Edgehalla

Category Week Planner · 2026-27

Best saves schedules, fantasy week 1 (Sep 28-Oct 4)

Saves. The opponent factor is the opponent's own shots on goal per game. Teams are ranked by effective games: games this week, each weighted by how many shots the opponent takes. VAN leads with 4.21.

Data updated:

Teams ranked for saves

Early season: teams have played about 2 games, so the opponent factors are mostly 2025-26 numbers. This season's games count for about 20% and the share grows every week.

Teams by effective saves games, week 1
#TeamGPEffectivePer gameOpponents (factor)
1Vancouver Canucks44.211.05@ EDM (1.08)vs EDM (1.08)vs CGY (0.98)vs VGK (1.08)
2New York Rangers44.011.00@ BOS (0.98)vs TBL (1.00)@ DET (0.98)vs UTA (1.04)
3Philadelphia Flyers33.311.10vs PIT (1.07)@ NJD (1.15)vs CAR (1.09)
4Chicago Blackhawks33.121.04@ VGK (1.08)@ UTA (1.04)@ BUF (1.00)
5Florida Panthers33.101.03@ CAR (1.09)@ SJS (0.98)@ ANA (1.02)
6Seattle Kraken33.041.01@ CGY (0.98)@ EDM (1.08)vs CGY (0.98)
7Toronto Maple Leafs33.011.00vs MTL (0.95)vs NYI (1.03)vs OTT (1.03)
8Boston Bruins32.960.99vs NYR (0.91)@ WPG (1.00)@ MIN (1.05)
9Calgary Flames32.840.95vs SEA (0.95)@ VAN (0.93)@ SEA (0.95)
10Carolina Hurricanes32.840.95vs FLA (0.97)vs WSH (0.98)@ PHI (0.89)
11Edmonton Oilers32.820.94vs VAN (0.93)@ VAN (0.93)vs SEA (0.95)
12Vegas Golden Knights32.810.94vs CHI (0.85)vs ANA (1.02)@ VAN (0.93)
13Utah Mammoth32.740.91vs CHI (0.85)@ CBJ (0.97)@ NYR (0.91)
14New York Islanders22.131.07@ TOR (0.98)vs NJD (1.15)
15Los Angeles Kings22.131.06@ COL (1.15)@ SJS (0.98)
16St. Louis Blues22.111.05@ DAL (0.96)@ COL (1.15)
17Washington Capitals22.101.05@ CAR (1.09)@ TBL (1.00)
18Montreal Canadiens22.061.03@ TOR (0.98)@ PIT (1.07)
19Anaheim Ducks22.041.02@ VGK (1.08)vs FLA (0.97)
20Columbus Blue Jackets22.041.02vs BUF (1.00)vs UTA (1.04)
21San Jose Sharks22.021.01vs FLA (0.97)vs LAK (1.05)
22Nashville Predators22.011.00vs MIN (1.05)vs DAL (0.96)
23Colorado Avalanche22.001.00vs LAK (1.05)vs STL (0.94)
24Winnipeg Jets21.970.98vs BOS (0.98)@ DET (0.98)
25Minnesota Wild21.950.97@ NSH (0.97)vs BOS (0.98)
26New Jersey Devils21.920.96vs PHI (0.89)@ NYI (1.03)
27Detroit Red Wings21.910.96vs NYR (0.91)vs WPG (1.00)
28Dallas Stars21.910.95vs STL (0.94)@ NSH (0.97)
29Tampa Bay Lightning21.890.95@ NYR (0.91)vs WSH (0.98)
30Pittsburgh Penguins21.840.92@ PHI (0.89)vs MTL (0.95)
31Buffalo Sabres21.820.91@ CBJ (0.97)vs CHI (0.85)
32Ottawa Senators10.980.98@ TOR (0.98)

Projected saves leaders, week 1

Projected totals for the week, weighted by expected starts. Off-night games in green.

Players by projected saves, week 1
#PlayerGSSV
1Kevin LankinenVAN · G2.9379.8
2Igor ShesterkinNYR · G2.9476.8
3Jeremy SwaymanBOS · G2.6268.0
4Carter HartVGK · G2.9367.4
5Joseph WollPHI · G2.0260.5
6Ilya SorokinNYI · G2.0157.4
7Spencer KnightCHI · G2.0254.7
8Yaroslav AskarovSJS · G2.0154.5
9Juuse SarosNSH · G2.0153.4
10Jet GreavesCBJ · G2.0153.4
11Jakub DobesMTL · G2.0153.4
12Lukas DostalANA · G1.9252.4
13Sergei BobrovskyTOR · G2.0251.9
14Mackenzie BlackwoodCOL · G2.0151.2
15Jacob MarkstromFLA · G1.9349.7
16Devon LeviEDM · G2.0249.4
17Andrei VasilevskiyTBL · G2.0149.3
18Brandon BussiCAR · G2.0248.7
19Joey DaccordSEA · G1.9248.3
20Dustin WolfCGY · G1.9247.9
21Arturs SilovsPIT · G2.0146.7
22John GibsonDET · G1.9246.5
23Ukko-Pekka LuukkonenBUF · G2.0146.0
24Stuart SkinnerWPG · G1.9245.8
25Jesper WallstedtMIN · G1.7143.1
26Karel VejmelkaUTA · G1.9242.9
27Philipp GrubauerSEA · G1.1232.5
28Jordan BinningtonSTL · G1.0129.4
29Darcy KuemperLAK · G1.0129.4
30Logan ThompsonWSH · G1.0128.8
31Akira SchmidFLA · G1.1328.7
32Sebastian CossaUTA · G1.1228.6
33Nico DawsNJD · G1.0127.9
34Daniel VladarPHI · G1.0227.8
35Arvid SoderblomCHI · G1.0227.6
36Anthony StolarzTOR · G1.0227.2
37Devin CooleyCGY · G1.1226.1
38Charlie LindgrenWSH · G1.0125.9
39Linus UllmarkOTT · G1.025.1
40Joel HoferSTL · G1.0124.8

How it works

  1. Volume first. We count each team's games in the Monday-to-Sunday fantasy week and flag off-nights (fewer than 10 games) and back-to-backs. See games per week for the whole season.
  2. Opponents second, only where it helps. For each category we measure what every team allows per game (shots on goal against, hits and blocks its opponents record, faceoffs its opponents win, goals against). A factor of 1.10 means 10% more than the league average. We then tested out of sample whether these factors improve weekly forecasts over games times each team's own rate. They did, by a small margin, for shots on goal, hits, blocks, faceoffs won and goalie saves (where the factor is the opponent's own shots), so only those use them. Goals, assists, points, penalty minutes and goals against are volume only. The table below has the numbers.
  3. Each factor is shrunk toward average by how reliable that category is at the team level. We split last season's games into odd and even halves: when the halves agree (high split-half r), team differences are real and the factor is kept; when they do not, it is pulled toward 1. Early in the season this year's small sample is blended with last season, regressed by how well team factors carried over from one season to the next.
  4. Player rates come from rest-of-season projections: LineupExperts for goals, assists, points, PIM, shots, hits, blocks and goalie wins, saves and goals against, with our derived projection model filling power-play points, shorthanded points, plus/minus and faceoffs. Anything still missing (and shutouts) comes from our box scores, this season plus last season at half weight.
  5. Goalies: expected starts come from our goalie start model where it covers the week, otherwise from each goalie's share of projected starts, normalised so a team's goalies add up to one start per game. Wins get the Schedule Edge win-probability change for each game.
  6. The rater turns weekly totals into z-scores within the top 300 skaters and 64 goalies, then sums them with your weights. Punted categories count for nothing. SV% and GAA are scored by impact, so one start cannot top them.
For saves, last season's split-half r was 0.86 and the year-over-year r 0.62; factors are shrunk accordingly.

Frequently asked questions

Which teams have the best saves schedule in week 1?

VAN (4 games, 4.21 effective), NYR (4 games, 4.01 effective), PHI (3 games, 3.31 effective), CHI (3 games, 3.12 effective), FLA (3 games, 3.10 effective).

Which teams have the worst saves schedule?

OTT (1 games), BUF (2 games), PIT (2 games), TBL (2 games), DAL (2 games).

How reliable is the opponent effect for saves?

Last season the opponent measure (how many shots the opponent takes) had a split-half correlation of 0.86 across the 32 teams and a year-over-year correlation of 0.62. We shrink each team's factor by that reliability. Out of sample it trims weekly forecast error by only a couple of percent, so games played matter far more.

Should I stream for one category?

In head-to-head category leagues, streaming for a close category late in the week often wins it. Volume matters most: an extra game usually beats a better opponent. Use the full week planner to see every category at once and punt the ones you cannot win.