{"id":62852,"date":"2021-04-20T17:06:50","date_gmt":"2021-04-20T16:06:50","guid":{"rendered":"https:\/\/datascientest.com\/?p=62852"},"modified":"2023-11-09T13:35:08","modified_gmt":"2023-11-09T13:35:08","slug":"expected-goals-comprendre-les-maths-qui-se-cachent-derrieres","status":"publish","type":"post","link":"https:\/\/datascientest.com\/expected-goals-comprendre-les-maths-qui-se-cachent-derrieres","title":{"rendered":"Expected goals : Comprendre les maths qui se cachent derri\u00e8re"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"62852\" class=\"elementor elementor-62852\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-30c9cfc elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"30c9cfc\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-d7ed513\" data-id=\"d7ed513\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-215092e elementor-widget elementor-widget-heading\" data-id=\"215092e\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-heading-title{padding:0;margin:0;line-height:1}.elementor-widget-heading .elementor-heading-title[class*=elementor-size-]>a{color:inherit;font-size:inherit;line-height:inherit}.elementor-widget-heading .elementor-heading-title.elementor-size-small{font-size:15px}.elementor-widget-heading .elementor-heading-title.elementor-size-medium{font-size:19px}.elementor-widget-heading .elementor-heading-title.elementor-size-large{font-size:29px}.elementor-widget-heading .elementor-heading-title.elementor-size-xl{font-size:39px}.elementor-widget-heading .elementor-heading-title.elementor-size-xxl{font-size:59px}<\/style><h2 class=\"elementor-heading-title elementor-size-default\">Le nombre d\u2019expected goals est un nouvel indicateur de performances apparu tr\u00e8s r\u00e9cemment dans l\u2019analyse du football. Cette statistique est de plus en plus utilis\u00e9e pour interpr\u00e9ter la physionomie d\u2019une rencontre, mais savons nous vraiment comment l\u2019interpr\u00e9ter ?<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8cfdc6c elementor-widget elementor-widget-text-editor\" data-id=\"8cfdc6c\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-text-editor.elementor-drop-cap-view-stacked .elementor-drop-cap{background-color:#69727d;color:#fff}.elementor-widget-text-editor.elementor-drop-cap-view-framed .elementor-drop-cap{color:#69727d;border:3px solid;background-color:transparent}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap{margin-top:8px}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap-letter{width:1em;height:1em}.elementor-widget-text-editor .elementor-drop-cap{float:left;text-align:center;line-height:1;font-size:50px}.elementor-widget-text-editor .elementor-drop-cap-letter{display:inline-block}<\/style>\t\t\t\t<p><span style=\"font-weight: 400;\">Cet article a pour but de vous pr\u00e9senter le plus simplement possible les r\u00e9alit\u00e9s math\u00e9matiques qui se cachent derri\u00e8re les expected goals (xG). Les r\u00e9sultats pr\u00e9sent\u00e9s sont issus d\u2019une simulation r\u00e9alis\u00e9e par David Sumpter sur la cha\u00eene youtube Friends of Tracking sur les donn\u00e9es de la premi\u00e8re league sur une saison enti\u00e8re .<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-507d61a elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"507d61a\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-c5e58ee\" data-id=\"c5e58ee\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-8689d62 elementor-widget elementor-widget-heading\" data-id=\"8689d62\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Qu\u2019est-ce qu\u2019un expected goal ?\u00a0<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e0e3256 elementor-widget elementor-widget-text-editor\" data-id=\"e0e3256\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Qu\u2019est-ce qu\u2019un xG ? A quoi correspond un score de 2.71 \u00e0 0.78 en xG ?<\/span><\/p><p><strong>A chaque tir effectu\u00e9 lors d\u2019un match, il est possible d\u2019attribuer une probabilit\u00e9 pour que la balle se retrouve au fond des filets<\/strong><\/p><p><span style=\"font-weight: 400;\">Par exemple, un tir des 35 m\u00e8tres aura une tr\u00e8s faible probabilit\u00e9 de r\u00e9ussite (peut-\u00eatre 5% donc 0.05 xG) alors qu\u2019un tir sur p\u00e9nalty aura de bonnes chances de tromper le gardien (76% donc 0.76 xG). En additionnant les expected goals de tous les tirs d\u2019un match, nous obtenons donc un score en xG.<\/span><\/p><p><span style=\"font-weight: 400;\">Par rapport au score classique qui ne comptabilise que les buts, l\u2019avantage des xG est qu\u2019ils sont calcul\u00e9s sur un plus grand nombre d\u2019\u00e9v\u00e9nements. Ils refl\u00e8tent donc souvent la physionomie d\u2019une rencontre et permettent bien souvent d\u2019identifier l\u2019\u00e9quipe qui a eu les plus grosses occasions.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-db4d245 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"db4d245\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-d6be523\" data-id=\"d6be523\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-34e2b87 elementor-widget elementor-widget-heading\" data-id=\"34e2b87\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Mais alors comment est calcul\u00e9e cette probabilit\u00e9 ? \n<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3867dbb elementor-widget elementor-widget-text-editor\" data-id=\"3867dbb\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Pour comprendre cela, construisons ensemble un mod\u00e8le d\u2019expected goals tr\u00e8s simple. Partons de l\u2019intuition suivante : <\/span><b>plus vous \u00eates loin du but, plus vous aurez de mal \u00e0 marquer<\/b><span style=\"font-weight: 400;\">. Dans notre mod\u00e8le, la probabilit\u00e9 de marquer sera \u00e9tablie en ne consid\u00e9rant que la position du tir.\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Nous allons donc visualiser la r\u00e9partition des tirs dans l\u2019espace en 2 dimensions.<\/span><\/p><p><span style=\"font-weight: 400;\">Voici ce que l\u2019on obtient sur une saison compl\u00e8te de football en premi\u00e8re league :<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-38461b8 elementor-widget elementor-widget-image\" data-id=\"38461b8\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-image{text-align:center}.elementor-widget-image a{display:inline-block}.elementor-widget-image a img[src$=\".svg\"]{width:48px}.elementor-widget-image img{vertical-align:middle;display:inline-block}<\/style>\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"439\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-126.png\" class=\"attachment-large size-large wp-image-62903\" alt=\"Number of shot\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-126.png 1024w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-126-300x165.png 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-126-768x422.png 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\">Cette visualisation ainsi que tous les graphiques qui suivent sont r\u00e9alis\u00e9s par David Sumpter, professeur de math\u00e9matiques appliqu\u00e9s \u00e0 l\u2019universit\u00e9 de Uppsala. David a notamment cofond\u00e9 la cha\u00eene Friends of Tracking sur laquelle vous pourrez trouver du contenu riche sur le football analytics :<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-204b795 elementor-widget elementor-widget-text-editor\" data-id=\"204b795\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Maintenant comparons \u00e0 la r\u00e9partition du nombre de buts marqu\u00e9s :<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-00b9279 elementor-widget elementor-widget-image\" data-id=\"00b9279\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"439\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_template_blog-127.png\" class=\"attachment-large size-large wp-image-62912\" alt=\"Number of goals\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_template_blog-127.png 1024w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_template_blog-127-300x165.png 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_template_blog-127-768x422.png 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a2fa83f elementor-widget elementor-widget-text-editor\" data-id=\"a2fa83f\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">On remarque que le nombre de tirs en dehors de la surface semble \u00eatre proportionnellement bien plus important que le nombre de buts.<\/span><\/p><p><span style=\"font-weight: 400;\">Maintenant rappelons nous que notre objectif est d\u2019\u00e9tablir une probabilit\u00e9 de but pour chaque tir. Pour cela, nous effectuons le rapport nombre de buts\/nombre de tirs nombre de buts nombre de tirs pour chaque zone quadrill\u00e9e de l\u2019espace. Ce rapport est notre probabilit\u00e9 de marquer. Ensuite nous affichons cette probabilit\u00e9 pour chaque zone de l\u2019espace et voil\u00e0 le r\u00e9sultat :<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2a548a1 elementor-widget elementor-widget-image\" data-id=\"2a548a1\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"439\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-142.png\" class=\"attachment-large size-large wp-image-63104\" alt=\"\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-142.png 1024w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-142-300x165.png 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-142-768x422.png 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-404521b elementor-widget elementor-widget-image\" data-id=\"404521b\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"439\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-128.png\" class=\"attachment-large size-large wp-image-62904\" alt=\"\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-128.png 1024w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-128-300x165.png 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-128-768x422.png 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-254c25a elementor-widget elementor-widget-text-editor\" data-id=\"254c25a\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Cette image est un premier mod\u00e8le d\u2019expected goals. Mais comme vous pouvez vous en rendre compte, il est loin d\u2019\u00eatre parfait et poss\u00e8de beaucoup de limites.<\/span><\/p><p><span style=\"font-weight: 400;\">La premi\u00e8re observation que nous pouvons faire est que le r\u00e9sultat obtenu semble pr\u00e9senter des anomalies.\u00a0<\/span><\/p><p><strong><span style=\"font-family: var( --e-global-typography-text-font-family ), Sans-serif; font-size: var( --e-global-typography-text-font-size );\">En effet, certaines zones de l\u2019espace tr\u00e8s \u00e9loign\u00e9es semblent avoir une probabilit\u00e9 de marquer tr\u00e8s importante.<\/span><\/strong><\/p><p><span style=\"font-weight: 400;\">Ceci est d\u00fb au fait que l\u2019exemple consid\u00e9r\u00e9 ne prend en compte les tirs sur <\/span><b>une seule saison<\/b><span style=\"font-weight: 400;\">, dans un seul championnat. Parfois, il n\u2019y a eu qu\u2019un tir dans une zone tr\u00e8s \u00e9loign\u00e9e, et ce tir a \u00e9t\u00e9 marqu\u00e9 et c\u2019est ce que nous appelons la magie du football. Cependant, si nous avions effectu\u00e9 nos calculs avec beaucoup plus de donn\u00e9es (plusieurs championnats sur plusieurs saisons), le r\u00e9sultat obtenu aurait pr\u00e9sent\u00e9 des anomalies moins fortes.<\/span><\/p><p><span style=\"font-weight: 400;\">A partir de cette visualisation g\u00e9n\u00e9r\u00e9e, nous allons maintenant essayer de <\/span><b>construire un mod\u00e8le math\u00e9matique <\/b><span style=\"font-weight: 400;\">qui colle le mieux \u00e0 la fr\u00e9quence de buts observ\u00e9e. Pour cela, nous allons \u00e9tudier deux param\u00e8tres s\u00e9par\u00e9ment : l\u2019angle de tir et la distance au but.<\/span><\/p><p><span style=\"font-weight: 400;\">L\u2019angle de tir repr\u00e9sente l\u2019angle entre les deux poteaux \u00e0 l\u2019endroit du tir.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<section class=\"elementor-section elementor-inner-section elementor-element elementor-element-ed4d2af elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"ed4d2af\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-inner-column elementor-element elementor-element-6770bbf\" data-id=\"6770bbf\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-c8b037c elementor-widget elementor-widget-image\" data-id=\"c8b037c\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"439\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_template_blog-129.png\" class=\"attachment-large size-large wp-image-62913\" alt=\"L\u2019angle de tir\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_template_blog-129.png 1024w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_template_blog-129-300x165.png 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_template_blog-129-768x422.png 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-inner-column elementor-element elementor-element-c12d119\" data-id=\"c12d119\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-41bc14e elementor-widget elementor-widget-image\" data-id=\"41bc14e\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"439\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-130.png\" class=\"attachment-large size-large wp-image-62905\" alt=\"L\u2019angle de tir\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-130.png 1024w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-130-300x165.png 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-130-768x422.png 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<div class=\"elementor-element elementor-element-46b8839 elementor-widget elementor-widget-image\" data-id=\"46b8839\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"439\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-131.png\" class=\"attachment-large size-large wp-image-62906\" alt=\"L\u2019angle de tir\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-131.png 1024w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-131-300x165.png 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-131-768x422.png 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1e704e1 elementor-widget elementor-widget-text-editor\" data-id=\"1e704e1\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Cette fois-ci, nous repr\u00e9sentons la <\/span><b>probabilit\u00e9 de marqu<\/b><span style=\"font-weight: 400;\"><strong>er<\/strong> obtenue pr\u00e9c\u00e9demment dans chaque zone de l\u2019espace, en fonction de l\u2019angle de tir de cette zone. On on obtient le nuage de point suivant :<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a0f1a83 elementor-widget elementor-widget-image\" data-id=\"a0f1a83\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"439\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-132.png\" class=\"attachment-large size-large wp-image-62907\" alt=\"Nuage de points\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-132.png 1024w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-132-300x165.png 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-132-768x422.png 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3c1af84 elementor-widget elementor-widget-text-editor\" data-id=\"3c1af84\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Ensuite, une <\/span><a href=\"https:\/\/datascientest.com\/regression-logistique-quest-ce-que-cest\">r\u00e9gression logistique<\/a> permet d&rsquo;approcher ces points par la formule : P(theta) = . Nous avons choisi une r\u00e9gression logistique et non une r\u00e9gression lin\u00e9aire, car elle permet d\u2019avoir une probabilit\u00e9 de marquer qui vaut 1 lorsque l\u2019angle s\u2019approche de 180\u00b0 et 0 lorsque l\u2019angle vaut 0\u00b0. (Pour un petit rappel sur la regression logistique,\u00a0<a href=\"https:\/\/datascientest.com\/regression-logistique-quest-ce-que-cest\" target=\"_blank\" rel=\"noopener\">relisez cet article<\/a>\u00a0)<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-dc12b8b elementor-widget elementor-widget-image\" data-id=\"dc12b8b\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"439\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-143.png\" class=\"attachment-large size-large wp-image-63105\" alt=\"\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-143.png 1024w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-143-300x165.png 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-143-768x422.png 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-62fa523 elementor-widget elementor-widget-text-editor\" data-id=\"62fa523\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Maintenant, nous pouvons faire exactement la m\u00eame chose avec la distance :<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-837ab9c elementor-widget elementor-widget-image\" data-id=\"837ab9c\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"439\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-134.png\" class=\"attachment-large size-large wp-image-62909\" alt=\"Nuage de points\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-134.png 1024w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-134-300x165.png 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-134-768x422.png 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f5ce595 elementor-widget elementor-widget-text-editor\" data-id=\"f5ce595\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Encore une fois nous faisons une <\/span><b>r\u00e9gression logistique<\/b><span style=\"font-weight: 400;\">, et nous obtenons une probabilit\u00e9 de marquer en fonction de la distance :\u00a0<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4befb6f elementor-widget elementor-widget-image\" data-id=\"4befb6f\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"439\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-144.png\" class=\"attachment-large size-large wp-image-63103\" alt=\"\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-144.png 1024w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-144-300x165.png 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-144-768x422.png 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-480b030 elementor-widget elementor-widget-text-editor\" data-id=\"480b030\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Le mod\u00e8le n\u2019est pas id\u00e9al car la probabilit\u00e9 de marquer \u00e0 0 m\u00e8tre devrait \u00eatre \u00e9gale \u00e0 1. Il m\u00e9riterait d\u2019\u00eatre am\u00e9lior\u00e9 (par exemple en ajoutant un <\/span><span style=\"font-weight: 400;\">d<\/span><span style=\"font-weight: 400;\">2<\/span><span style=\"font-weight: 400;\">dans l&rsquo;exponentielle) mais partons avec cette premi\u00e8re approximation.<\/span><\/p><p><span style=\"font-weight: 400;\">Ces 2 mod\u00e8les math\u00e9matiques, <\/span><b>l\u2019un bas\u00e9 sur l\u2019angle et l\u2019autre sur la distance<\/b><span style=\"font-weight: 400;\">, pr\u00e9disent notre probabilit\u00e9 de marquer exp\u00e9rimentale de mani\u00e8re plut\u00f4t correcte. N\u00e9anmoins ils ne le font pas de mani\u00e8re ultra pr\u00e9cise.<\/span><\/p><p><span style=\"font-family: var( --e-global-typography-text-font-family ), Sans-serif; font-size: var( --e-global-typography-text-font-size );\">Pour <\/span><b style=\"font-family: var( --e-global-typography-text-font-family ), Sans-serif; font-size: var( --e-global-typography-text-font-size );\">am\u00e9liorer l\u2019exactitude <\/b><span style=\"font-family: var( --e-global-typography-text-font-family ), Sans-serif; font-size: var( --e-global-typography-text-font-size );\">de notre mod\u00e8le math\u00e9matique, nous prenons cette fois ci en compte l\u2019impact de ces 2 dimensions simultan\u00e9ment.<\/span><\/p><p><span style=\"font-weight: 400;\">Nous faisons cela \u00e0 l\u2019aide d\u2019une r\u00e9gression \u00e0 plusieurs variables mais cela d\u00e9passe un peu le cadre th\u00e9orique de cet article. Le r\u00e9sultat qui \u00e9merge de cette r\u00e9gression \u00e0 deux variables est le suivant :<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-71da23e elementor-widget elementor-widget-image\" data-id=\"71da23e\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"439\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-136.png\" class=\"attachment-large size-large wp-image-62911\" alt=\"probalit\u00e9 de goals\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-136.png 1024w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-136-300x165.png 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_expected_goals_blog-136-768x422.png 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-12296cc elementor-widget elementor-widget-text-editor\" data-id=\"12296cc\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Le mod\u00e8le n\u2019est pas id\u00e9al car la probabilit\u00e9 de marquer \u00e0 0 m\u00e8tre devrait \u00eatre \u00e9gale \u00e0 1. Il m\u00e9riterait d\u2019\u00eatre am\u00e9lior\u00e9 (par exemple en ajoutant un <\/span><span style=\"font-weight: 400;\">d<\/span><span style=\"font-weight: 400;\">2<\/span><span style=\"font-weight: 400;\">dans l&rsquo;exponentielle) mais partons avec cette premi\u00e8re approximation.<\/span><\/p><p><span style=\"font-weight: 400;\">Ces 2 mod\u00e8les math\u00e9matiques, <\/span><b>l\u2019un bas\u00e9 sur l\u2019angle et l\u2019autre sur la distance<\/b><span style=\"font-weight: 400;\">, pr\u00e9disent notre probabilit\u00e9 de marquer exp\u00e9rimentale de mani\u00e8re plut\u00f4t correcte. N\u00e9anmoins ils ne le font pas de mani\u00e8re ultra pr\u00e9cise.<\/span><\/p><p><span style=\"font-family: var( --e-global-typography-text-font-family ), Sans-serif; font-size: var( --e-global-typography-text-font-size );\">Pour am\u00e9liorer l\u2019exactitude de notre mod\u00e8le math\u00e9matique, nous prenons cette fois ci en compte l\u2019impact de ces 2 dimensions simultan\u00e9ment.<\/span><\/p><p><span style=\"font-weight: 400;\">Nous faisons cela \u00e0 l\u2019aide d\u2019une r\u00e9gression \u00e0 plusieurs variables mais cela d\u00e9passe un peu le cadre th\u00e9orique de cet article. Le r\u00e9sultat qui \u00e9merge de cette r\u00e9gression \u00e0 deux variables est le suivant :<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f32d3a5 elementor-widget elementor-widget-text-editor\" data-id=\"f32d3a5\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Ce mod\u00e8le math\u00e9matique prend en compte \u00e0 la fois <\/span><b>l\u2019angle et la distance<\/b><span style=\"font-weight: 400;\"> au but du tir effectu\u00e9. Il est \u00e9labor\u00e9 de mani\u00e8re \u00e0 coller au mieux \u00e0 la r\u00e9alit\u00e9 des buts observ\u00e9s. Il est donc maintenant beaucoup plus g\u00e9n\u00e9ral, pr\u00e9sente moins d\u2019anomalies et semble mieux se rapprocher de la r\u00e9alit\u00e9. A partir de ce mod\u00e8le, il est ainsi possible d\u2019<\/span><b>attribuer une probabilit\u00e9 de marquer <\/b><span style=\"font-weight: 400;\">aux prochains tirs effectu\u00e9s suivant la zone du tir.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-8489e37 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"8489e37\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-b7eb4a9\" data-id=\"b7eb4a9\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-7f0a40a elementor-widget elementor-widget-heading\" data-id=\"7f0a40a\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Conclusion\n<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7bdcc64 elementor-widget elementor-widget-text-editor\" data-id=\"7bdcc64\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-size: 15px; font-weight: 400;\">Vous avez vu comment construire, \u00e0 partir de l\u2019angle et de la distance, un mod\u00e8le d\u2019expected goals. Ce mod\u00e8le permet de tirer des premiers enseignements pour les joueurs. Par exemple, on se rend compte qu\u2019il est difficile de marquer lorsque le tir est excentr\u00e9, et qu\u2019une passe en retrait sera peut-\u00eatre plus appropri\u00e9e.<\/span><\/p><p><span style=\"font-weight: 400;\">Par ailleurs, notre mod\u00e8le est loin d\u2019\u00eatre parfait. Son premier d\u00e9faut est qu\u2019il est \u00e9tabli sur la base des donn\u00e9es d\u2019<\/span><b>un seul championnat lors d\u2019une seule saison<\/b><span style=\"font-weight: 400;\">. Son deuxi\u00e8me d\u00e9faut est que nous avons pris en compte seulement l\u2019angle et la distance pour l\u2019\u00e9laborer. Des mod\u00e8les plus \u00e9labor\u00e9s prendrons en compte la zone de contact du tir (t\u00eate ou pied), la position des d\u00e9fenseurs au moment de la frappe, le type d&rsquo;action (attaque plac\u00e9e, contre attaque), le choix du pied (bon ou mauvais) et bien d\u2019autres param\u00e8tres encore.<\/span><\/p><p>S\u2019il y a bien <strong style=\"font-weight: 400;\">une chose \u00e0 retenir de cet article,<\/strong> c\u2019est que les <strong>expected goal<\/strong><b>s<\/b><span style=\"font-weight: 400;\"> sont <strong>construits<\/strong> pour <strong>coller<\/strong> au mieux \u00e0 la <strong>fr\u00e9quence<\/strong> de <strong>buts<\/strong> observ\u00e9s <strong>en fonction d\u2019une multitude de param\u00e8tres<\/strong>. Une probabilit\u00e9 de scorer reste une probabilit\u00e9. Elle se v\u00e9rifiera en moyenne sur le long terme si elle est construite correctement, mais sur un seul match tout reste possible et c\u2019est bien cela qui fait la magie de ce sport.\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Si vous \u00eates int\u00e9ress\u00e9 par l\u2019analyse de donn\u00e9es en rapport avec le football, nous vous recommandons d\u2019aller<a href=\"https:\/\/datascientest.com\/mpg-le-foot-dans-toute-sa-data\"> visiter le projet \u201c<span style=\"text-decoration: underline;\"><em>MPG, le foot dans toute sa data<\/em><\/span>\u201d<\/a> d\u00e9velopp\u00e9 au sein du\u00a0<\/span><a href=\"https:\/\/studio.multi.datascientest.com\/\" target=\"_blank\" rel=\"noopener\">studio de DataScientest<\/a><span style=\"font-weight: 400;\">.\u00a0<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b86017a elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"b86017a\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm elementor-animation-grow\" href=\"https:\/\/datascientest.com\/rdv\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">En savoir plus sur les formations<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Le nombre d\u2019expected goals est un nouvel indicateur de performances apparu tr\u00e8s r\u00e9cemment dans l\u2019analyse du football. Cette statistique est de plus en plus utilis\u00e9e pour interpr\u00e9ter la physionomie d\u2019une rencontre, mais savons nous vraiment comment l\u2019interpr\u00e9ter ? Cet article a pour but de vous pr\u00e9senter le plus simplement possible les r\u00e9alit\u00e9s math\u00e9matiques qui se [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":62912,"comment_status":"open","ping_status":"open","sticky":false,"template":"elementor_theme","format":"standard","meta":{"content-type":"","inline_featured_image":false},"categories":[2494],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v21.7 (Yoast SEO v21.7) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Expected goals : Comprendre les maths qui se cachent derri\u00e8re<\/title>\n<meta name=\"description\" content=\"D\u00e9couvrez tout ce qui se cache derri\u00e8re les Expected Goals : cette statistique de plus en plus importante dans le monde du football !\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/datascientest.com\/expected-goals-comprendre-les-maths-qui-se-cachent-derrieres\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Expected goals : Comprendre les maths qui se cachent derri\u00e8re\" \/>\n<meta property=\"og:url\" content=\"https:\/\/datascientest.com\/expected-goals-comprendre-les-maths-qui-se-cachent-derrieres\" \/>\n<meta property=\"og:site_name\" content=\"Formation Data Science | DataScientest.com\" \/>\n<meta property=\"article:published_time\" content=\"2021-04-20T16:06:50+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-11-09T13:35:08+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/04\/illu_template_blog-127.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1024\" \/>\n\t<meta property=\"og:image:height\" content=\"562\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"Margalith Mamou\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u00c9crit par\" \/>\n\t<meta name=\"twitter:data1\" content=\"Margalith Mamou\" \/>\n\t<meta name=\"twitter:label2\" content=\"Dur\u00e9e de lecture estim\u00e9e\" \/>\n\t<meta name=\"twitter:data2\" content=\"10 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/datascientest.com\/expected-goals-comprendre-les-maths-qui-se-cachent-derrieres\",\"url\":\"https:\/\/datascientest.com\/expected-goals-comprendre-les-maths-qui-se-cachent-derrieres\",\"name\":\"Expected goals : Comprendre les maths qui se cachent derri\u00e8re\",\"isPartOf\":{\"@id\":\"https:\/\/datascientest.com\/#website\"},\"datePublished\":\"2021-04-20T16:06:50+00:00\",\"dateModified\":\"2023-11-09T13:35:08+00:00\",\"author\":{\"@id\":\"https:\/\/datascientest.com\/#\/schema\/person\/1c2cce73f7edd34162d45b93c92adb00\"},\"description\":\"D\u00e9couvrez tout ce qui se cache derri\u00e8re les Expected Goals : cette statistique de plus en plus importante dans le monde du football !\",\"inLanguage\":\"fr-FR\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/datascientest.com\/expected-goals-comprendre-les-maths-qui-se-cachent-derrieres\"]}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/datascientest.com\/#website\",\"url\":\"https:\/\/datascientest.com\/\",\"name\":\"Formation Data Science | DataScientest.com\",\"description\":\"Leader de la formation en Data Science\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/datascientest.com\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"fr-FR\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/datascientest.com\/#\/schema\/person\/1c2cce73f7edd34162d45b93c92adb00\",\"name\":\"Margalith Mamou\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"fr-FR\",\"@id\":\"https:\/\/datascientest.com\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/datascientest.com\/wp-content\/uploads\/2023\/11\/Margalith.jpg\",\"contentUrl\":\"https:\/\/datascientest.com\/wp-content\/uploads\/2023\/11\/Margalith.jpg\",\"caption\":\"Margalith Mamou\"},\"description\":\"Margalith Mamou est Product Manager chez DataScientest, apr\u00e8s avoir occup\u00e9 le poste de Chef de projet Web pendant plus d'un an au sein de la m\u00eame entreprise. 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