The Most Antagonistic NHL Teams

Ever wondered which NHL teams are the most aggressive? We’ve crunched the numbers to reveal the most antagonistic professional ice hockey teams and players.
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The NHL is adored around North America for guaranteed drama, speed, and high-aggression play. But which teams and players are the most antagonistic overall? We decided to find out.
By analyzing the penalty and fight records for each NHL team and its players between the 2017/18 and 2021/22 seasons, a new study by Betway has been able to reveal the most antagonistic teams and players.
From there, the number of penalties and fights for this season was forecasted by using an exponential smoothing algorithm* to reveal who is likely to be the most antagonistic this season.
Which NHL teams give away the most penalties?
Comparing data between the 2017/18 and 2021/22 seasons, we can reveal that the Tampa Bay Lightning are the most antagonistic team in the NHL, receiving an astonishing 1,558 penalties over the last five years. Although they rank seventh when we only consider major penalties (105).
Next up, the Nashville Predators conceded 1,533 penalties between 2017-2022, 131 of which were majors – more than any other hockey franchise. The Boston Bruins rank third (1,481), followed by the Anaheim Ducks (1,463), and New York Rangers (1,440).
Meanwhile, the Washington Capitals rank sixth, receiving 1,433 penalties since 2017, more than Colorado Avalanche (1,427), Minnesota Wild (1,411), and Calgary Flames (1,407).
Looking at the other end of the table, Seattle Kraken have the cleanest record, with just 279 penalties received since 2017 – only 26 of which were majors. This comes as no surprise as the newfound team has yet to make its mark on the ice. Other teams in the lower half – those who are least antagonistic - include the New York Islanders (1,216), St. Louis Blues (1,262), Los Angeles Kings (1,268), Edmonton Oilers (1,315), Winnipeg Jets (1,317), and Philadelphia Flyers (1,327).
Which NHL teams are predicted to be the most antagonistic this season?
Based on data from the last five years, we’ve been able to forecast the NHL’s most antagonistic teams for this season.
Leading the way, the Nashville Predators (322) are expected to receive more penalties than any other team this season, ahead of the Tampa Bay Lightning (321), and current Atlantic Division leaders the Boston Bruins (311).
Which NHL players get into the most fights?
Analyzing fight data across the NHL since 2017/18, it’s interesting that only two of the top-ten most aggressive players feature for the same franchise (Calgary Flames), while the most common position is left wing. But no players are more antagonistic than Nicolas Deslauriers. In fact, the Philadelphia Flyers left wing has been involved in 39 fights over the last five years, including 13 last season.
Washington Capitals right wing Tom Wilson ranks second with 34 fight involvements, followed by Ottawa Senators left wing Austin Watson (33), former Florida Panthers center Michael Haley (32), and Tampa Bay Lightning left wing Patrick Maroon (30).
Meanwhile, Nashville Predators defenseman Mark Borowiecki (29), Minnesota Wild right wing Marcus Foligno (26), and Los Angeles Kings left wing Brendan Lemieux all have 25+ fight involvements, ahead of Seattle Kraken right wing John Hayden (22). Finally, Calgary Flames left wing Milan Lucic, Toronto Maple Leafs left wing Kyle Clifford, and Philadelphia Flyers centre Zack MacEwen round out the top ten, with 21 fights apiece.
After crunching the numbers, we can reveal that, statistically, no other NHL player will get into more fights this season than Nashville Predators left wing Tanner Jeannot (14).
Next up, Mark Borowiecki and Nicolas Deslauriers are expected to be involved in 13 fights each, ahead of MacEwen (12), San Diego Gulls center Sam Carrick (11), and Minnesota Wild right wing Brandon Duhaime (11), while Arizona Coyotes left wing Liam O’Brien, San Jose Sharks left wing Jonah Gadjovich, Minnesota Wild defense Jacob Middleton, Marcus Foligno, and Patrick Maroon are all forecasted to feature in 10 fights.
Finally, Detroit Red Wings right wing Givani Smith might feature just outside the predicted top ten players for 2022/23 fights (9).
With the 2022/23 NHL season well underway, it’ll be interesting to see whether our predictions prove to be correct! In the meantime, check out all the latest NHL news in the world of sport.
Methodology
We analysed stats from past seasons to figure out which NHL teams and players are the most aggressive and partake in the most fights. We collected data from NHL.com and hockeyfights.com and compiled the results. This shows us which teams and players are the most antagonistic, from 2017/2018 to 2021/2022.
- Team Penalty data - https://www.foxsports.com/nhl/team-stats?category=miscellaneous
- Player Fight data - https://www.hockeyfights.com/leaders/teams/1
This data set looks at the NHL teams and individual players between the 2017/2018 and 2021/2022 seasons, to reveal the most antagonistic.
The teams were ranked based on the minor and major penalties received, and their total penalty minutes. For the players, we collected data on the total fights they were part of during each season.
*The forecast was done as follows:
Once the team penalty data and player fight data were collected for the previous seasons (2017/2018 – 2021/2022), they were ready to be used to forecast the data. First the season numbers had to be altered to individual years, to allow for forecasting. To do this, the seasons were changed to their ending year (e.g 2017/2018 becomes 2018), as most of the season takes place after the new year. From here the “forecast.ets” function was used for the forecasting. This function calculates or predicts a future value based on historical values by using an exponential smoothing algorithm. A normal linear forecast would take an average of values over the historical time period and would extend this average line to the future. The exponential smoothing algorithm instead gives more weight to values closer in date to the present, meaning values for 2022 carry more weight in the prediction than for values from 2018. This helps to increase the accuracy of the forecast.
The inputs for this function are:
- Target date - The year you want to predict data for. We need to run a different formula for each year we are forecasting for.
- Values - The values you wish to forecast, in this case player fights or team penalties.
- Timeline - The corresponding years for the values, in this case 2018 through to 2022
Once the values for team penalty data and player fight data were forecasted, they were then added to the corresponding tables. Each value was rounded to the nearest whole number, and values that were predicted to become negative were cut off at 0, as you cannot have a negative number of fights or penalties. Seattle Krakens were not included in the forecast, as they only have one years’ worth of data, so any resulting forecast would be inaccurate and unreliable.
This data is accurate as of 09/29/2022.