How has each Islander historically performed in playoffs?: Part One
The New York Islanders are set for their first round matchup against the Pittsburgh Penguins. The Islanders will need every player to perform in order to knock off the Penguins, given Pittsburgh's history of playoff success but how has each individual Islander historically performed in the playoffs versus the regular season?
Obviously, Mathew Barzal has no playoff experience in the NHL, so for some sort of indication, you can look to his Western Hockey League regular season vs playoff performance. With Seattle in the WHL, Barzal played 202 regular season games, where he had 63 goals and 278 points across four years. He had a 0.31 goals per game (GPG) average and 1.38 points per game (PPG) average. In his 202 games, he was a plus-70, an average of 0.35 positive plus/minus points per game. Barzal also played 49 playoff games with Seattle and his goals per game average was up to 0.35 goals per game, while his points per game average was 1.33, down very slightly from his regular season stats. He was a plus-11 in his 49 playoff games, an average of 0.22 positive plus/minus points per game. Barzal’s statistics were very similar between the regular season and playoffs. Obviously the WHL playoffs can’t begin to compare to the gravity of the NHL playoffs but Barzal’s history at least shows his play hasn’t differed between the regular season and playoffs.
Bailey, like many others, has a limited sample size to work with in the playoffs. That being said, he hasn’t shown much difference between regular season and playoff statistics. He’s scored four goals and 11 points in 22 games, a 0.50 points per game average in three different playoff stints, compared to his regular season 0.54 points per game average. His goals per game average in the playoffs is 0.18, the same goals per game average he’s totalled through regular season games. He’s carried a negative plus/minus points per game average of 0.06, while in the playoffs, Bailey has averaged a negative 0.18 plus/minus points per game average but the increase can also be due to tougher competition. He’s also averaged 2.05 shots per game in the playoffs, up from his regular season 1.58 shots per game (SPG) average. His playoff Corsi For percentage (CF%) is 47.8, down slightly from his regular season CF% of 48.7.
Similar to Mathew Barzal, Beauvillier has no NHL playoff experience but we can look to QMJHL playoff records. His regular season GPG average was 0.51 and PPG average of 1.16. Comparatively, his playoff GPG average was 0.53 and his playoff PPG average was all but identical, rounding to 1.16 as well. His SPG average of 5.00 was up from his regular season average of 4.23. So again, though the WHL postseason can’t compare to that of the NHL, it’s still a good indication of Beauviller’s ability to perform in high-pressure games.
Casey Cizikas’ playoff stats almost mirror his regular season stats perfectly. In 24 career playoff games, his 0.13 GPG is the same as his regular season GPG average and his 0.33 PPG average is the slightest bit higher than his 0.32 regular season PPG average. At a career plus-one in the playoffs, he carries a 0.04 positive plus/minus per game average, again almost matching his regular season 0.04 positive plus/minus per game average. He’s averaged 1.29 SPG in the playoffs, up slightly from his 1.19 career SPG average. He does have a 45.4 CF% in the playoffs, up from his regular season career CF% of 40.9. Of anyone, Cizikas may be the most consistent between regular season and the playoffs of any Islanders forward.
Cal Clutterbuck isn’t relied on for his production, but nevertheless he’s a forward and we’ll take a look at his stats. Clutterbuck’s GPG is higher in the playoffs (0.22) than it is in the regular season (0.15) and his PPG is higher as well in the playoffs (0.35 vs 0.29). His SPG are very similar, with a 1.83 in the playoffs and 1.78 in the regular season, while his CF% is slightly lower at 43.7 as opposed to 44.3 in the regular season. Clutterbuck’s production one way or another though probably isn’t going to make or break a series.
There’s no arguing— Jordan Eberle’s playoff stats with Edmonton in 2016-17 look ugly. The winger had no goals and just two assists in 13 playoff games, with a minus-six rating to show for. Contrast this against his regular season PPG average of 0.72 and regular season GPG average of 0.31 and it doesn’t look great by any means. As you dive into his advanced stats though, he really wasn’t as bad as he seemed. His SPG average was down from 2.37 to 1.69 but Eberle still had a CF% of 55.4. If you dig a little deeper, the team shooting percentage while Eberle was on the ice was a ridiculous 2.9%. Eberle’s advanced stats show he was unlucky in the playoff run. That being said, it’s hard to use advanced stats as an argument in the playoffs, where key players need to produce. The advanced stats suggest that Eberle’s production may look better this time around, that being said, he needs to produce.
Scratch Cizikas, Valtteri Filppula may have the most similar numbers between the regular season and playoffs. Filppula’s playoff GPG average is 0.16, down from his regular season’s 0.20 but his PPG average is consistent at 0.52 between both. His SPG playoff average is 1.64, up from 1.42 in the regular season, while his CF% is identical between both regular season and playoffs at 52.6. He has a positive plus/minus of 0.04 in the regular season and a 0.03 positive plus/minus in the playoffs. Filppula may not be the same player he was a few years ago but he he’s historically been very consistent in the playoffs.
Komarov has seen his production fall in the playoffs. He has no goals and just one assist in 15 career playoff games, compared to his 0.36 PPG regular season average. His playoff SPG average is down from 1.40 to 1.13 in the playoffs and his CF% is down from 45.6 to 42.9. Komarov isn’t known for production but he’ll need to be better than playoff history has shown.
Kuhnhackl is someone who also isn’t known for production but it especially doesn’t come in the playoffs. His PPG average is down from 0.24 in the regular season to 0.15 in the playoffs, his SPG average is down from 0.95 to 0.74 and his CF% is down from 39.6 to 37.5. Needless to say but his numbers definitely aren’t excellent.
Lee has a small playoff sample size so let’s not read too much into it. Lee had no goals and only one assist in five playoff games in 2014-15 and averaged 1.60 PPG and a 53.1 CF%. These numbers are obviously down from his 0.61 regular season PPG average, 2.48 SPG average and 57.3 CF% but remember that the playoff numbers did come in Lee’s first full NHL season as well.
Martin isn’t a guy who’s going to put up points but we’ll run through the comparison quickly anyways. Broken record? Oh well. Martin’s playoff PPG average is down to 0.13 from 0.19 and his SPG average is 1.16 from 1.20. That being said, his playoff CF% is up quite a ways to 50.2 from 45.8. All in all, pretty similar.
Nelson has only played 18 playoff games but his numbers are down slightly from how he’s produced in the regular season. Nelson holds a 0.39 PPG and 2.00 SPG average, down from his 0.50 regular season PPG average and 2.04 SPG average. He also holds a negative 0.28 plus/minus per game playoff average, down from his positive 0.01 plus/minus average and his CF% drops from 51.7 in the regular season to 49.1 in the playoffs. It’s not a significant drop in play by any means but the stats do show his playoff performance is lower in every category from the regular season.
Part Two, going up later tonight, will take a look at how each defenseman and goalie has performed in the playoffs against their career regular season stats.
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