Edgehalla

Category Week Planner · 2026-27

Best blocks schedules, fantasy week 7 (Nov 9-15)

Blocked shots. The opponent factor is blocks its opponents record per game (the home scorer’s counting bias is now negligible). Teams are ranked by effective games: games this week, each weighted by how many blocks the opponent allows. NSH leads with 4.08.

Data updated:

Teams ranked for blocks

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 blocks games, week 7
#TeamGPEffectivePer gameOpponents (factor)
1Nashville Predators44.081.02@ LAK (1.07)@ ANA (1.05)@ VGK (1.01)@ SJS (0.95)
2Philadelphia Flyers44.071.02@ VAN (1.01)@ EDM (1.02)@ CBJ (1.01)vs EDM (1.02)
3San Jose Sharks43.930.98vs NYI (0.98)vs PIT (0.93)@ UTA (1.07)vs NSH (0.95)
4Florida Panthers43.900.97@ CBJ (1.01)vs DET (0.98)@ STL (1.00)@ DAL (0.91)
5Edmonton Oilers43.690.92vs NYR (1.02)vs PHI (0.88)@ TOR (0.91)@ PHI (0.88)
6Washington Capitals33.291.09@ OTT (0.95)@ NJD (1.16)vs NJD (1.16)
7Detroit Red Wings33.191.06@ STL (1.00)@ FLA (1.12)@ TBL (1.08)
8St. Louis Blues33.171.06vs DET (0.98)@ UTA (1.07)vs FLA (1.12)
9New York Rangers33.171.06@ EDM (1.02)@ CGY (1.13)@ VAN (1.01)
10Calgary Flames33.141.05vs NYR (1.02)@ LAK (1.07)@ ANA (1.05)
11Toronto Maple Leafs33.101.03vs COL (1.12)vs MIN (0.95)vs EDM (1.02)
12Columbus Blue Jackets33.081.03vs FLA (1.12)vs TBL (1.08)vs PHI (0.88)
13Montreal Canadiens33.081.03vs MIN (0.95)@ BOS (1.00)vs COL (1.12)
14Los Angeles Kings33.071.02vs NSH (0.95)vs NYI (0.98)vs CGY (1.13)
15Anaheim Ducks33.071.02vs NSH (0.95)vs NYI (0.98)vs CGY (1.13)
16New York Islanders33.071.02@ SJS (0.95)@ LAK (1.07)@ ANA (1.05)
17Vegas Golden Knights33.041.01vs UTA (1.07)vs NSH (0.95)vs VAN (1.01)
18Ottawa Senators33.041.01vs WSH (0.99)vs COL (1.12)@ PIT (0.93)
19Dallas Stars32.970.99vs WPG (0.93)vs BUF (0.92)vs FLA (1.12)
20Utah Mammoth32.960.99@ VGK (1.01)vs STL (1.00)vs SJS (0.95)
21Tampa Bay Lightning32.920.97@ BUF (0.92)@ CBJ (1.01)vs DET (0.98)
22Vancouver Canucks32.910.97vs PHI (0.88)vs NYR (1.02)@ VGK (1.01)
23Minnesota Wild32.910.97@ MTL (1.00)@ TOR (0.91)@ BOS (1.00)
24New Jersey Devils32.910.97@ WPG (0.93)vs WSH (0.99)@ WSH (0.99)
25Winnipeg Jets32.870.96vs NJD (1.16)@ DAL (0.91)@ CHI (0.80)
26Colorado Avalanche32.860.95@ TOR (0.91)@ OTT (0.95)@ MTL (1.00)
27Buffalo Sabres32.780.93vs TBL (1.08)@ CHI (0.80)@ DAL (0.91)
28Seattle Kraken22.441.22vs CAR (1.22)@ CAR (1.22)
29Boston Bruins21.950.97vs MTL (1.00)vs MIN (0.95)
30Pittsburgh Penguins21.910.95@ SJS (0.95)vs OTT (0.95)
31Chicago Blackhawks21.850.93vs BUF (0.92)vs WPG (0.93)
32Carolina Hurricanes21.730.86@ SEA (0.86)vs SEA (0.86)

Projected blocks leaders, week 7

Projected totals for the week. Off-night games in green.

Players by projected blocks, week 7
#PlayerGPBLK
1Nick SeelerPHI · D438.5
2Jacob TroubaSJS · D438.3
3Travis SanheimPHI · D437.7
4Cameron YorkPHI · D437.7
5Darnell NurseSJS · D437.6
6Connor MurphyEDM · D437.1
7Moritz SeiderDET · D317.0
8Ilya LyubushkinNSH · D446.9
9Brayden McNabbVGK · D336.9
10Colton ParaykoSTL · D316.8
11Martin FehervaryWSH · D316.8
12Alexander RomanovNYI · D316.6
13Noah DobsonMTL · D316.6
14Jake WalmanEDM · D436.5
15Zach WhitecloudCGY · D326.4
16Jake McCabeTOR · D316.4
17Radko GudasFLA · D426.3
18Roman JosiNSH · D446.3
19Chris TanevTOR · D316.2
20MacKenzie WeegarUTA · D316.2
21Esa LindellDAL · D316.2
22Alexandre CarrierMTL · D316.2
23Brandt ClarkeLAK · D316.1
24Simon EdvinssonDET · D316.1
25Ben ChiarotDET · D316.0
26Matt RoyWSH · D315.9
27Mike MathesonMTL · D315.9
28Kaiden GuhleMTL · D315.9
29Jonas BrodinMIN · D315.8
30Rasmus RistolainenPHI · D435.8
31Simon BenoitPHI · D435.7
32Jacob MiddletonCGY · D325.7
33Ryan PulockNYI · D315.7
34Jamie DrysdalePHI · D435.6
35Jake SandersonOTT · D315.6
36Rasmus SandinWSH · D315.5
37Rasmus AnderssonVGK · D335.5
38Marcus PetterssonNYR · D335.5
39Andrew PeekeUTA · D315.5
40Thomas HarleyDAL · D315.4

Matchup models plugged in

  • Banger Environment Index: hits and blocksHIT, BLKComing soon

Until a model is live, its categories use the team opponent factors above (or volume only where those did not validate).

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 blocks, last season's split-half r was 0.85 and the year-over-year r 0.73; factors are shrunk accordingly.

Frequently asked questions

Which teams have the best blocks schedule in week 7?

NSH (4 games, 4.08 effective), PHI (4 games, 4.07 effective), SJS (4 games, 3.93 effective), FLA (4 games, 3.90 effective), EDM (4 games, 3.69 effective).

Which teams have the worst blocks schedule?

CAR (2 games), CHI (2 games), PIT (2 games), BOS (2 games), SEA (2 games).

How reliable is the opponent effect for blocks?

Last season the opponent measure (how many blocks the opponent allows) had a split-half correlation of 0.85 across the 32 teams and a year-over-year correlation of 0.73. 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.