ICE Hockey League 2023/24 — results, standings and analytics

Some data is unavailable right now (goalies, teams). Panels that depend on it are hidden.

Scheduled games 0

No scheduled games left for this selection. The model accuracy below still covers the season's completed games.

Predicted vs actual 338

212 hit · 126 missed · 17 exact

Winner called right62.7%212 of 338 games

Exact scoreline175.0% of games

Mean goal error±1.93on the total goals in a game

Mean prediction56.2%home actually won 58.6%

Every finished game with the prediction it had beforehand, sortable by any column

19 Apr 2024, 19:30	KACvsRBS	66%	3.0 – 2.1	2:2	2:6	Miss	+3.0
16 Apr 2024, 19:30	RBSvsKAC	50%	2.5 – 2.5	2:2	1:4	Miss	+0.0
14 Apr 2024, 17:30	KACvsRBS	65%	3.0 – 2.1	2:2	2:3 OT	Miss	-0.1
12 Apr 2024, 19:30	RBSvsKAC	49%	2.4 – 2.4	2:2	6:5 OT	Miss	+6.2
09 Apr 2024, 19:30	KACvsRBS	65%	2.9 – 2.0	2:2	4:2	Hit	+1.1
07 Apr 2024, 17:30	RBSvsKAC	52%	2.4 – 2.3	2:2	2:5	Miss	+2.2
05 Apr 2024, 19:30	KACvsRBS	64%	2.9 – 2.1	2:2	0:1 OT	Miss	-3.9
02 Apr 2024, 19:30	RBSvsHCB	66%	2.9 – 2.0	2:1	3:2 OT	Hit	+0.2
30 Mar 2024, 18:00	HCBvsRBS	51%	2.4 – 2.4	2:2	1:4	Miss	+0.3
28 Mar 2024, 19:30	RBSvsHCB	65%	2.9 – 2.0	2:1	2:3	Miss	+0.2
26 Mar 2024, 19:45	HCBvsRBS	50%	2.4 – 2.4	2:2	3:2	Miss	+0.2
26 Mar 2024, 19:30	HCPvsKAC	35%	2.3 – 3.3	2:3	3:5	Hit	+2.4
24 Mar 2024, 18:30	RBSvsHCB	65%	2.8 – 1.9	2:1	4:3	Hit	+2.2
24 Mar 2024, 17:30	KACvsHCP	79%	3.9 – 2.0	3:1	3:1	Hit★	-1.9
22 Mar 2024, 19:45	HCBvsRBS	51%	2.4 – 2.3	2:2	1:3	Miss	-0.7
22 Mar 2024, 19:30	HCPvsKAC	36%	2.4 – 3.2	2:3	2:4	Hit	+0.4
19 Mar 2024, 19:30	KACvsHCP	76%	3.8 – 2.0	3:2	7:1	Hit	+2.2
19 Mar 2024, 19:15	RBSvsHCB	66%	2.9 – 2.0	2:1	0:2	Miss	-2.9
16 Mar 2024, 17:30	AVSvsHCP	65%	3.4 – 2.5	3:2	1:4	Miss	-0.9
13 Mar 2024, 19:45	HCPvsAVS	52%	3.0 – 2.9	2:2	4:2	Hit	+0.2
13 Mar 2024, 19:30	PIVvsKAC	37%	2.5 – 3.4	2:3	1:5	Hit	+0.1
11 Mar 2024, 19:45	HCBvsVSV	64%	3.3 – 2.4	3:2	2:1	Hit	-2.8
11 Mar 2024, 19:30	RBSvsBWL	67%	3.0 – 2.0	3:1	5:1	Hit	+1.0
11 Mar 2024, 19:15	AVSvsHCP	65%	3.4 – 2.5	3:2	5:3	Hit	+2.2
11 Mar 2024, 19:15	KACvsPIV	81%	4.2 – 2.0	4:2	1:6	Miss	+0.8
09 Mar 2024, 19:30	VSVvsHCB	50%	2.8 – 2.8	2:2	6:1	Hit	+1.4
09 Mar 2024, 19:30	PIVvsKAC	35%	2.5 – 3.5	2:3	1:3	Hit	-2.0
09 Mar 2024, 18:00	BWLvsRBS	49%	2.4 – 2.5	2:2	2:3	Hit	+0.1
08 Mar 2024, 19:45	HCPvsAVS	52%	3.0 – 2.8	2:2	2:1	Hit	-2.8
07 Mar 2024, 19:45	HCPvsAVS	52%	3.0 – 2.9	2:2	4:3 OT	Hit	+1.2
07 Mar 2024, 19:30	HCBvsVSV	64%	3.3 – 2.4	3:2	6:1	Hit	+1.3
07 Mar 2024, 19:15	RBSvsBWL	65%	2.9 – 2.1	2:2	5:1	Hit	+1.0
07 Mar 2024, 19:15	KACvsPIV	77%	4.0 – 2.1	4:2	7:0	Hit	+0.8
05 Mar 2024, 19:30	PIVvsKAC	38%	2.6 – 3.4	2:3	0:1	Hit	-5.1
05 Mar 2024, 19:15	BWLvsRBS	50%	2.4 – 2.5	2:2	3:2	Miss	+0.1
05 Mar 2024, 19:15	VSVvsHCB	53%	2.9 – 2.7	2:2	2:4	Miss	+0.4
04 Mar 2024, 19:15	AVSvsHCP	65%	3.4 – 2.5	3:2	3:2	Hit★	-0.9
03 Mar 2024, 18:00	HCBvsVSV	61%	3.1 – 2.4	3:2	5:2	Hit	+1.4
03 Mar 2024, 17:30	RBSvsBWL	63%	2.9 – 2.1	2:2	4:0	Hit	-1.0
03 Mar 2024, 17:30	AVSvsHCP	64%	3.4 – 2.5	3:2	3:2 OT	Hit★	-0.9
03 Mar 2024, 17:30	KACvsPIV	79%	4.2 – 2.2	4:2	0:2	Miss	-4.5
29 Feb 2024, 19:30	HCPvsOLL	62%	3.5 – 2.8	3:2	4:3 OT	Hit	+0.8
27 Feb 2024, 19:30	PIVvsHCI	59%	3.4 – 2.8	3:2	5:2	Hit	+0.8
27 Feb 2024, 19:15	OLLvsHCP	53%	3.2 – 3.0	3:2	6:2	Hit	+1.9
25 Feb 2024, 18:00	HCPvsOLL	62%	3.5 – 2.8	3:2	3:0	Hit	-3.3
25 Feb 2024, 17:30	HCIvsPIV	59%	3.3 – 2.7	3:2	3:6	Miss	+2.9
23 Feb 2024, 19:15	HCPvsRBS	44%	2.4 – 2.8	2:2	3:2	Miss	-0.2
23 Feb 2024, 19:15	HCBvsKAC	42%	2.4 – 2.9	2:2	3:0	Miss	-2.3
23 Feb 2024, 19:15	HCIvsASH	78%	4.2 – 2.2	4:2	5:0	Hit	-1.4
23 Feb 2024, 19:15	BWLvsOLL	68%	3.5 – 2.4	3:2	6:5	Hit	+5.1

Showing 50 of 338 rows. Sort or filter to narrow the list.

Each row's prediction was built from the games played before that date only — nothing after it. Sort by Goals Δ or Call to find where the model went wrong. A ★ marks a game whose exact scoreline it also got right.

Biggest upsets

RBSvsVIC
27 Oct 2023, 19:15 · predicted 90% home
1:2 OTaway won
PIVvsG99
17 Nov 2023, 19:30 · predicted 86% home
1:2 OTaway won
BWLvsG99
30 Dec 2023, 18:00 · predicted 85% home
1:4away won
BWLvsASH
12 Jan 2024, 19:15 · predicted 84% home
3:4 OTaway won
G99vsHCP
01 Nov 2023, 17:30 · predicted 16% home
3:2 OThome won

Games where the model was most confident in the side that lost.

Best calls

RBSvsASH
20 Oct 2023, 19:15 · predicted 95% home
4:2as predicted
G99vsRBS
29 Oct 2023, 17:30 · predicted 9% home
1:2as predicted
VSVvsASH
26 Sept 2023, 19:15 · predicted 90% home
2:1 SOas predicted
KACvsG99
27 Oct 2023, 19:15 · predicted 89% home
4:1as predicted
VSVvsG99
03 Nov 2023, 19:15 · predicted 89% home
3:2as predicted

Confident calls that came in. Note these are cheap to collect — a good model should have many of them, which is why the upsets matter more.

How well does this model do?

338 games scored

Winner called right62.7%home-only baseline 58.6%

Brier score0.227baseline 0.246 · lower is better

Log loss0.648baseline 0.685

Beats the baseline by0.019Brier points of skill

Total-goals error±1.93mean absolute error per game

Exact scoreline5.0%hit rate on the likeliest score

Accuracy as the season went onCumulative share of games called right, against picking the home side every time

Home-only baseline
Model

Table view

Games scored	Home-only baseline	Model
12	58.3%	66.7%
24	58.3%	66.7%
36	63.9%	58.3%
48	58.3%	58.3%
60	58.3%	63.3%
72	55.6%	61.1%
84	57.1%	60.7%
96	58.3%	60.4%
108	59.3%	60.2%
120	62.5%	60.8%
132	62.1%	59.8%
144	61.8%	59.0%
156	60.9%	58.3%
168	58.9%	57.7%
180	58.9%	57.8%
192	58.3%	57.8%
204	58.8%	58.3%
216	57.4%	57.9%
228	57.9%	58.3%
240	57.9%	59.2%
252	57.9%	59.9%
264	58.3%	60.6%
276	58.3%	61.6%
288	58.3%	62.8%
300	59.3%	63.0%
312	59.6%	63.8%
324	59.3%	63.9%
336	58.9%	63.1%
338	58.6%	62.7%

Both lines are cumulative, so they settle as the sample grows. The gap between them is the model's edge over the naive pick.

CalibrationWhen the model says 70%, does the home side win 70% of the time?

Predicted
Actual

Table view

Predicted home win %	Predicted	Actual	Games
10–20	18%	86%	7
20–30	25%	32%	22
30–40	35%	28%	40
40–50	46%	58%	50
50–60	55%	55%	67
60–70	65%	67%	70
70–80	75%	72%	54
80–90	85%	80%	25

The two lines tracking each other means the probabilities can be taken at face value. Where "actual" sits above "predicted", the model is under-confident in the home side; below, it is over-confident. Check the game count before reading much into a bucket — the extremes hold far fewer games than the middle. Buckets with fewer than five games are left out.

Every game is predicted using only the games played before it — a walk-forward test, so these are the numbers the model would really have produced. The baseline is "always back the home side", priced at the home-win rate known at the time. Team strengths start from the 2022/23 final table.

How the prediction works

Each team gets an attack and a defence multiplier from the goals it has scored and conceded, measured against the league average.
A fixture's expected goals are the league's home (or away) scoring rate times the attacking team's attack times the defending team's defence — so home advantage comes out of fitting home and away separately, not from a bonus added on top.
Both sides' goals are then treated as independent Poisson draws, which gives a probability for every scoreline rather than one guess, and from that the win, overtime and exact-score numbers.
Rates are shrunk toward the prior with six games of weight, so an early 7-1 win does not make a team look unbeatable. This is why fixtures are marked low confidence until both teams have played a few games.
Overtime and shootouts are treated as a coin flip. The feeds carry nothing that reliably predicts a shootout winner, and pretending otherwise would just be noise.

Goal models like this one capture scoring rates, not injuries, suspensions, travel, goalie rotation or roster changes. Treat the probabilities as a calibrated baseline, not a forecast — and read the accuracy panel above before trusting any single number.