Australia at South Africa; 12.0-43.0

Club Level Predictions

The first set of predictions treats a club as the smallest object, as the club develops its members, organizes a gameplan, and deploys its players as needed for each match. This club model has a prediction of 0.819, which translates to predicting South Africa to win by 13.7.

Each club has a rating and a rating deviation (simiar to a Glicko system), and expected performances can be generated. This allows for simulated matches and spreads like the ones below.

Projected Performances

Projected Spreads

Projected Results

Player Level Predictions

Treating teams instead as an entity made up of the currently active players, I have ratings for each player in an altogether different system. These can be combined to form team ratings once teamsheets are announced, weighting starters a bit higher than the reserves. After the match is played, players can be weighted by their minutes on the field, allowing for an accurate measure of the team’s composition. With these compiled team ratings, we can make predictions, measure inaccuracy, and update the individual player ratings.

Prediction with Player Minutes: Australia by 5.6

Australia by 9.6 on a neutral field

There were 4 large changes in win probability in this match

Prediction without Player Minutes: Australia by 6.5

Australia by 10.5 on a neutral pitch

Away Minutes	Away Player	Away elo	Away Percentile	Number	Home Percentile	Home elo	Home Player	Home Minutes
65	James Slipper	145.17	100	1	89	100.3	Steven Kitshoff	63
65	Dave Porecki	105.56	91	2	95	112.34	Bongi Mbonambi	63
65	Allan Alaalatoa	125.72	99	3	99	128.46	Frans Malherbe	63
83	Nick Frost	70.33	34	4	nan	95.51	Jean Kleyn	69
52	Will Skelton	119.55	95	5	nan	94.25	Marvin Orie	54
32	Tom Hooper	77.16	49	6	nan	94.04	Marco van Staden	66
83	Michael Hooper	148.11	99	7	47	77.55	Pieter-Steph du Toit	83
83	Rob Valetini	108.75	92	8	94	112.36	Duane Vermeulen	83
59	Nic White	126.69	98	9	nan	95.81	Cobus Reinach	65
69	Quade Cooper	130.83	98	10	78	96.95	Manie Libbok	83
83	Marika Koroibete	77.23	48	11	nan	96.13	Kurt-Lee Arendse	83
52	Reece Hodge	103.55	86	12	97	125.43	Andre Esterhuizen	83
83	Len Ikitau	104.71	88	13	84	100.39	Lukhanyo Am	83
83	Suliasi Vunivalu	95.11	78	14	nan	96.47	Canan Moodie	83
83	Tom Wright	103.07	84	15	nan	95.23	Willie Le Roux	69
27	Jordan Uelese	79.25	55	16	nan	94.96	Joseph Dweba	20
18	Matt Gibbon	95.86	84	17	83	95.07	Thomas du Toit	20
18	Zane Nonggorr	92.23	73	18	17	61.68	Vincent Koch	20
31	Richie Arnold	93.59	77	19	89	104.9	RG Snyman	29
42	Pete Samu	89.92	72	20	nan	94.71	Evan Roos	14
24	Tate McDermott	98.42	82	21	nan	94.48	Deon Fourie	17
31	Samu Kerevi	111.67	93	22	88	105.97	Grant Williams	18
14	Carter Gordon	87.66	63	23	80	98.75	Damian Willemse	14