Online Table Games

Hardest Grid Categories (And How to Solve Them)

Some grid categories make you feel like a genius when you solve them and completely stumped when you don't. The hardest cells combine obscure elements, narrow criteria, or multiple constraints that dramatically shrink the pool of possible answers. Understanding what makes these categories difficult and developing specific strategies for each type turns impossible cells into solvable challenges. Here's how to tackle the toughest grid categories.

January 24, 2026

Obscure Team × Team Combos

When two teams with limited player overlap intersect, you're hunting for journeymen, deadline rentals, or brief stints that most fans never noticed. Examples include Arizona Coyotes × New Jersey Devils or Florida Panthers × Minnesota Wild, where few players have moved between both franchises.

Why These Are Hard

Obscure team pairings create difficulty through rarity:

Few players in history have played for both
No obvious stars connect these specific franchises
Correct answers are often depth players or backup goalies
Your brain doesn't naturally associate these teams together

The smaller the overlap in actual player movement history, the harder the cell becomes. Some team pairings might only have 5-10 valid answers in entire league history.

Solution Strategy

Think about player archetypes that move frequently:

Deadline rentals during playoff pushes
Mid-career journeymen signing one-year deals
Backup goalies rotating through organizations
Veteran depth pieces chasing roster spots

Focus on the 2010s especially, as modern free agency created more player movement than earlier eras. Check both teams' playoff years for deadline acquisitions that might connect them.

If you're obsessed with grid games, you need to try Gridzy Hockey, the NHL version of that daily "perfect grid" challenge.

Team × Narrow Stat Thresholds

Cells requiring specific statistical achievements with one team dramatically reduce possible answers. Examples include "Florida Panthers × 40-goal season" or "Columbus Blue Jackets × 100-point season," where franchise history limits who could have reached these milestones.

The Difficulty Factor

Narrow stats with specific teams create multiple filters:

Player must have played for that exact team
Player must have reached the threshold during their time there
Some franchises have short histories or few elite scorers
Career stats don't count, only single-season achievements matter

Expansion teams and historically weak franchises have very short lists of players who reached elite statistical thresholds while wearing their uniform.

How to Crack These

Learn each franchise's record holders and standout seasons:

Every team has 1-3 franchise scoring record holders
Playoff success years usually featured 40-goal or 100-point guys
Recent expansion teams have shorter lists (easier to memorize)
Check franchise record books during offseason for grid prep

For example, Florida Panthers' 40-goal club includes Pavel Bure, Olli Jokinen, and Jonathan Huberdeau. That's essentially your entire answer pool for that specific cell combination.

Ready for a new daily sports grid? Gridzy drops a fresh NHL grid every morning, and the best part is you can't use the same player twice.

Team × Very Specific Award

Awards with smaller winner pools create tighter constraints than common trophies. Examples include "Selke winner + Team X" or "Conn Smythe + Team Y," where only a handful of players in league history satisfy both conditions.

Why Specific Awards Are Tough

Less common awards have shorter lists:

Selke Trophy (defensive forward) awarded since 1978
Conn Smythe (playoff MVP) only goes to Cup winners
Lady Byng (sportsmanship) has niche winner profile
Calder (rookie of year) limits to players' first seasons

Combined with team requirements, you might only have 2-3 valid answers total for some combinations, and if you've already used those players elsewhere, you're stuck.

Memorization Strategy

Build short lists for specialized awards:

Selke winners by team (usually defensive centers)
Conn Smythe winners organized by franchise
Lady Byng winners (often low-penalty skilled players)
Award winners who played for multiple teams

These lists are manageable because fewer players win specialized hardware. Spending 30 minutes learning Selke history pays dividends across dozens of future grids.

Pre-Merger / Defunct Franchises

Cells involving relocated or defunct franchises require historical knowledge most casual fans lack. Examples include Hartford Whalers × 1,000-point career or Quebec Nordiques × All-Star appearance, where you need to know both the franchise lineage and which players were there.

The Historical Challenge

Defunct franchises add complexity:

Whalers became Carolina Hurricanes (1997)
Nordiques became Colorado Avalanche (1995)
Original Jets became Arizona Coyotes (1996)
Thrashers became current Jets (2011)

You need to know the main stars from each franchise's original location and which achievements they earned there versus after relocation.

Relocation Lineage Strategy

Know the star players from each relocated franchise:

Whalers/Canes: Ron Francis, Kevin Dineen, Gordie Howe's final years
Nordiques/Avs: Joe Sakic, Peter Stastny, Mats Sundin (early)
Original Jets/Coyotes: Dale Hawerchuk, Teemu Selanne (rookie season)
Thrashers/Jets 2.0: Ilya Kovalchuk, Dany Heatley, Marian Hossa

Learning just the top 5-10 stars from each franchise's pre-relocation era covers most grid needs without requiring encyclopedic historical knowledge.

Multi-Constraint Cells

Some grids hide multiple requirements in single cells or create implied constraints through surrounding categories. Examples include "Played for both A and B + won Award C" or situations where filling other cells correctly requires saving specific players for multi-constraint spots.

Why These Break People

Multiple simultaneous filters shrink answer pools dramatically:

Each additional constraint eliminates 80-90% of remaining options
Sometimes only 1-2 players in history satisfy all conditions
No-repeat rule means you might have already used your answer
Grid creators use these as deliberate difficulty spikes

The hardest grids place multi-constraint cells where several possible answers exist, but you've already used them in earlier cells, forcing you to find the one obscure player you haven't used yet.

Advanced Solution Approach

Think of true superstars who moved late in careers:

Hall of Famers who were not one-team players
MVPs or award winners who changed teams after winning
Elite players who ring-chased at career end
Stars traded at their peak (rarer but memorable)

Examples: Jaromir Jagr (played everywhere, won awards), Ray Bourque (Boston to Colorado), Chris Chelios (Montreal, Chicago, Detroit), Patrick Roy (Montreal to Colorado). These multi-team stars with hardware often unlock impossible-seeming cells.

You know that feeling when you hit a perfect grid? Gridzy Hockey gives you that same rush, only with NHL teams, trophies, and milestones.

Backup Goalie Cells

Goalie-specific cells are often harder than skater cells because:

Fewer goalies play compared to skaters (one per team at a time)
Backup goalies move frequently but aren't memorable
Starter-to-backup transitions create weird career paths
Most fans can't name backup goalies from even five years ago

When a cell clearly needs a goalie (both constraints involve goalie stats or awards), your answer pool shrinks to maybe 50 relevant players instead of 500, and if you don't follow goalies closely, you're guessing blind.

Goalie-Specific Strategy

Build mental categories for goalies:

Franchise starters (stayed 5+ years with one team)
Journeyman backups (played for 6+ teams)
Award-winning goalies (Vezina, Conn Smythe, Jennings)
Goalies who moved as starters between teams

Having even 20-30 goalies organized this way covers most grid needs. Focus on recent decades since older goalie careers are harder to verify and less commonly tested.

International Player Complications

When grids involve birthplace, nationality, or international achievements:

Eastern European players who played for Soviet teams before NHL
Players who switched national team eligibility
Olympic medals, World Championship golds, international caps
Drafted by team X, played for nation Y combinations

These cells require knowing where players were born, which countries they represented, and international hockey history beyond just NHL play.

International Knowledge Building

Focus on major hockey nations systematically:

Canada, USA, Russia, Sweden, Finland, Czech Republic
Learn top 10-15 NHLers from each country
Know which won Olympic gold or World Championships
Understand Soviet/Russian player migration patterns

This framework covers 90% of international grid cells without requiring deep knowledge of every hockey-playing nation.

Play Gridzy Hockey Free Every Day

Gridzy Hockey is Shurzy's daily NHL grid game where you pretend you're "just messing around" and then suddenly you're 15 minutes deep arguing with yourself about whether some 2009 fourth-liner qualifies as a 40-goal guy.

You get nine guesses to fill a 3×3 grid, you can't reuse players, and every pick is either a genius flex or instant regret. So yeah, it's basically hockey trivia with stakes.

New grid drops every day at 6:00am ET, which is perfect because nothing says "healthy morning routine" like panicking over who won the Lady Byng in 1998. If you think you know puck, prove it.

Go play Gridzy right now!

‍

Share this post: