{"id":142840,"date":"2015-10-18T13:58:33","date_gmt":"2015-10-18T11:58:33","guid":{"rendered":"http:\/\/mybroadband.co.za\/news\/?p=142840"},"modified":"2015-10-19T07:17:07","modified_gmt":"2015-10-19T05:17:07","slug":"computer-perfectly-predicts-springbok-win-over-wales","status":"publish","type":"post","link":"https:\/\/mybroadband.co.za\/news\/software\/142840-computer-perfectly-predicts-springbok-win-over-wales.html","title":{"rendered":"Computer perfectly predicts Springbok win over Wales"},"content":{"rendered":"

Principa’s data scientists have compiled statistics from over 6,000 rugby games played by 99 teams since 1995 to predict the results of the 2015 Rugby World Cup – a task which resulted in them perfectly guessing\u00a0the result of the Springboks vs Wales quarter final game.<\/p>\n

The project started with two teams within the company developing algorithms to predict the results of the tournament’s matches, which resulted in Team Nero being given the job of predicting the quarter final games.<\/p>\n

“Due to the many human variables in a match \u2013 such as injuries, penalties, referee calls, last-minute player decisions and even health – we may not be able to predict the exact scores, but with each match we will be able to provide an increasingly high probability of our predicted outcome,” said\u00a0Principa.<\/p>\n

Nero predicted the Boks to win by 4 points against Wales – which they did – and New Zealand to beat France in their quarter final by 28 points. New Zealand ended up winning by 49 points.<\/p>\n

The Ireland vs Argentina game sees the South Americans losing by 8, according to the prediction, and Australia beating Scotland by 24 points.<\/p>\n

\n
\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Match<\/strong><\/span><\/td>\nPrediction by Nero<\/strong><\/span><\/td>\nActual Result<\/strong><\/span><\/td>\n<\/tr>\n
1. England vs Fiji<\/strong><\/td>\nEngland by 24<\/td>\nEngland by 24<\/td>\n<\/tr>\n
2. Tonga vs Georgia<\/strong><\/td>\nTonga by 6<\/td>\nGeorgia by 7<\/td>\n<\/tr>\n
3. Ireland vs Canada<\/strong><\/td>\nIreland by 49<\/td>\nIreland by 43<\/td>\n<\/tr>\n
4. South Africa vs Japan<\/strong><\/td>\nSouth Africa by 33<\/td>\nJapan by 2<\/td>\n<\/tr>\n
5. France vs Italy<\/strong><\/td>\nFrance by 20<\/td>\nFrance by 22<\/td>\n<\/tr>\n
6. Samoa vs USA<\/strong><\/td>\nSamoa by 14<\/td>\nSamoa by 9<\/td>\n<\/tr>\n
7. Wales vs Uruguay<\/strong><\/td>\nWales by 55<\/td>\nWales by 45<\/td>\n<\/tr>\n
8. New Zealand vs Argentina<\/strong><\/td>\nNew Zealand by 27<\/td>\nNew Zealand by 10<\/td>\n<\/tr>\n
9. Scotland vs Japan<\/strong><\/td>\nScotland by 13<\/td>\nScotland by 35<\/td>\n<\/tr>\n
10. Australia vs Fiji<\/strong><\/td>\nAustralia by 24<\/td>\nAustralia by 15<\/td>\n<\/tr>\n
11. France vs Romania<\/strong><\/td>\nFrance by 29<\/td>\nFrance by 27<\/td>\n<\/tr>\n
12. New Zealand vs Namibia<\/strong><\/td>\nNew Zealand by 63<\/td>\n\u00a0New Zealand by 44<\/td>\n<\/tr>\n
13. Argentina vs Georgia<\/strong><\/td>\nArgentina by 15<\/td>\n\u00a0Argentina by 45<\/td>\n<\/tr>\n
14. Italy vs Canada<\/strong><\/td>\nCanada\u00a0by 15<\/td>\nItaly by 5<\/td>\n<\/tr>\n
15. South Africa vs Samoa<\/strong><\/td>\nSouth Africa by 25<\/td>\nSouth Africa by 40<\/td>\n<\/tr>\n
16. England vs Wales<\/strong><\/td>\nWales by 2<\/td>\nWales by 3<\/td>\n<\/tr>\n
17.\u00a0 Ireland vs Romania<\/strong><\/td>\nIreland by 40<\/td>\nIreland by 34<\/td>\n<\/tr>\n
18. Scotland vs USA<\/strong><\/td>\nScotland by 18<\/td>\nScotland by 23<\/td>\n<\/tr>\n
19. Australia vs Uruguay<\/strong><\/td>\nAustralia by 56<\/td>\nAustralia by 62<\/td>\n<\/tr>\n
20. Tonga vs Namibia<\/strong><\/td>\nTonga by 24<\/td>\nTonga by 14<\/td>\n<\/tr>\n
21. Wales vs Fiji<\/strong><\/td>\nWales by 23<\/td>\n\u00a0Wales by 10<\/td>\n<\/tr>\n
22. France vs Canada<\/strong><\/td>\nFrance by 36<\/td>\nFrance by 23<\/td>\n<\/tr>\n
23. New Zealand vs Georgia<\/strong><\/td>\nNew Zealand by 51<\/td>\nNew Zealand by 33<\/td>\n<\/tr>\n
24. Samoa vs Japan<\/strong><\/td>\nSamoa\u00a0by 3<\/td>\nJapan by 21<\/td>\n<\/tr>\n
25. South Africa vs Scotland<\/strong><\/td>\nSouth Africa by 11<\/td>\nSouth Africa by 18<\/td>\n<\/tr>\n
26. Australia vs England<\/strong><\/td>\nAustralia by 11<\/td>\nAustralia by 20<\/td>\n<\/tr>\n
27. Argentina vs Tonga<\/strong><\/td>\nArgentina by 18<\/td>\nArgentina by 29<\/td>\n<\/tr>\n
28. Ireland vs Italy<\/strong><\/td>\nIreland by 29<\/td>\nIreland by 7<\/td>\n<\/tr>\n
29. Canada vs Romania<\/strong><\/td>\nRomania by 4<\/td>\nRomania by 2<\/td>\n<\/tr>\n
30. Fiji vs Uruguay<\/strong><\/td>\nFiji by 35<\/td>\nFiji by 32<\/td>\n<\/tr>\n
31. South Africa vs USA<\/strong><\/td>\nSouth Africa by 37<\/td>\nSouth Africa by 64<\/td>\n<\/tr>\n
32. Georgia vs Namibia<\/strong><\/td>\nGeorgia by 17<\/td>\nGeorgia by 1<\/td>\n<\/tr>\n
33. New Zealand vs Tonga<\/strong><\/td>\nNew Zealand by 46<\/td>\nNew Zealand by 38<\/td>\n<\/tr>\n
\u00a034. Scotland vs Samoa<\/strong><\/td>\nScotland by 17<\/td>\nScotland by 3<\/td>\n<\/tr>\n
35. Australia vs Wales<\/strong><\/td>\nAustralia by 7<\/td>\nAustralia by 11<\/td>\n<\/tr>\n
36. England vs Uruguay<\/strong><\/td>\nEngland by 46<\/td>\nEngland by 57<\/td>\n<\/tr>\n
37. Argentina vs Namibia<\/strong><\/td>\nArgentina by 43<\/td>\nArgentina 45<\/td>\n<\/tr>\n
38. Italy vs Romania<\/strong><\/td>\nItaly by 14<\/td>\n\u00a0Italy by 10<\/td>\n<\/tr>\n
39. Ireland vs France<\/strong><\/td>\nIreland by 8<\/td>\nIreland by 15<\/td>\n<\/tr>\n
40. USA vs Japan<\/strong><\/td>\nJapan by 14<\/td>\nJapan by 9<\/td>\n<\/tr>\n
Q1 South Africa vs Wales<\/strong><\/td>\nSouth Africa by 4<\/td>\nSouth Africa by 4<\/td>\n<\/tr>\n
Q2 New Zealand vs France<\/strong><\/td>\nNew Zealand by 28<\/td>\nNew Zealand by 49<\/td>\n<\/tr>\n
Q3 Ireland vs Argentina<\/strong><\/td>\nIreland by 8<\/td>\nArgentina by 23<\/td>\n<\/tr>\n
Q4 Australia vs Scotland<\/strong><\/td>\nAustralia by 24<\/td>\nAustralia by 1<\/td>\n<\/tr>\n<\/tbody>\n<\/table><\/div>\n<\/div>\n

Nero’s predictions can be viewed here<\/a><\/strong>.<\/p>\n

More on\u00a0software<\/h3>\n

New Google Chrome browser released<\/a><\/strong><\/p>\n

OS X El Capitan launch<\/a><\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"

A team of data scientists has used 6,000 rugby games-worth of statistics to predict the outcomes of the 2015 Rugby World Cup matches.<\/p>\n","protected":false},"author":23,"featured_media":139006,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[16],"tags":[36,33432,32166,2938],"class_list":["post-142840","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-software","tag-active","tag-prediction-software","tag-rugby-world-cup-2015","tag-springboks"],"_links":{"self":[{"href":"https:\/\/mybroadband.co.za\/news\/wp-json\/wp\/v2\/posts\/142840"}],"collection":[{"href":"https:\/\/mybroadband.co.za\/news\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mybroadband.co.za\/news\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mybroadband.co.za\/news\/wp-json\/wp\/v2\/users\/23"}],"replies":[{"embeddable":true,"href":"https:\/\/mybroadband.co.za\/news\/wp-json\/wp\/v2\/comments?post=142840"}],"version-history":[{"count":1,"href":"https:\/\/mybroadband.co.za\/news\/wp-json\/wp\/v2\/posts\/142840\/revisions"}],"predecessor-version":[{"id":142842,"href":"https:\/\/mybroadband.co.za\/news\/wp-json\/wp\/v2\/posts\/142840\/revisions\/142842"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/mybroadband.co.za\/news\/wp-json\/wp\/v2\/media\/139006"}],"wp:attachment":[{"href":"https:\/\/mybroadband.co.za\/news\/wp-json\/wp\/v2\/media?parent=142840"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mybroadband.co.za\/news\/wp-json\/wp\/v2\/categories?post=142840"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mybroadband.co.za\/news\/wp-json\/wp\/v2\/tags?post=142840"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}