-pivotal-role-that-ai-can-play-in-managing-data-fatigue-in-sport\/","title":{"rendered":"The Pivotal Role that AI Can Play in Managing Data Fatigue in Sport"},"content":{"rendered":"\n\n
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\n 17 Feb 2022 <\/p>\n \t\t\t\t\t\t\n\t\t\t\t\t\t\t<\/span>Articles<\/a>\n\n\t\t\t\t\t\t

The Pivotal Role that AI Can Play in Managing Data Fatigue in Sport<\/h1>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\n \n\t\t\t<\/div>\n\t\t<\/div>\n\n\t<\/div>\n<\/div>\n
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Category <\/div>\n Data & Innovation<\/a> <\/div>\n
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https:\/\/leadersinsport.com\/performance-institute\/articles\/the-pivotal-role-that-ai-can-play-in-managing-data-fatigue-in-sport\/<\/div>\n <\/div>\n <\/div>\n <\/section>\n\n\n\n\n
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A data & innovation article brought to you by our Partners<\/p>\n

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Data fatigue is a longstanding issue in professional sports. As teams collect more comprehensive and diverse datasets, however, the problem is only becoming more acute.<\/h4>\n
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\u201cI experienced it first-hand as a practitioner,\u201d Rich Buchanan tells the Leaders Performance Institute, having previously worked behind the scenes at Swansea City FC, the Wales FA, and other organizations. \u201cThe people tasked with making sense out of assorted data are under immense pressure to interpret information every single day for every single player throughout an entire season. The weight of delivering ROI lies in their hands.\u201d<\/p>\n

Buchanan, who has also worked for organizations in the US and continental Europe, is now the Performance Director at Zone7<\/a>. The company\u2019s artificial intelligence [AI] system is being used by a growing number of top-tier sports outfits as they look to convert data collection into actionable insights for higher levels of athlete performance and availability.<\/p>\n

\u201cIf you have one person undertaking manual analysis and interpretation, it is difficult, if not impossible, to do that consistently well over the course of a campaign,\u201d he continues. \u201cJust as we\u2019ve seen in other industries, I believe AI will play an increasingly important role in helping professionals identify complex risk patterns from an athlete\u2019s data that would otherwise be invisible to the human eye.\u201d<\/p>\n

How does data fatigue manifest? \u201cTypically, sports scientists or fitness coaches are the ones tasked with monitoring players using data-generating tools, like GPS or biometric wearables,\u201d says Buchanan. \u201cMany of these professionals, however, are not data specialists by trade. They are generally sports practitioners whose expertise is better served in \u00a0athlete-facing environments \u2013 on a pitch, in a gym, etc. \u2013 where they work directly with athletes in a practical manner.\u201d<\/p>\n

\u201cRight now, the conventional norm for making sense of athlete performance data in sport requires significant time commitment to examine large datasets. It is a laborious manual analysis and interpretation process, one which often runs counter to why these professionals embarked on a career in sport in the first place. As a result, disenchantment becomes quickly apparent and you see signs of data fatigue setting in as they\u2019re pressured to deliver meaningful insights that can then be practically applied.<\/p>\n

\u201cEven now, as many organizations employ data science personnel, it\u2019s not humanly possible to do this kind of manual analysis and interpretation effectively and consistently for multiple athletes over the course of a season. Combined with the frequency and complexity of new datasets becoming available, the manual approach often results in flawed insights that reduce the value that organizations receive from investments in data collection tools.\u201d<\/p>\n

Buchanan works closely with Tal Brown, CEO and Co-Founder of Zone7, whose extensive background in creating and deploying AI technology with the likes of Salesforce and Oracle has allowed him to witness data fatigue first-hand.<\/p>\n

\u201cThe need to find accurate solutions for harmonizing, analyzing, and interpreting such large volumes of data has never been clearer,\u201d says Brown. \u201cI\u2019ve spent much of my career creating intelligent tools that minimize data fatigue while creating more efficient data analysis processes. This is now becoming a significant challenge for decision makers in sport, especially as they\u2019re tasked with validating and correctly interpreting data from a growing array of different sources. It\u2019s not just game and competition data, we\u2019re also seeing increased amounts of medical, strength & conditioning, sleep and general wellbeing data generated by wearable technologies.\u201d<\/p>\n

The scenario of data fatigue described by Buchanan is not uncommon and Zone7 is aware of the vital need to adopt a \u2018practitioner\u2019s lens,\u2019 continues Brown. \u201cTech innovation and evolution is driven by the need to answer harder questions in more efficient and reliable ways. You need to collaborate with practitioners and ultimately provide the insights that add value in their specific environments.\u201d<\/p>\n

One such practitioner is Javier Vidal, a Performance Coach with Spanish La Liga club Valencia CF. Vidal has used Zone7 in a number of different team environments. \u201cZone7 is a tool I\u2019ve used for several years,\u201d said Vidal. \u201cIts AI has allowed me to adapt my day-to-day routine and get more value of out new data generating technologies that are arising all the time.<\/p>\n

Zone7 has been deployed and operated real time by Vidal at Valencia CF since the start of the 21\/22 season and the number of confirmed injuries has dropped by 52% compared to the previous season. This closely resembles results during his tenure in Getafe another La Liga team, where Vidal saw a drop of 70%, with a 65% reduction in days that first-team players were lost due to injury. \u201cIt would be the work of many people analyzing data all day to gain such useful information, but with Zone7 I get accurate, usable information within minutes that I can immediately put into practice.\u201d<\/p>\n

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Photo: Zone7<\/h6>\n

Buchanan adds that, in the case of forecasting injury risk, AI can also take a complex, multifaceted problem and present it in an easy-to-understand way. \u201cAt the top line, Zone7 presents \u2018athletes at high, medium, or low risk. On top of that, it presents potential actionable solutions, such as, \u2018do more or less in this specific area than you originally intended.\u201d<\/p>\n

Multifaceted problems also create greater risk of blind spots emerging in athlete monitoring. In this case, the relationship between classic sports performance data streams such as external workload, strength and internal workload, and \u2018next gen\u2019 of data points such as heartrate variability [HRV] and biomarkers monitoring stress, sleep or diet presents a margin for error. \u201cWe can create visibility into how those nodes interact in the day-to-day environment,\u201d says Brown. \u201cMore data allows us to calibrate tools that can understand those relationships. Traditional spreadsheet-like tools just don\u2019t offer that functionality.\u201d<\/p>\n

One of the missions driving Zone7 is to give practitioners a sense of security at moments when they are under significant pressure to deliver. \u201cOne of the hardest parts of a coach, analyst, or performance specialist\u2019s job is giving definitive advice on decisions made around athletes,\u201d says Buchanan. \u201cThe number of times these professionals are tasked with doing this under pressure from all directions, with only their own subjective opinion to draw upon, is concerning. Equipping medical, fitness or coaching professionals with the objectivity that AI provides, driven by complex computations, creates more certainty and a stronger case for the advice they provide in that scenario.\u201d<\/p>\n

\u201cHumans, by nature, already have in-built biases,” Buchanan continues. \u201cWe already have opinions about certain athletes; who\u2019s robust and who\u2019s not robust, who\u2019s likely to report muscle tightness, etc. Now, if Zone7 corroborates those opinions, it assures the user. If what Zone7 suggests turns out to be true, then the trust builds. When we suggest something that\u2019s counterintuitive, people may find that uncomfortable because it\u2019s challenging preconceived beliefs. But I would say, in a way, that\u2019s the true value-add that Zone7 brings, highlighting those blind spots. We\u2019re there to make sure those players, and the opportunities to pre-emptively intervene, don\u2019t slip through the net.\u201d<\/p>\n

Brown and Buchanan are excited about the opportunities that lie ahead for data science in professional sports, whether that be 360-degree support for any interaction a player has related to performance, the possibility for longitudinal injury risk profiling, or the ability to support practitioner across a variety of different sports, each with their own cadences. The latter is already underway, with Zone7 being actively applied across American football, basketball, baseball, and rugby, in addition to extensive work in soccer.<\/p>\n

Zone7 will also continue to challenge accepted wisdoms. \u201cRegardless of the value individual practitioners and sports organizations place on data to manage athletes\/players, the industry has been heavily reliant on simplistic data analysis and interpretation for a number of years and, quite simply, there\u2019s now a more refined way of doing it,\u201d says Buchanan. \u201cUsing AI to simulate different training load scenarios with the aim of physically peaking on certain days on the training cycle is just around the corner. \u201cThis is where people can get very precise on how they prepare their players or athletes for future events, rather than best guess periodization models.\u201d<\/p>\n

\u201cUltimately, future sporting success belongs to those who leverage their data in the most efficient, effective and accurate manner. We\u2019re here, primed and ready to help practitioners in sport do just that.\u201d<\/p>\n

To connect with Zone7 directly, please email rory.monon@leadersinsport.com<\/p>\n<\/p>\n <\/div>\n \n \n \n <\/div>\n

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