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Home / NHL

NHL Puck Line Stats: Which Teams Actually Win by 2+ Goals?

  • The puck line is usually set at 1.5 goals in hockey betting.
  • -1.5 requires a two-goal win for a bigger payout; +1.5 covers every close game.
  • Last season, underdog +1.5 bets broke even, but price and trends are key.
Ryan Tucker
By Ryan Tucker • Sports Editor & Betting Analyst
Sports Tipster & Betting Model Expert
Updated:
NHL Puck Line Stats

What the puck line is


The puck line is hockey's spread, and it is almost always 1.5 goals. A team at -1.5 has to win by two or more, and you get a bigger payout than the moneyline. A team at +1.5 can win or lose by one, and you pay a bigger price for that cushion. Every game has both sides, so this page looks at both.

The 2025-26 baseline


Shrink last season down to 100 games. Here's how they finished:

  • 41 games: won by 2+ goals, no empty-netter needed.
  • 16 games: won by 2+ goals, but only because of a late empty-net goal.
  • 18 games: won by one goal in regulation.
  • 25 games: decided in overtime or a shootout.

So the winner won by two or more in 57 of 100 games, and the loser stayed within one in the other 43.

Two moments swing the puck line more than anything else. When a team is up 3-2 and the other side pulls its goalie, an empty-net goal makes it 4-2 and flips both sides of the bet. And every overtime or shootout game ends with a one-goal margin, so -1.5 always loses it and +1.5 always wins it. That was one game in four last season.

Puck Line comparisons last season


Here's what $100 on every bet returned at closing prices in 2025-26:
Blind betTypical priceHit rate
Return per $100
Favorite -1.517033.10%-$14.80
Underdog +1.5-21867.00%about even
All teams -1.5-28.20%-$13.80
All teams +1.5-71.80%-$2.20

The case for -1.5 - The payout does the work. At around +170, one win covers almost two losses, so a team only needs to win big a bit more often than its price says. Buffalo did that all season and returned +29.4 units on -1.5. The catch is that -1.5 loses every overtime game and often needs an empty-netter to get home, which is why it was the worst blind bet on the board.

The case for +1.5 - It wins most of the time, including every overtime game and every one-goal loss. Underdog +1.5 was the only blind bet that came out roughly even, with the bookmaker's margin already in the price. The catch is the price. At -218, one loss wipes out about two wins, and part of last season's edge came from favorites winning less often than usual, which may not repeat.

2026-27 live table



"Won by 2+" shows how many of a team's wins came by two or more goals, and the red tick is the league average. 
"Needed ENG" is how many of those only got there with an empty-netter, and "OT/SO wins" is how many wins came after regulation. 
The margin label sums it up: Wide teams win by 2+ often, Tight teams win close, and Average sits in between. In the 2025-26 view, the P/L columns show what one unit on that team every game returned on each side. An asterisk means fewer than 10 wins this season, so treat that number as noise.

Working out a fair price


You can turn the table into a fair price for both sides in three steps. Take a -200 favorite, which wins about 67% of the time. Say it wins by 2+ in 70% of its wins.

  • 67% x 70% = about 47%. That's the favorite's chance to cover -1.5, a fair price of about +114.
  • 100% - 47% = 53%. That's the underdog's chance to cover +1.5, a fair price of about -114.

Compare both with the book. If one side pays more than your fair price, the numbers lean that way. If neither does, they don't point anywhere.

When the numbers break


Small samples: early in the season, and the P/L columns only cover one season.
The year: 2025-26 was a bad year for favorites, which helped +1.5 and hurt -1.5.
Price: the same team can be a good bet at one price and a bad one at another.
Goalies: a backup in net changes margins more than anything in this table.

Ryan Tucker
Ryan Tucker

Sports Editor & Betting Analyst • Sports Tipster & Betting Model Expert

Ryan is a sports content writer and editor, producing insights and analysis for major sports including NFL, NHL, NBA and more.


Born in Australia, multiple trips to North America deepened his love for the four major US sports and a continuing dream to catch as much live action as possible.

Stats and data analysis has now outgrown the hobby tag and the countless models and simulations are now being put to good use writing previews and predictions for all major sporting events across basketball, ice hockey, baseball, football and Australian sports that are still close to his heart.

You can find Ryan on Muckrack and LinkedIn.

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