{"id":51,"date":"2020-04-05T16:53:23","date_gmt":"2020-04-05T20:53:23","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-peopleanalytics\/submission\/moneyball-and-soccer\/"},"modified":"2020-04-05T16:53:23","modified_gmt":"2020-04-05T20:53:23","slug":"moneyball-and-soccer","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-peopleanalytics\/submission\/moneyball-and-soccer\/","title":{"rendered":"Moneyball and Soccer"},"content":{"rendered":"

General consensus usually traces the use of statistics and data analysis in sports back to <\/span>Moneyball<\/span><\/i>, a now famous term coined to describe the Oakland A\u2019s approach to building a competitive baseball team despite having one of the MLB\u2019s most stretched payroll budgets. The concept was rather simple: Instead of relying on the traditional and often subjective knowledge of seasoned player scouts, who watch videos and attend games to judge a player\u2019s ability, the <\/span>Moneyball <\/span><\/i>approach relied on statistical, objective evidence and data analytics to build a roster. This way, small-market teams would be able to compete with much wealthier teams by buying undervalued players and selling overvalued ones.\u00a0<\/span><\/p>\n

 <\/p>\n

The use of data analytics has since seen a significant and widespread increase in the world of sports. There are countless success stories of teams using data analytics to improve scouting, enhance performance, or even predict outcomes. While analytics quickly caught up and brought tangible benefits to sports such as baseball, American football and basketball, the fluid and chaotic game of soccer remained the \u201cleast statistical of major sports\u201d (as per a <\/span>New York Times<\/span><\/i> proclaimed in an article back in 2010 before the World Cup) until recent times. This said, for our analysis we were primarily interested in <\/span>this Financial Times<\/span><\/a> article about soccer clubs using data analytics to improve scouting and sign-on optimal players.<\/span><\/p>\n

 <\/p>\n

The benefits of data-supported scouting are numerous. As the article mentions, using data analytics in the early stages of scouting casts a wider net while searching for players and providing clubs access to markets they would not have previously considered or been exposed to. This is particularly relevant to small and medium sized soccer clubs with limited financial resources, which historically, have been at a competitive disadvantage. The obvious players they wanted were already known on the market and probably well out of their budget. Enter data analytics. Having a 3 person team crunching away at global player performance stats from an office is significantly cheaper, and faster, than employing an army of scouts to go around the world looking for the next big hit.<\/span><\/p>\n

 <\/p>\n

Another big pro of data-supported scouting is efficiency. There are roughly 265 million professional soccer players around the world, without even taking into account youth and amateurs. No human scout can be expected to sort through all this data, look at different metrics and find the next best batch for their soccer club. However, a competent data analytics team can handle all this data efficiently and find the right correlations and compatibility between potential recruits the metrics most relevant to the soccer club.\u00a0<\/span><\/p>\n

 <\/p>\n

A drawback of data analytics, is well, that it is entirely based on objective data. Regardless of how many metrics you capture, there are soft qualities such as team dynamics, temper, motivation and even pure skill that cannot be quantified, measured or predicted upon by complex algorithms and machine learning techniques. That is the beauty of the chaotic and fluid game of soccer. Only the human eye can be trained to pick up on these qualities (so far), and that is why we believe scouts are still critical in the process. They have a keen eye that captures what machines can\u2019t and assess the player\u2019s congruence within a team. All they ever needed was data to direct their vision into the right field.\u00a0<\/span><\/p>\n

 <\/p>\n

As such, even though we are proponents of the use of data analytics in soccer, we don\u2019t see it as replacement but rather a complement of the traditional scouting process. Clubs can now have a credible and reliable shortlist of potential recruits that scouts can leverage to find the ultimate player-club fit. However, as more soccer clubs adopt this approach, we believe that incorporating data analytics into club operations will reach a point of marginal returns as the competitive advantage becomes the competitive norm.<\/span><\/p>\n

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Source:<\/p>\n

https:\/\/www.forbes.com\/sites\/robertkidd\/2018\/11\/19\/soccers-moneyball-moment-how-enhanced-analytics-are-changing-the-game\/#34471ea76b20<\/span><\/a><\/p>\n

https:\/\/www.nytimes.com\/2019\/05\/22\/magazine\/soccer-data-liverpool.html<\/span><\/a><\/p>\n

https:\/\/www.ft.com\/content\/84aa8b5e-c1a9-11e8-84cd-9e601db069b8<\/span><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Was Brad Pitt really onto something? How data analytics is changing the way soccer clubs scout and sign new players<\/p>\n","protected":false},"author":11026,"featured_media":53,"comment_status":"open","ping_status":"closed","template":"","categories":[427,429,428],"class_list":["post-51","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry","category-data-analytics","category-scouting","category-soccer","hck-taxonomy-industry-sports"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-peopleanalytics\/assignment\/lpa-blog-assignment\/","yoast_head":"\nMoneyball and Soccer - Leading with People Analytics<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/d3.harvard.edu\/platform-peopleanalytics\/submission\/moneyball-and-soccer\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Moneyball and Soccer - Leading with People Analytics\" \/>\n<meta property=\"og:description\" content=\"Was Brad Pitt really onto something? 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