{"id":997,"date":"2014-04-14T03:01:03","date_gmt":"2014-04-14T07:01:03","guid":{"rendered":"http:\/\/www.cricmetric.com\/blog\/?p=997"},"modified":"2014-04-14T03:01:03","modified_gmt":"2014-04-14T07:01:03","slug":"ipl-2014-pre-tournament-rankings-of-teams","status":"publish","type":"post","link":"https:\/\/www.cricmetric.com\/blog\/2014\/04\/ipl-2014-pre-tournament-rankings-of-teams\/","title":{"rendered":"IPL 2014: Pre-tournament rankings of teams"},"content":{"rendered":"

In the just concluded World T20 Tournament<\/a>, we had posted pre-match predictions<\/a> for all the matches in the second round and knock-out stage of the tournament. In the end, we were able to get correct predictions for 15 out of total 23 matches for which we generated the predictions, resulting in a success rate of 65%. Given the highly uncertain nature of the T20 format, we feel this is a good start. We are now ready to generate pre-match predictions for the upcoming season<\/a> of Indian Premier League<\/a> as well.<\/p>\n

Before that, we have generated a ranking of all the teams playing in this tournament. The methodology used for ranking the teams is be similar to what we use for predicting the outcome T20 matches<\/a>. For each player in the tournament, we will generate the Eigenfactor score (EFscore)<\/a>, in this case using the data of\u00a0IPL 2013<\/a> and Champions League Twenty20 2013<\/a>. A team’s score is the sum total of the scores of its individual players, no more and no less. The advantage of this method is that even tough the rosters of the teams have changed drastically since the latest auction of the IPL players<\/a>, we can still compute the total score of a team based on the scores of the players. There are quite a few players in the tournament for which the EFscore cannot be computed, since they did not play in either IPL 2013 or Champions League T20 2013. However, for each team we have scores of at least 11 players, and so we base our rankings on the top 11 players of each team.<\/p>\n

Note that the top 11 players of each team may not necessarily be the final 11 that eventually play in the tournament. Some of the teams have more than 4 overseas players in top 11, while a team can field at most 4 overseas players in any match. Furthermore, some of the players may be unavailable during the tournament, either because of their international commitments, or because they are injured. This information will be taken into account when generating the pre-match predictions, but for generating the pre-tournament rankings of teams we simply stick to the score of top 11 players of each team.<\/p>\n

A detailed preview of each team will be posted in the coming days before the tournament starts. For now, here is the table with the ranks of each of the teams in this tournament.<\/p>\n\n\n\n\n\t\n\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t
Rank<\/th>Team<\/th>Total score<\/th>\n<\/tr>\n<\/thead>\n
1<\/td>Sunrisers Hyderabad<\/a><\/td>1.106<\/td>\n<\/tr>\n
2<\/td>Chennai Super Kings<\/a><\/td>1.080<\/td>\n<\/tr>\n
3<\/td>Rajasthan Royals<\/a><\/td>1.063<\/td>\n<\/tr>\n
4<\/td>Mumbai Indians<\/a><\/td>1.055<\/td>\n<\/tr>\n
5<\/td>Kolkata Knight Riders<\/a><\/td>0.955<\/td>\n<\/tr>\n
6<\/td>Royal Challengers Bangalore<\/a><\/td>0.820<\/td>\n<\/tr>\n
7<\/td>Kings XI Punjab<\/a><\/td>0.789<\/td>\n<\/tr>\n
8<\/td>Delhi Daredevils<\/a><\/td>0.561<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

In the just concluded World T20 Tournament, we had posted pre-match predictions for all the matches in the second round and knock-out stage of the tournament. In the end, we were able to get correct predictions for 15 out of total 23 matches for which we generated the predictions, resulting in a success rate of… Read More »IPL 2014: Pre-tournament rankings of teams<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"neve_meta_sidebar":"","neve_meta_container":"","neve_meta_enable_content_width":"","neve_meta_content_width":0,"neve_meta_title_alignment":"","neve_meta_author_avatar":"","neve_post_elements_order":"","neve_meta_disable_header":"","neve_meta_disable_footer":"","neve_meta_disable_title":"","footnotes":""},"categories":[1],"tags":[],"class_list":["post-997","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/www.cricmetric.com\/blog\/wp-json\/wp\/v2\/posts\/997","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.cricmetric.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.cricmetric.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.cricmetric.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.cricmetric.com\/blog\/wp-json\/wp\/v2\/comments?post=997"}],"version-history":[{"count":2,"href":"https:\/\/www.cricmetric.com\/blog\/wp-json\/wp\/v2\/posts\/997\/revisions"}],"predecessor-version":[{"id":1001,"href":"https:\/\/www.cricmetric.com\/blog\/wp-json\/wp\/v2\/posts\/997\/revisions\/1001"}],"wp:attachment":[{"href":"https:\/\/www.cricmetric.com\/blog\/wp-json\/wp\/v2\/media?parent=997"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.cricmetric.com\/blog\/wp-json\/wp\/v2\/categories?post=997"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.cricmetric.com\/blog\/wp-json\/wp\/v2\/tags?post=997"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}