﻿{"id":7275,"date":"2021-03-03T08:05:37","date_gmt":"2021-03-03T07:05:37","guid":{"rendered":"http:\/\/ensai.fr\/?p=7275"},"modified":"2021-03-04T09:39:50","modified_gmt":"2021-03-04T08:39:50","slug":"stats-perform-sportstech","status":"publish","type":"post","link":"https:\/\/ensai.fr\/en\/stats-perform-sportstech\/","title":{"rendered":"Stats Perform\u00a0Partners with ENSAI for its\u00a0Annual Data Challenge\u00a0"},"content":{"rendered":"<p><strong>Data Science and high-level sports are at the heart of ENSAI\u2019s 2021 Data Challenge. On March 3d and 4th, students worked in teams on issues submitted by the French Rugby Federation\u2019s Research and Development Department. All data is provided by <a href=\"https:\/\/www.statsperform.com\/\" target=\"_blank\" rel=\"noopener\">Stats Perform<\/a>, a global SportsTech company.\u00a0 <\/strong><\/p>\n<p>An interview with Andy Cooper, Marketing Manager at Stats Perform.<\/p>\n<h3>Andy, could you present Stats Perform?<\/h3>\n<p><strong>Andy Cooper<\/strong>: Stats Perform is the global SportsTech leader in data and AI technology, providing the most trusted sports data and latest advancements in applying AI and machine learning to deliver better predictions and insights for fan engagement, betting and team performance. As a company, we have collected data across sports for 40 years and currently provide services to over 1,500 customers worldwide.<\/p>\n<p>We possess a data archive which is faster, deeper and broader than any other sports database in the world.<\/p>\n<blockquote><p>This database is used to power our own AI Innovation Center, which is comprised of over 300 developers and 50 AI Scientists and Engineers.<\/p><\/blockquote>\n<p>They are actively building cutting-edge solutions which are providing fans with richer insights during live broadcasts, and teams with predictive performance insights to enhance their analysis and decision-making.<\/p>\n<h3>Stats Perform is the leader in its field: what particular technologies have made the difference?<\/h3>\n<p>There are a number of technologies we have pioneered, across different sports, which are making a big difference in terms of supporting analysts and coaches with applied use of data and AI-derived insights.<\/p>\n<p>In rugby, we have a tool called <strong>RugbyHub<\/strong> which synchronizes match data and video. This synchronization helps coaches and analysts to analyze key phases of play which are specific to a game plan.<\/p>\n<p>We also have the most advanced BI tool in professional rugby, <strong>DataEngine<\/strong>, where analysts can build customized reports to establish longer-term performance trends, across different positions on the field, which can inform decision-making across recruitment and performance analysis.<\/p>\n<blockquote><p>Speaking more broadly, we have recently developed and patented a computer vision tracking technology, AutoStats, which applies AI-enhanced body recognition to fluidly track a player\u2019s location, movement and key in-game involvements, all directly from a broadcast video.<\/p><\/blockquote>\n<p>https:\/\/youtu.be\/5nEzPzyfDdI<\/p>\n<p>This has been pioneered in basketball to help <strong>NBA<\/strong> franchises evaluate elite draft prospects, using video footage from NCAA (university) matches, by comparing season-wide performance outputs which historically could only be generated through in-venue tracking hardware.<\/p>\n<p>This is just one example of how <strong>AI technology is going to change the way analysis is conducted in sports<\/strong> during this decade and beyond.<\/p>\n<h3>How do Stats Perform\u2019s technologies help the coaches and increase the athletes\u2019 performance?<\/h3>\n<p>The key objective for all of our technologies is to <strong>ensure insights can be applied on the training ground<\/strong>.<\/p>\n<blockquote><p>A good example of this is Expected Goals in football (xG), which assigns a value to a shot based on the shot location and the probability that it will result in a goal, taking into account a number of different contextual factors.<\/p><\/blockquote>\n<p>From a coaching perspective, these outputs can be applied to teach attacking players about decision-making in front of the goal \u2013 identifying areas where, based on probability, it is better to pass instead of shooting, because of the difficulty to score from that location. Since xG was introduced, we are seeing fewer shots taking place from long range, which shows the impact that metric is having.<\/p>\n<p>In rugby, we have also developed a success <strong>probability model to rate leading goal-kickers worldwid<\/strong>e. The model takes into account a player\u2019s historical kicking performance, the difficulty of a kick based on the field location and several venue-related adjustments to assign an \u2018Expected Conversion Success Rate\u2019 for goalkickers.<\/p>\n<p>This has been used to power the Kick Predictor, as seen on the AWS match stats during the Six Nations championship, and can also be applied from a coaching perspective because if your opposition possesses a strong goal kicker, discipline in relation to avoiding conceding penalties is going to be crucial in the final outcome.<\/p>\n<h3>Could you name a team whose use of Stats Perform\u2019s technologies led them to victory when perhaps it wasn\u2019t expected in the first place?<\/h3>\n<p>Because we work with so many teams worldwide, it is very difficult to single out individual teams. For example, in football, every team that won the league title in the <strong>top five European leagues<\/strong> last season had services from Stats Perform, as did the winners of the <strong>UEFA Champions League<\/strong> and <strong>Europa League<\/strong>.<\/p>\n<blockquote><p>If we were to highlight successes, I would probably focus on two international football teams that used our Edge Analysis technology, which includes several AI prediction and simulation features, to help them achieve unprecedented success.<\/p><\/blockquote>\n<p><strong>Croatia<\/strong> used the platform to attain insights into their opponents during their run to the 2018 World Cup final, whilst <strong>Qatar<\/strong> also used the platform to aid their match preparation at the 2019 Asian Cup, when they beat South Korea and Japan to win their first-ever confederation title.<\/p>\n<h3>How do fans and bettors benefit from Stats Perform\u2019s technologies?<\/h3>\n<p>Every high-quality sportsbook and fantasy game chooses Stats Perform\u2019s premium sports content to help them create more entertaining and trusted sports betting and fantasy experiences. Today\u2019s sports bettor demands a frictionless sports betting experience.<\/p>\n<p>Betting sites need to provide valuable resources for bettors and keep them entertained with <strong>live scores<\/strong> and rich, <strong>live statistics<\/strong> for thousands of events. Our data is relied upon by millions of bettors around the world and drives more confident decision-making for hundreds of thousands of sporting events per year.<\/p>\n<p><strong>As a part of the Data Challenge at ENSAI, Stats Perform will also hold a conference on Data Science and Rugby for its participants. Find out more about <a href=\"https:\/\/ensai.fr\/en\/entreprises\/devenir-partenaire\/\">ENSAI\u2019s corporate partners<\/a>.\u00a0\u00a0<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Data Science and high-level sports are at the heart of ENSAI\u2019s 2021&#8230; <br \/><a class=\"readmore\" href=\"https:\/\/ensai.fr\/en\/stats-perform-sportstech\/\">Lire la suite<\/a><\/p>\n","protected":false},"author":73,"featured_media":7276,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[391],"tags":[382,417],"class_list":["post-7275","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-school","tag-partnerships","tag-sports"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.9 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Stats Perform\u00a0Partners with ENSAI for its\u00a0Annual Data Challenge\u00a0 | ENSAI<\/title>\n<meta name=\"description\" content=\"Data Science and high-level sports will be at the heart of ENSAI\u2019s next Data Challenge. On March 3d and 4th, students will work in teams on issues submitted by the French Rugby Federation\u2019s Research and Development Department. All data will be provided by Stats Perform, a global SportsTech company.\u00a0\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/ensai.fr\/en\/stats-perform-sportstech\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Stats Perform\u00a0Partners with ENSAI for its\u00a0Annual Data Challenge\u00a0 | ENSAI\" \/>\n<meta property=\"og:description\" content=\"Data Science and high-level sports will be at the heart of ENSAI\u2019s next Data Challenge. On March 3d and 4th, students will work in teams on issues submitted by the French Rugby Federation\u2019s Research and Development Department. All data will be provided by Stats Perform, a global SportsTech company.\u00a0\" \/>\n<meta property=\"og:url\" content=\"https:\/\/ensai.fr\/en\/stats-perform-sportstech\/\" \/>\n<meta property=\"og:site_name\" content=\"ENSAI\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/Ensai35\/\" \/>\n<meta property=\"article:published_time\" content=\"2021-03-03T07:05:37+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2021-03-04T08:39:50+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/ensai.fr\/wp-content\/uploads\/2021\/03\/stats-perform-ensai.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"720\" \/>\n\t<meta property=\"og:image:height\" content=\"421\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Flore Ithor\u00e9-Tilly\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Flore Ithor\u00e9-Tilly\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"5 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/ensai.fr\/en\/stats-perform-sportstech\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/ensai.fr\/en\/stats-perform-sportstech\/\"},\"author\":{\"name\":\"Flore Ithor\u00e9-Tilly\",\"@id\":\"https:\/\/ensai.fr\/#\/schema\/person\/c9cdfe8987c29837993d1a90c7e951d1\"},\"headline\":\"Stats Perform\u00a0Partners with ENSAI for its\u00a0Annual Data Challenge\u00a0\",\"datePublished\":\"2021-03-03T07:05:37+00:00\",\"dateModified\":\"2021-03-04T08:39:50+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/ensai.fr\/en\/stats-perform-sportstech\/\"},\"wordCount\":958,\"publisher\":{\"@id\":\"https:\/\/ensai.fr\/#organization\"},\"image\":{\"@id\":\"https:\/\/ensai.fr\/en\/stats-perform-sportstech\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/ensai.fr\/wp-content\/uploads\/2021\/03\/stats-perform-ensai.jpg\",\"keywords\":[\"partnerships\",\"sports\"],\"articleSection\":[\"The school\"],\"inLanguage\":\"en-US\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/ensai.fr\/en\/stats-perform-sportstech\/\",\"url\":\"https:\/\/ensai.fr\/en\/stats-perform-sportstech\/\",\"name\":\"Stats Perform\u00a0Partners with ENSAI for its\u00a0Annual Data Challenge\u00a0 | ENSAI\",\"isPartOf\":{\"@id\":\"https:\/\/ensai.fr\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/ensai.fr\/en\/stats-perform-sportstech\/#primaryimage\"},\"image\":{\"@id\":\"https:\/\/ensai.fr\/en\/stats-perform-sportstech\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/ensai.fr\/wp-content\/uploads\/2021\/03\/stats-perform-ensai.jpg\",\"datePublished\":\"2021-03-03T07:05:37+00:00\",\"dateModified\":\"2021-03-04T08:39:50+00:00\",\"description\":\"Data Science and high-level sports will be at the heart of ENSAI\u2019s next Data Challenge. On March 3d and 4th, students will work in teams on issues submitted by the French Rugby Federation\u2019s Research and Development Department. All data will be provided by Stats Perform, a global SportsTech company.\u00a0\",\"breadcrumb\":{\"@id\":\"https:\/\/ensai.fr\/en\/stats-perform-sportstech\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/ensai.fr\/en\/stats-perform-sportstech\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/ensai.fr\/en\/stats-perform-sportstech\/#primaryimage\",\"url\":\"https:\/\/ensai.fr\/wp-content\/uploads\/2021\/03\/stats-perform-ensai.jpg\",\"contentUrl\":\"https:\/\/ensai.fr\/wp-content\/uploads\/2021\/03\/stats-perform-ensai.jpg\",\"width\":720,\"height\":421,\"caption\":\"stats perform partners with ensai\"},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/ensai.fr\/en\/stats-perform-sportstech\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Accueil\",\"item\":\"https:\/\/ensai.fr\/en\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Stats Perform\u00a0Partners with ENSAI for its\u00a0Annual Data Challenge\u00a0\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/ensai.fr\/#website\",\"url\":\"https:\/\/ensai.fr\/\",\"name\":\"ENSAI\",\"description\":\"La Science des Donn\u00e9es\",\"publisher\":{\"@id\":\"https:\/\/ensai.fr\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/ensai.fr\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"},{\"@type\":\"Organization\",\"@id\":\"https:\/\/ensai.fr\/#organization\",\"name\":\"ENSAI\",\"url\":\"https:\/\/ensai.fr\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/ensai.fr\/#\/schema\/logo\/image\/\",\"url\":\"https:\/\/ensai.fr\/wp-content\/uploads\/2019\/05\/Ensai-logo.png\",\"contentUrl\":\"https:\/\/ensai.fr\/wp-content\/uploads\/2019\/05\/Ensai-logo.png\",\"width\":493,\"height\":463,\"caption\":\"ENSAI\"},\"image\":{\"@id\":\"https:\/\/ensai.fr\/#\/schema\/logo\/image\/\"},\"sameAs\":[\"https:\/\/www.facebook.com\/Ensai35\/\"]},{\"@type\":\"Person\",\"@id\":\"https:\/\/ensai.fr\/#\/schema\/person\/c9cdfe8987c29837993d1a90c7e951d1\",\"name\":\"Flore Ithor\u00e9-Tilly\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/ensai.fr\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/secure.gravatar.com\/avatar\/f86ed95b523ba36d583949e04974eedc813967e510ad55e33cd993c04c1e0a14?s=96&d=mm&r=g\",\"contentUrl\":\"https:\/\/secure.gravatar.com\/avatar\/f86ed95b523ba36d583949e04974eedc813967e510ad55e33cd993c04c1e0a14?s=96&d=mm&r=g\",\"caption\":\"Flore Ithor\u00e9-Tilly\"}}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Stats Perform\u00a0Partners with ENSAI for its\u00a0Annual Data Challenge\u00a0 | ENSAI","description":"Data Science and high-level sports will be at the heart of ENSAI\u2019s next Data Challenge. On March 3d and 4th, students will work in teams on issues submitted by the French Rugby Federation\u2019s Research and Development Department. All data will be provided by Stats Perform, a global SportsTech company.\u00a0","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/ensai.fr\/en\/stats-perform-sportstech\/","og_locale":"en_US","og_type":"article","og_title":"Stats Perform\u00a0Partners with ENSAI for its\u00a0Annual Data Challenge\u00a0 | ENSAI","og_description":"Data Science and high-level sports will be at the heart of ENSAI\u2019s next Data Challenge. On March 3d and 4th, students will work in teams on issues submitted by the French Rugby Federation\u2019s Research and Development Department. All data will be provided by Stats Perform, a global SportsTech company.\u00a0","og_url":"https:\/\/ensai.fr\/en\/stats-perform-sportstech\/","og_site_name":"ENSAI","article_publisher":"https:\/\/www.facebook.com\/Ensai35\/","article_published_time":"2021-03-03T07:05:37+00:00","article_modified_time":"2021-03-04T08:39:50+00:00","og_image":[{"width":720,"height":421,"url":"https:\/\/ensai.fr\/wp-content\/uploads\/2021\/03\/stats-perform-ensai.jpg","type":"image\/jpeg"}],"author":"Flore Ithor\u00e9-Tilly","twitter_card":"summary_large_image","twitter_misc":{"Written by":"Flore Ithor\u00e9-Tilly","Est. reading time":"5 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/ensai.fr\/en\/stats-perform-sportstech\/#article","isPartOf":{"@id":"https:\/\/ensai.fr\/en\/stats-perform-sportstech\/"},"author":{"name":"Flore Ithor\u00e9-Tilly","@id":"https:\/\/ensai.fr\/#\/schema\/person\/c9cdfe8987c29837993d1a90c7e951d1"},"headline":"Stats Perform\u00a0Partners with ENSAI for its\u00a0Annual Data Challenge\u00a0","datePublished":"2021-03-03T07:05:37+00:00","dateModified":"2021-03-04T08:39:50+00:00","mainEntityOfPage":{"@id":"https:\/\/ensai.fr\/en\/stats-perform-sportstech\/"},"wordCount":958,"publisher":{"@id":"https:\/\/ensai.fr\/#organization"},"image":{"@id":"https:\/\/ensai.fr\/en\/stats-perform-sportstech\/#primaryimage"},"thumbnailUrl":"https:\/\/ensai.fr\/wp-content\/uploads\/2021\/03\/stats-perform-ensai.jpg","keywords":["partnerships","sports"],"articleSection":["The school"],"inLanguage":"en-US"},{"@type":"WebPage","@id":"https:\/\/ensai.fr\/en\/stats-perform-sportstech\/","url":"https:\/\/ensai.fr\/en\/stats-perform-sportstech\/","name":"Stats Perform\u00a0Partners with ENSAI for its\u00a0Annual Data Challenge\u00a0 | ENSAI","isPartOf":{"@id":"https:\/\/ensai.fr\/#website"},"primaryImageOfPage":{"@id":"https:\/\/ensai.fr\/en\/stats-perform-sportstech\/#primaryimage"},"image":{"@id":"https:\/\/ensai.fr\/en\/stats-perform-sportstech\/#primaryimage"},"thumbnailUrl":"https:\/\/ensai.fr\/wp-content\/uploads\/2021\/03\/stats-perform-ensai.jpg","datePublished":"2021-03-03T07:05:37+00:00","dateModified":"2021-03-04T08:39:50+00:00","description":"Data Science and high-level sports will be at the heart of ENSAI\u2019s next Data Challenge. On March 3d and 4th, students will work in teams on issues submitted by the French Rugby Federation\u2019s Research and Development Department. All data will be provided by Stats Perform, a global SportsTech company.\u00a0","breadcrumb":{"@id":"https:\/\/ensai.fr\/en\/stats-perform-sportstech\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/ensai.fr\/en\/stats-perform-sportstech\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/ensai.fr\/en\/stats-perform-sportstech\/#primaryimage","url":"https:\/\/ensai.fr\/wp-content\/uploads\/2021\/03\/stats-perform-ensai.jpg","contentUrl":"https:\/\/ensai.fr\/wp-content\/uploads\/2021\/03\/stats-perform-ensai.jpg","width":720,"height":421,"caption":"stats perform partners with ensai"},{"@type":"BreadcrumbList","@id":"https:\/\/ensai.fr\/en\/stats-perform-sportstech\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Accueil","item":"https:\/\/ensai.fr\/en\/"},{"@type":"ListItem","position":2,"name":"Stats Perform\u00a0Partners with ENSAI for its\u00a0Annual Data Challenge\u00a0"}]},{"@type":"WebSite","@id":"https:\/\/ensai.fr\/#website","url":"https:\/\/ensai.fr\/","name":"ENSAI","description":"La Science des Donn\u00e9es","publisher":{"@id":"https:\/\/ensai.fr\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/ensai.fr\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/ensai.fr\/#organization","name":"ENSAI","url":"https:\/\/ensai.fr\/","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/ensai.fr\/#\/schema\/logo\/image\/","url":"https:\/\/ensai.fr\/wp-content\/uploads\/2019\/05\/Ensai-logo.png","contentUrl":"https:\/\/ensai.fr\/wp-content\/uploads\/2019\/05\/Ensai-logo.png","width":493,"height":463,"caption":"ENSAI"},"image":{"@id":"https:\/\/ensai.fr\/#\/schema\/logo\/image\/"},"sameAs":["https:\/\/www.facebook.com\/Ensai35\/"]},{"@type":"Person","@id":"https:\/\/ensai.fr\/#\/schema\/person\/c9cdfe8987c29837993d1a90c7e951d1","name":"Flore Ithor\u00e9-Tilly","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/ensai.fr\/#\/schema\/person\/image\/","url":"https:\/\/secure.gravatar.com\/avatar\/f86ed95b523ba36d583949e04974eedc813967e510ad55e33cd993c04c1e0a14?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/f86ed95b523ba36d583949e04974eedc813967e510ad55e33cd993c04c1e0a14?s=96&d=mm&r=g","caption":"Flore Ithor\u00e9-Tilly"}}]}},"_links":{"self":[{"href":"https:\/\/ensai.fr\/en\/wp-json\/wp\/v2\/posts\/7275","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ensai.fr\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ensai.fr\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ensai.fr\/en\/wp-json\/wp\/v2\/users\/73"}],"replies":[{"embeddable":true,"href":"https:\/\/ensai.fr\/en\/wp-json\/wp\/v2\/comments?post=7275"}],"version-history":[{"count":5,"href":"https:\/\/ensai.fr\/en\/wp-json\/wp\/v2\/posts\/7275\/revisions"}],"predecessor-version":[{"id":7284,"href":"https:\/\/ensai.fr\/en\/wp-json\/wp\/v2\/posts\/7275\/revisions\/7284"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/ensai.fr\/en\/wp-json\/wp\/v2\/media\/7276"}],"wp:attachment":[{"href":"https:\/\/ensai.fr\/en\/wp-json\/wp\/v2\/media?parent=7275"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ensai.fr\/en\/wp-json\/wp\/v2\/categories?post=7275"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ensai.fr\/en\/wp-json\/wp\/v2\/tags?post=7275"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}