Edgehalla

Category Week Planner · 2026-27

Best saves schedules, fantasy week 4 (Oct 19-25)

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. COL leads with 4.01.

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 4
#TeamGPEffectivePer gameOpponents (factor)
1Colorado Avalanche44.011.00@ PHI (0.89)@ NJD (1.15)vs TBL (1.00)@ NSH (0.97)
2Anaheim Ducks43.980.99@ NYR (0.91)@ NYI (1.03)@ NJD (1.15)@ PHI (0.89)
3San Jose Sharks43.950.99@ TOR (0.98)@ MTL (0.95)@ OTT (1.03)@ BOS (0.98)
4Minnesota Wild43.940.99@ EDM (1.08)@ CGY (0.98)@ SEA (0.95)@ VAN (0.93)
5Toronto Maple Leafs43.940.98vs SJS (0.98)@ CBJ (0.97)vs NYR (0.91)@ EDM (1.08)
6Tampa Bay Lightning33.261.09@ VGK (1.08)@ COL (1.15)@ UTA (1.04)
7New Jersey Devils33.231.08vs COL (1.15)vs ANA (1.02)vs LAK (1.05)
8Nashville Predators33.211.07@ BOS (0.98)@ PIT (1.07)vs COL (1.15)
9Philadelphia Flyers33.181.06vs COL (1.15)@ BUF (1.00)vs ANA (1.02)
10St. Louis Blues33.171.06vs WPG (1.00)vs VGK (1.08)vs CAR (1.09)
11Los Angeles Kings33.151.05@ WSH (0.98)@ NYI (1.03)@ NJD (1.15)
12Edmonton Oilers33.131.04vs MIN (1.05)vs CAR (1.09)vs TOR (0.98)
13Vancouver Canucks33.131.04vs CAR (1.09)vs DET (0.98)vs MIN (1.05)
14Seattle Kraken33.071.02vs DET (0.98)vs UTA (1.04)vs MIN (1.05)
15New York Islanders33.041.01vs ANA (1.02)vs LAK (1.05)@ DAL (0.96)
16New York Rangers33.041.01vs ANA (1.02)@ TOR (0.98)@ OTT (1.03)
17Utah Mammoth33.031.01vs PIT (1.07)@ SEA (0.95)vs TBL (1.00)
18Dallas Stars33.011.00vs BOS (0.98)vs WPG (1.00)vs NYI (1.03)
19Pittsburgh Penguins32.970.99@ UTA (1.04)vs FLA (0.97)vs NSH (0.97)
20Florida Panthers32.960.99@ OTT (1.03)@ PIT (1.07)@ CHI (0.85)
21Carolina Hurricanes32.950.98@ VAN (0.93)@ EDM (1.08)@ STL (0.94)
22Vegas Golden Knights32.920.97vs TBL (1.00)@ STL (0.94)@ CBJ (0.97)
23Boston Bruins32.900.97@ DAL (0.96)vs NSH (0.97)vs SJS (0.98)
24Detroit Red Wings32.870.96@ SEA (0.95)@ VAN (0.93)@ CGY (0.98)
25Ottawa Senators32.860.95vs FLA (0.97)vs SJS (0.98)vs NYR (0.91)
26Winnipeg Jets32.850.95@ STL (0.94)@ DAL (0.96)vs MTL (0.95)
27Montreal Canadiens32.830.94vs SJS (0.98)@ CHI (0.85)@ WPG (1.00)
28Columbus Blue Jackets22.061.03vs TOR (0.98)vs VGK (1.08)
29Washington Capitals22.061.03vs LAK (1.05)vs BUF (1.00)
30Calgary Flames22.031.02vs MIN (1.05)vs DET (0.98)
31Chicago Blackhawks21.920.96vs MTL (0.95)vs FLA (0.97)
32Buffalo Sabres21.870.93vs PHI (0.89)@ WSH (0.98)

Projected saves leaders, week 4

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

Players by projected saves, week 4
#PlayerGSSV
1Ilya SorokinNYI · G2.9179.1
2Lukas DostalANA · G2.8175.7
3Jeremy SwaymanBOS · G2.873.2
4Karel VejmelkaUTA · G2.8171.6
5Arturs SilovsPIT · G2.8170.4
6Juuse SarosNSH · G2.4167.4
7Andrei VasilevskiyTBL · G2.3166.1
8Yaroslav AskarovSJS · G2.4165.4
9Mackenzie BlackwoodCOL · G2.5362.5
10Kevin LankinenVAN · G2.2159.8
11Joey DaccordSEA · G2.359.5
12Igor ShesterkinNYR · G2.2159.0
13Jake OettingerDAL · G2.3158.5
14Sergei BobrovskyTOR · G2.2156.8
15Jake AllenNJD · G2.056.8
16John GibsonDET · G2.355.9
17Brandon BussiCAR · G2.355.8
18Darcy KuemperLAK · G2.155.5
19Jakub DobesMTL · G2.2255.0
20Joel HoferSTL · G1.848.0
21Jet GreavesCBJ · G1.847.3
22Logan ThompsonWSH · G1.747.2
23Stuart SkinnerWPG · G1.9145.5
24Joseph WollPHI · G1.6245.5
25Dustin WolfCGY · G1.744.9
26Jesper WallstedtMIN · G1.7144.8
27Carter HartVGK · G1.843.0
28Spencer KnightCHI · G1.7243.0
29Jacob MarkstromFLA · G1.7242.0
30Scott WedgewoodCOL · G1.5340.3
31Linus UllmarkOTT · G1.6139.9
32Daniel VladarPHI · G1.4238.7
33Tristan JarryEDM · G1.538.3
34Ukko-Pekka LuukkonenBUF · G1.5135.7
35Filip GustavssonMIN · G1.4135.3
36Jordan BinningtonSTL · G1.233.6
37Akira SchmidFLA · G1.3233.3
38Ville HussoANA · G1.2130.8
39Anthony StolarzTOR · G1.0127.3
40Anton ForsbergLAK · G0.924.7

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 4?

COL (4 games, 4.01 effective), ANA (4 games, 3.98 effective), SJS (4 games, 3.95 effective), MIN (4 games, 3.94 effective), TOR (4 games, 3.94 effective).

Which teams have the worst saves schedule?

BUF (2 games), CHI (2 games), CGY (2 games), WSH (2 games), CBJ (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.