Research Report: Comparative Goaltending Efficacy (2025-2026 Season)

Inclusion Criteria

Restricted to goaltenders with a minimum of 15 Games Played during the 2025-26 season.

Primary Findings: The Season’s Elite

The following table represents the top 20 goaltenders for the 2025-26 season, ranked by their average standing across all five pillars.

Rank	Player	Team	GP	Composite Score
1	Scott Wedgewood	COL	45	2.0
2	Mackenzie Blackwood	COL	39	9.9
3	Jake Oettinger	DAL	54	10.0
4	Jesper Wallstedt	MIN	35	10.4
5	Andrei Vasilevskiy	TBL	58	11.5
6	Joel Hofer	STL	46	11.5
7	Alex Lyon	BUF	36	11.6
8	Brandon Bussi	CAR	39	13.4
9	Ukko-Pekka Luukkonen	BUF	35	13.8
10	Filip Gustavsson	MIN	50	14.1
11	Logan Thompson	WSH	58	15.0
12	Linus Ullmark	OTT	49	17.6
13	Jeremy Swayman	BOS	55	18.1
14	Jakub Dobes	MTL	43	18.8
15	Casey DeSmith	DAL	30	20.1
16	Karel Vejmelka	UTA	64	20.6
17	Dan Vladar	PHI	52	20.6
18	Ilya Sorokin	NYI	55	21.1
19	Connor Ingram	EDM	32	21.2
20	John Gibson	DET	57	22.9

Detailed Logical Analysis

1. The Wedgewood Anomaly

Scott Wedgewood's Composite Score of 2.0 represents the largest #1-to-#2 separation in either the current season or the 2021-2026 historical baseline. Wedgewood ranks #1 in three of five pillars (Save Efficiency Ratio, Loss Suppression, Victory Efficiency), #2 in Win Rate, and #5 in Shutout Rate. His 7.9-point gap over second-ranked Mackenzie Blackwood (9.9 Composite) is nearly 80 times larger than the gap between #2 and #3, and exceeds the entire spread from #2 down to #11. By comparison, the historical baseline produced a #1-#2 gap of only 1.0 points (Ullmark to Shesterkin). Across 45 games for Colorado, Wedgewood's profile reflects the cross-pillar dominance the Composite methodology was designed to surface — not a peak in one statistical category, but near-peak performance in nearly all of them simultaneously.

2. The Dual-Goaltender Phenomenon

The 2025-26 season produces a structural pattern with no parallel in any single-year cut of the historical baseline: three franchises place both of their primary goaltenders inside the top 10. Colorado holds the #1 and #2 positions outright (Wedgewood and Mackenzie Blackwood). Buffalo places Alex Lyon at #7 and Ukko-Pekka Luukkonen at #9. Minnesota places Jesper Wallstedt at #4 and Filip Gustavsson at #10. The historical baseline produced isolated examples of teammates inside the top 10 (Carolina's Kochetkov at #4 and Andersen at #5), but never three teams concurrently. The simultaneous emergence of three dual-elite goaltending tandems suggests that defensive system quality — rather than goaltender talent in isolation — is producing concurrent high Composite scores at those organizations.

3. The Workload Pattern

Of the seven goaltenders with 55 or more games played this season (Vejmelka, Vasilevskiy, Thompson, Gibson, Greaves, Sorokin, Swayman), only Andrei Vasilevskiy (#5) finishes in the top 10. The remaining six high-volume goaltenders cluster between #11 and #22, with Loss Suppression and GA/Win pillars consistently dragging their composites: Sorokin, for example, ranks elite in Shutout Rate (#2) but #50 in Loss Suppression, collapsing his composite to #18. This pattern echoes the historical finding that high game load correlates with Composite degradation. In 2025-26 the effect is observable in real time, and Vasilevskiy stands as the lone goaltender whose individual skill currently overcomes the workload tax.

Conclusions

The 2025-26 season produces both a generational outlier (Wedgewood's 2.0 Composite) and a statistically rare team-level pattern (three franchises with dual top-10 goalies). The veteran tier — Vasilevskiy, Ullmark, Swayman, Sorokin — remains statistically present but compressed: outside Vasilevskiy, no veteran sustains the cross-pillar profile required for a top-10 finish. The data validates the Composite methodology in real time. It is sensitive enough to surface a true outlier when one occurs, resilient enough to keep familiar veteran names in their expected tier, and granular enough to expose structural team-level patterns that traditional metrics conceal.

Thesis: Single-Season Validation of the Multi-Pillar Model

The Outlier Floor

The most significant single-season finding is the distance between #1 and #2. A Composite of 2.0 implies a goaltender ranked at or near the absolute top of the league in five independent statistical categories simultaneously. The 7.9-point gap between Wedgewood and Blackwood is the largest #1/#2 separation on record across our datasets and serves as a real-time validation of the Composite methodology. The model does not average a true outlier into a peer group — it isolates him.

The System Cluster

The simultaneous emergence of Colorado, Buffalo, and Minnesota as dual-elite goaltending teams is the second major structural finding. Three teams in a single season placing both primary goaltenders in the top 10 indicates a measurable effect of defensive system efficiency at the franchise level. Where the historical baseline produced isolated dual entries, the current season produces a cluster — three teams, six goaltenders, all in the top 10. This is the team-system signal made visible at scale.

The Workload Tax in Real Time

The mid-season data confirms the historical thesis on workload. Of the seven goaltenders carrying 55+ games played, only Vasilevskiy maintains a top-10 position. The remaining six see their Loss Suppression or GA/Win pillars erode their composite into the 15-22 range despite competent Save Efficiency Ratios. This is the "shot frequency tax" identified in the historical thesis, now observable inside a single active season rather than across a five-year arc.

Final Conclusion

The 2025-26 season demonstrates that the Composite Efficacy Score functions as designed at the single-season scale: it surfaces a true outlier (Wedgewood), preserves expected tier placements for veteran elites (Vasilevskiy), and reveals system-level patterns invisible to traditional metrics (the dual-goaltender clusters at Colorado, Buffalo, and Minnesota). Read alongside the 2021-2026 historical baseline, the season produces a complete current-state snapshot of NHL goaltending efficacy — the second of two parallel reports built on a single methodology.

The complete table

66 qualifying goaltenders · every pillar value and rank

#	Player	Team	GP	GS	W	L	OT	SA	Svs	GA	Sv%	GAA	SO	Win Rate	Rk	SO Rate	Rk	Svs/GA	Rk	Loss Rate	Rk	GA/Win	Rk	Composite
1	Scott Wedgewood	COL	45	43	31	6	6	1093	1007	86	0.921	2.02	4	0.689	2	0.093	5	11.71	1	0.140	1	2.77	1	2.0
2	Mackenzie Blackwood	COL	39	36	23	10	2	933	843	90	0.904	2.51	3	0.590	8	0.083	7.5	9.37	19	0.278	10	3.91	5	9.9
3	Jake Oettinger	DAL	54	54	35	12	6	1372	1234	138	0.899	2.59	4	0.648	5	0.074	11	8.94	25	0.222	3	3.94	6	10.0
4	Jesper Wallstedt	MIN	35	33	18	9	6	1020	934	87	0.916	2.61	4	0.514	21	0.121	3	10.74	2	0.273	8	4.83	18	10.4
5	Andrei Vasilevskiy	TBL	58	58	39	15	4	1483	1353	132	0.912	2.31	2	0.672	4	0.034	38.5	10.25	6	0.259	6	3.38	3	11.5
6	Joel Hofer	STL	46	43	24	13	5	1250	1137	114	0.91	2.61	6	0.522	19	0.140	1	9.97	8	0.302	14	4.75	15.5	11.5
7	Alex Lyon	BUF	36	34	20	10	4	979	888	92	0.907	2.77	3	0.556	13	0.088	6	9.65	15	0.294	13	4.60	11	11.6
8	Brandon Bussi	CAR	39	39	31	6	2	912	816	97	0.895	2.47	2	0.795	1	0.051	25	8.41	37	0.154	2	3.13	2	13.4
9	Ukko-Pekka Luukkonen	BUF	35	34	22	9	3	930	846	85	0.91	2.52	1	0.629	6	0.029	41	9.95	11	0.265	7	3.86	4	13.8
10	Filip Gustavsson	MIN	50	49	28	15	6	1377	1245	133	0.904	2.69	4	0.560	11	0.082	9	9.36	20	0.306	15	4.75	15.5	14.1
11	Logan Thompson	WSH	58	58	31	21	6	1587	1447	140	0.912	2.44	4	0.534	16	0.069	16	10.34	4	0.362	29	4.52	10	15.0
12	Linus Ullmark	OTT	49	49	28	12	8	1198	1067	131	0.891	2.73	3	0.571	9	0.061	19	8.15	43	0.245	5	4.68	12	17.6
13	Jeremy Swayman	BOS	55	54	31	18	4	1571	1426	146	0.908	2.71	2	0.564	10	0.037	33.5	9.77	13	0.333	21	4.71	13	18.1
14	Jakub Dobes	MTL	43	42	29	10	4	1187	1070	117	0.901	2.78	0	0.674	3	0.000	56	9.15	24	0.238	4	4.03	7	18.8
15	Casey DeSmith	DAL	30	28	15	8	6	760	689	71	0.907	2.43	1	0.500	24	0.036	36.5	9.70	14	0.286	12	4.73	14	20.1
16	Karel Vejmelka	UTA	64	63	38	20	3	1626	1458	169	0.897	2.75	2	0.594	7	0.032	40	8.63	29	0.317	18	4.45	9	20.6
17	Dan Vladar	PHI	52	51	29	14	7	1283	1162	121	0.906	2.42	0	0.558	12	0.000	56	9.60	18	0.275	9	4.17	8	20.6
18	Ilya Sorokin	NYI	55	54	29	24	2	1530	1386	144	0.906	2.68	7	0.527	17	0.130	2	9.62	17	0.444	50	4.97	19.5	21.1
19	Connor Ingram	EDM	32	30	16	10	3	763	686	77	0.899	2.6	2	0.500	24	0.067	18	8.91	26	0.333	21	4.81	17	21.2
20	John Gibson	DET	57	57	29	22	4	1461	1317	144	0.901	2.72	4	0.509	22	0.070	14	9.15	23	0.386	36	4.97	19.5	22.9
21	Anton Forsberg	LAK	36	31	16	12	5	952	866	87	0.91	2.57	3	0.444	40	0.097	4	9.95	10	0.387	37	5.44	24	23.0
22	Tristan Jarry	PIT,EDM	33	29	18	9	3	832	734	98	0.882	3.32	2	0.545	14	0.069	16	7.49	55	0.310	16	5.44	25	25.2
23	Jet Greaves	CBJ	55	53	26	19	9	1539	1397	142	0.908	2.6	2	0.473	30	0.038	32	9.84	12	0.358	27	5.46	26	25.4
24	Igor Shesterkin	NYR	51	51	25	19	6	1425	1299	126	0.912	2.5	1	0.490	26	0.020	45	10.31	5	0.373	31	5.04	21	25.6
25	David Rittich	NYI	30	28	14	10	3	720	644	76	0.894	2.76	2	0.467	32.5	0.071	12.5	8.47	35	0.357	26	5.43	23	25.8
26	Akira Schmid	VGK	34	29	16	10	6	791	706	85	0.893	2.59	2	0.471	31	0.069	16	8.31	40	0.345	24	5.31	22	26.6
27	Arturs Silovs	PIT	39	38	19	12	8	1020	906	115	0.888	3.07	2	0.487	27	0.053	23	7.88	47	0.316	17	6.05	32	29.2
28	Joonas Korpisalo	BOS	31	28	14	9	6	851	761	90	0.894	3.15	1	0.452	37	0.036	36.5	8.46	36	0.321	19	6.43	37	33.1
29	Stuart Skinner	EDM,PIT	50	50	23	17	9	1267	1125	142	0.888	2.92	2	0.460	34	0.040	31	7.92	46	0.340	23	6.17	35	33.8
30	Sergei Bobrovsky	FLA	52	51	27	23	1	1250	1096	154	0.877	3.07	4	0.519	20	0.078	10	7.12	59	0.451	51	5.70	29	33.8
31	Darcy Kuemper	LAK	50	50	19	14	15	1234	1100	134	0.891	2.78	3	0.380	54	0.060	20	8.21	41	0.280	11	7.05	47	34.6
32	Lukas Dostal	ANA	56	55	30	20	4	1513	1344	169	0.888	3.1	0	0.536	15	0.000	56	7.95	45	0.364	30	5.63	27	34.6
33	Jake Allen	NJD	37	36	17	17	2	1031	932	100	0.904	2.74	1	0.459	35	0.028	42	9.32	21	0.472	54	5.88	30	36.4
34	Philipp Grubauer	SEA	32	28	13	12	4	866	787	79	0.909	2.65	0	0.406	45	0.000	56	9.96	9	0.429	46	6.08	34	38.0
35	Jacob Markstrom	NJD	44	43	23	19	1	1113	983	130	0.883	3.07	1	0.523	18	0.023	44	7.56	52	0.442	49	5.65	28	38.2
36	Joey Daccord	SEA	47	46	20	20	6	1307	1173	136	0.897	3.03	2	0.426	43	0.043	28.5	8.62	30	0.435	47.5	6.80	43	38.4
37	Juuse Saros	NSH	59	59	28	22	8	1700	1519	181	0.894	3.16	0	0.475	29	0.000	56	8.39	38	0.373	32	6.46	38	38.6
38	Dennis Hildeby	TOR	20	14	5	7	4	548	501	48	0.914	2.86	1	0.250	63	0.071	12.5	10.44	3	0.500	56.5	9.60	60	39.0
39	Justus Annunen	NSH	28	23	10	12	2	711	645	67	0.907	2.68	1	0.357	56	0.043	28.5	9.63	16	0.522	59	6.70	40	39.9
40	Alex Nedeljkovic	SJS	40	34	18	14	4	1049	940	109	0.896	2.87	0	0.450	38	0.000	56	8.62	31	0.412	42	6.06	33	40.0
41	Elvis Merzlikins	CBJ	30	29	14	11	3	812	717	95	0.883	3.4	1	0.467	32.5	0.034	38.5	7.55	54	0.379	33.5	6.79	42	40.1
42	Thatcher Demko	VAN	20	20	8	10	1	514	461	54	0.897	2.9	1	0.400	49	0.050	26.5	8.54	33	0.500	56.5	6.75	41	41.2
43	Joseph Woll	TOR	39	38	15	16	7	1220	1097	124	0.899	3.34	2	0.385	52.5	0.053	23	8.85	28	0.421	43.5	8.27	59	41.2
44	Ville Husso	ANA	20	19	10	8	2	534	472	62	0.884	3.25	0	0.500	24	0.000	56	7.61	48	0.421	43.5	6.20	36	41.5
45	Devin Cooley	CGY	31	26	10	10	6	847	770	77	0.909	2.69	0	0.323	59	0.000	56	10.00	7	0.385	35	7.70	53	42.0
46	Spencer Knight	CHI	55	55	19	25	11	1583	1428	155	0.902	2.82	3	0.345	58	0.055	21	9.21	22	0.455	52	8.16	58	42.2
47	Eric Comrie	WPG	25	24	12	11	1	654	582	72	0.89	3.13	0	0.480	28	0.000	56	8.08	44	0.458	53	6.00	31	42.4
48	Dustin Wolf	CGY	57	55	23	29	3	1558	1401	158	0.899	3.01	2	0.404	46.5	0.036	35	8.87	27	0.527	61	6.87	44	42.7
49	Connor Hellebuyck	WPG	57	57	23	23	11	1547	1385	162	0.895	2.86	0	0.404	46.5	0.000	56	8.55	32	0.404	41	7.04	46	44.3
50	Charlie Lindgren	WSH	21	20	9	8	3	602	529	73	0.879	3.52	1	0.429	42	0.050	26.5	7.25	58	0.400	39	8.11	57	44.5
51	Adin Hill	VGK	27	27	10	9	6	587	511	76	0.871	3.04	1	0.370	55	0.037	33.5	6.72	64	0.333	21	7.60	51.5	45.0
52	Frederik Andersen	CAR	35	35	16	14	5	849	742	107	0.874	3.05	0	0.457	36	0.000	56	6.93	61	0.400	39	6.69	39	46.2
53	Anthony Stolarz	TOR	26	25	10	10	3	708	632	76	0.893	3.28	0	0.385	52.5	0.000	56	8.32	39	0.400	39	7.60	51.5	47.6
54	Jonas Johansson	TBL	25	23	11	10	2	670	592	78	0.884	3.29	0	0.440	41	0.000	56	7.59	49	0.435	47.5	7.09	48	48.3
55	Yaroslav Askarov	SJS	47	47	21	20	4	1341	1185	157	0.884	3.63	0	0.447	39	0.000	56	7.55	53	0.426	45	7.48	50	48.6
56	Samuel Ersson	PHI	33	29	14	11	5	744	647	97	0.87	3.12	0	0.424	44	0.000	56	6.67	65	0.379	33.5	6.93	45	48.7
57	Jonathan Quick	NYR	25	24	6	17	2	671	598	73	0.891	3.09	2	0.240	64	0.083	7.5	8.19	42	0.708	66	12.17	65	48.9
58	Daniil Tarasov	FLA	33	31	13	15	3	925	828	97	0.895	3.05	0	0.394	51	0.000	56	8.54	34	0.484	55	7.46	49	49.0
59	Cam Talbot	DET	34	25	12	9	6	797	704	93	0.883	3.19	0	0.353	57	0.000	56	7.57	51	0.360	28	7.75	54	49.2
60	Samuel Montembeault	MTL	25	23	10	8	4	635	554	81	0.872	3.43	0	0.400	49	0.000	56	6.84	63	0.348	25	8.10	56	49.8
61	Vitek Vanecek	UTA	22	19	5	13	3	506	447	59	0.883	2.93	1	0.227	66	0.053	23	7.58	50	0.684	65	11.80	64	53.6
62	Arvid Soderblom	CHI	26	24	8	13	3	774	681	93	0.88	3.8	1	0.308	61	0.042	30	7.32	57	0.542	62	11.62	63	54.6
63	Jordan Binnington	STL	41	39	13	20	7	1010	882	128	0.873	3.33	1	0.317	60	0.026	43	6.89	62	0.513	58	9.85	61	56.8
64	Leevi Meriläinen	OTT	20	19	8	10	1	457	393	64	0.86	3.51	0	0.400	49	0.000	56	6.14	66	0.526	60	8.00	55	57.2
65	Nikita Tolopilo	VAN	21	18	6	11	2	582	513	69	0.881	3.61	0	0.286	62	0.000	56	7.43	56	0.611	63	11.50	62	59.8
66	Kevin Lankinen	VAN	47	43	11	27	5	1285	1125	160	0.875	3.7	0	0.234	65	0.000	56	7.03	60	0.628	64	14.55	66	62.2

Pillars: Win Rate (W/GP) · Shutout Rate (SO/GS) · Save Efficiency Ratio (Svs/GA) · Loss Suppression (L/GS) · Victory Efficiency (GA/W). Composite = mean of the five pillar ranks; lower is better. Full definitions: methodology.