{"id":2002,"date":"2019-10-18T22:37:26","date_gmt":"2019-10-18T21:37:26","guid":{"rendered":"https:\/\/marriott-stats.com\/nigels-blog\/?p=2002"},"modified":"2019-11-04T08:20:19","modified_gmt":"2019-11-04T08:20:19","slug":"rugby-world-cup-who-will-win-in-2019-2","status":"publish","type":"post","link":"https:\/\/marriott-stats.com\/nigels-blog\/rugby-world-cup-who-will-win-in-2019-2\/","title":{"rendered":"Rugby World Cup #2 – Who will win in 2019? – Knockout Round"},"content":{"rendered":"

It’s the quarter finals tomorrow and it’s time for me to predict the outcomes using World Rugby’s rankings.\u00a0 Although I got 33 out of 37 matches right in the pool stages, the 4 errors are enough to change my prediction of who will win.<\/p>\n

As of today, World’s Rugby Rankings for the 20 teams<\/a> taking part in the 2019 World Cup are as listed in order here.\u00a0 Since Japan is the host nation, 3\"\"\u00a0points have been added to their ranking points which puts them level with France rather than Argentina.\u00a0 It should be noted that Namibia are in fact in 23rd place in the full rankings but 3 teams ahead of them (Spain, Romania & Portugal) failed to qualify.<\/p>\n

The biggest upsets in the pool stages came with Japan beating Ireland in Pool A and Uruguay beating Fiji in Pool D.\u00a0 As a result, both teams improved their ranking points considerably with Ireland & USA suffering the largest fall.\u00a0 It’s notable that some teams are unchanged, most notably England.\u00a0 This is because the 3 teams they played prior to the cancelled match against France were all at least 10 points lower in the rankings.\u00a0 When the ranking gap exceeds 10 points, nothing changes if the stronger team wins.\u00a0 Had England been able to play and beat France then they would have gained ranking points.<\/p>\n

In my first post on the 2019 World Cup, I explained the two models I am using to predict matches, HighRank & ExpWin<\/strong><\/span><\/a>.\u00a0 HighRank<\/strong><\/span> says that the winner will be the team with the highest ranking points whilst ExpWin<\/span><\/strong> predicts the margin of victory for the stronger team based on the ranking points gap.\u00a0 One realisation I had with the ExpWin model is that it could be used to measure how well each team did in the pool stages by comparing the actual margin of victory with the expected \"\"margin of victory.\u00a0 For example Wales were expected to win all 4 of their pool matches by respectively 23 (Georgia), 2 (Australia), 21 (Fiji) & 36 points (Uruguay).\u00a0 In the event they underperformed slightly and the actual margin of victories were 29, 4, 12, 22, an average underperformance per match of 4 points which is what is shown in the last column of the ranking tables here.<\/p>\n

Indeed the table to the right resorts the 20 nations in terms of the difference between actual and expected winning margins.\u00a0 Of course we need to remember that New Zealand, Italy, England, France, Canada & Namibia were only able to play 3 matches due to Typhoon Hagibis.\u00a0 But this does show that South Africa, New Zealand, England, Japan & Australia were outperforming expectations whilst Wales, Ireland & France underperformed.\u00a0 I will come back to these figures later on.<\/p>\n

 <\/p>\n

How well have my models performed?<\/strong><\/span><\/p>\n

The short answer is that they have performed mostly inline with expectations and therefore I do not propose to change my model for the knockout phase.\u00a0 A more in-depth evaluation can be found here.<\/p>\n

 <\/p>\n

The Knock Out Rounds<\/strong><\/span><\/h4>\n

A reminder that I use dynamic ranking points i.e. the ranking points are modified for the semi finals and finals on the assumption that my quarter final predictions are correct.\u00a0 For each match I have given the probability of winning for the higher ranked team, the expected margin of victory for the higher ranked team and a + column that I will explain later.<\/p>\n

\"\"<\/p>\n

It is worth comparing these with what I was predicting before.<\/p>\n

\"\"<\/p>\n

Previously I had Ireland sneaking past New Zealand in the final but Japan’s stunning victory over Ireland upset that big time.\u00a0 With Japan topping pool A, the knockouts look very different.<\/p>\n

Most notably, Japan & South Africa are neck and neck in the quarter final.\u00a0 My model makes Japan marginal favourite which is quite remarkable but let’s not forget Brighton 4 years ago.\u00a0 I think some people are forgetting that you need to add 3 points to Japan’s ranking due to them playing at home.<\/p>\n

The Semis are expected to be close games and lead to a Wales v New Zealand final where I have the All Blacks winning their 3rd successive title by 3 points.<\/p>\n

However, an alternative forecast that I could have used would have been to add and subtract the over\/underperformance I mentioned earlier in the ranking tables.\u00a0 Take the Japan V South Africa quarterfinal where I basically have the margin of victory at zero i.e. a draw.\u00a0 South Africa have overperformed by 11 points whilst Japan have overperformed by 5 points.\u00a0 The difference is 6 points which could be added to the expected margin of victory and predicts a South Africa win by 6 points instead.\u00a0 This is what the + column in the predictions above show i.e. you can add this column to the expected margin victory to get an alternative forecast.<\/p>\n

All will be revealed come Sunday afternoon and next week I will update my forecast for the semi-finals.<\/p>\n

 <\/p>\n

My articles on the 2019 Rugby World Cup<\/strong><\/span><\/h4>\n
    \n
  1. Who will win in 2019 – Initial predictions ahead of Pool stage<\/a><\/li>\n
  2. Who will win in 2019 – Revised predictions ahead of Knockout stage<\/a><\/li>\n
  3. Who will win in 2019 – Final prediction ahead of the Final<\/a><\/li>\n
  4. How accurate were my predictions – written before the Final<\/a><\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"

    It’s the quarter finals tomorrow and it’s time for me to predict the outcomes using World Rugby’s rankings.\u00a0 Although I got 33 out of 37 matches right in the pool stages, the 4 errors are enough to change my prediction of who will win.<\/p>\n","protected":false},"author":3,"featured_media":2016,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_genesis_hide_title":false,"_genesis_hide_breadcrumbs":false,"_genesis_hide_singular_image":false,"_genesis_hide_footer_widgets":false,"_genesis_custom_body_class":"","_genesis_custom_post_class":"","_genesis_layout":"","footnotes":""},"categories":[6,4],"tags":[14,12,134,15,133],"class_list":{"0":"post-2002","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-forecasting","8":"category-sport","9":"tag-forecasts","10":"tag-rugby","11":"tag-rwc2019","12":"tag-sport-analytics","13":"tag-world-cup","14":"entry","15":"override"},"_links":{"self":[{"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/posts\/2002","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/comments?post=2002"}],"version-history":[{"count":7,"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/posts\/2002\/revisions"}],"predecessor-version":[{"id":2048,"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/posts\/2002\/revisions\/2048"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/media\/2016"}],"wp:attachment":[{"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/media?parent=2002"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/categories?post=2002"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/marriott-stats.com\/nigels-blog\/wp-json\/wp\/v2\/tags?post=2002"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}