🛡️ Big Block Games
Find players with elevated defensive engagement against specific opponents. These shot blockers finder matchups reveal who steps up their blocking game when facing certain teams.
⚠️ This tool shows historical block matchups based on 9 seasons of data. For real-time projections, check our Daily Projections →
🛡️ Upcoming Defensive Engagement Matchups
Rickard Rakell
Rickard Rakell
Noel Acciari
Noel Acciari
Noel Acciari
Oliver Ekman-Larsson
Jordan Martinook
Anthony Duclair
Max Domi
🏆 All-Time Block Matchups Leaderboard
Players with the highest defensive engagement vs specific opponents (9 seasons of data)
💡 These players consistently block more shots against these opponents - stream them for BLKs!
| # | Player | Team | vs Opponent | Games | BLK vs Opp | BLK Overall | Diff | % Increase | Score |
|---|---|---|---|---|---|---|---|---|---|
| 1 | Joshua Norris | BUF | SJS | 4 | 2.25 | 0.62 | +1.63 | +263% | 1.90 |
| 2 | Nick Paul | TBL | UTA | 3 | 1.33 | 0.52 | +0.81 | +156% | 1.13 |
| 3 | Joshua Norris | BUF | NSH | 5 | 1.40 | 0.62 | +0.78 | +126% | 0.91 |
| 4 | Alex Tuch | BUF | PHI | 17 | 1.53 | 0.79 | +0.74 | +94% | 0.75 |
| 5 | Rasmus Dahlin | BUF | NSH | 12 | 2.08 | 1.19 | +0.89 | +75% | 0.73 |
| 6 | Rasmus Dahlin | BUF | VGK | 12 | 2.08 | 1.19 | +0.89 | +75% | 0.73 |
| 7 | Ryan McLeod | BUF | PHI | 10 | 0.80 | 0.35 | +0.45 | +129% | 0.71 |
| 8 | Beck Malenstyn | BUF | VAN | 6 | 1.67 | 0.97 | +0.70 | +72% | 0.65 |
| 9 | Alex Tuch | BUF | WSH | 13 | 1.38 | 0.79 | +0.59 | +75% | 0.60 |
| 10 | Alex Tuch | BUF | VGK | 8 | 1.38 | 0.79 | +0.59 | +75% | 0.60 |
| 11 | Joshua Norris | BUF | PIT | 8 | 1.13 | 0.62 | +0.51 | +82% | 0.59 |
| 12 | Nick Paul | TBL | ANA | 12 | 0.92 | 0.52 | +0.40 | +77% | 0.56 |
| 13 | Jason Zucker | BUF | CHI | 23 | 0.78 | 0.40 | +0.38 | +95% | 0.55 |
| 14 | Nick Paul | TBL | OTT | 11 | 0.91 | 0.52 | +0.39 | +75% | 0.54 |
| 15 | Ryan McLeod | BUF | WSH | 9 | 0.67 | 0.35 | +0.32 | +91% | 0.51 |
| 16 | Jason Zucker | BUF | NYI | 24 | 0.75 | 0.40 | +0.35 | +87% | 0.51 |
How Defensive Engagement Analysis Works
Calculate Baselines
We compute each player's average blocked shots across all games to establish their normal blocking rate.
Analyze Opponent Splits
For each opponent, we calculate how their blocks compare to their baseline using z-scores.
Flag Elevated Matchups
Matchups with z-scores of 1.0+ are flagged as defensive engagement opportunities with upcoming schedule.
Frequently Asked Questions
What are Big Block Games?
Big Block Games are matchups where a player historically blocks significantly more shots than usual against a specific opponent. We use z-scores to identify players whose blocked shot totals spike against certain teams - perfect for streaming in banger leagues where BLKs count.
How is the Blocks Score calculated?
The Blocks Score uses z-scores to measure how much a player's blocked shots against a specific opponent exceed their career average. A score of 2.0+ means they block 2 standard deviations more shots than usual - that's elite defensive engagement.
Why do some players block more against certain teams?
Several factors drive elevated blocks: rivalry games with higher intensity, opponents with high shot volumes, matchup tendencies putting certain players on the ice against offensive stars, and defensive systems that emphasize shot blocking against specific teams.
What do the tier classifications mean?
Elite (🔥): Score 2.5+ — Massive spike in blocks vs this opponent. Strong (⚡): Score 1.5-2.5 — Significantly elevated blocking, very reliable. Mild (📈): Score 1.0-1.5 — Noticeable improvement, worth considering for streaming.
Are these only useful for defensemen?
While defensemen typically lead in blocked shots, some forwards also show elevated blocking tendencies against certain opponents. Our tool includes all positions - you might find valuable forward streamers for blocks too.
How do I use this for fantasy hockey streaming?
Check the upcoming games section to see which players have elevated block matchups coming up. Target these players for daily/weekly streaming when you need BLKs, especially in banger leagues where blocked shots are valuable.
What's the minimum sample size?
We require at least 3 games against an opponent to flag an elevated block matchup. This ensures the data reflects real tendencies rather than one-game flukes.
How is this different from regular block stats?
Regular stats show overall blocking rates. Our tool identifies opponent-specific spikes - players who block WAY more against certain teams. It's about finding the matchups where defensive engagement peaks.