Excellent épisode de statistiques avancées avec Stephen Valiquette, réfutant en partie l’article ESPN de Wyshinski, [here](https://www.espn.com/nhl/story/_/id/39902929/nhl-new-york-rangers-playoffs-2024-stanley-cup-analytics-data) Valiquette a contesté la statistique sur les Rangers étant mauvais en 5 sur 5 xG. Les Rangers sont 9e en 5 sur 5 xG, selon Clear Sight Analytics de Valiquette. D’autres points intéressants à retenir sont que les Rangers sont excellents dans : * Buts Est/Ouest * Équipes spéciales * Buts de rebond * Buts de déviation * Buts en échec-avant * Buts de mise en jeu Ils sont bien améliorés dans ces buts de jeu brisés et ces buts gras qui finissent par être si important en séries éliminatoires. La principale préoccupation concerne les buts autorisés hors de la course. Les derniers vainqueurs de coupe ont tous été parmi les 5 premiers et les Rangers se situent en bas de la ligue. Il espère que si Igor s’échauffe, cela neutralisera cette faiblesse. Il est également préoccupé par la production Kreider/Zibby line 5 contre 5. Il dit qu’ils sont trop sur le périmètre et qu’ils doivent placer la rondelle au milieu. Voici le lien vers le pod :
[https://podcasts.apple.com/us/podcast/bracing-for-ny-rangers-playoff-hockey-with-stephen/id1672627773?i=1000652119089](https://podcasts.apple.com/us/podcast/bracing-for-ny-rangers-playoff-hockey-with-stephen/id1672627773?i=1000652119089)
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TomGNYC
5 Comments
He didn’t make up the xG% numbers. That’s what you get when you look it up in EvolvingHockey (24th, 23rd if you use score and venue adjustments). NaturalStatTrick has the Rangers at 17th.
My biggest criticism of the article has to do with the stat about Panarin and the portion of his points scored on the PP (37%). This is a pretty normal number for elite/top-line players.
I have a spreadsheet that has all NHL players’ % of pts scored on the PP. I’ll grab examples and edit this post to include them later, but off the top of my head, I remember that Stamkos was at 50% last time I checked.
Back with some edits. Please note that this data is a month old, but it should still be exemplary of what I was talking about.
The top 10 players in points all recorded between 30-41% of their points on the power play, with Mikko Rantanen at the high end and Auston Matthews at the low. Of the players who had a reasonable amount of point at the time (let’s say 25), Shayne Gostisbehere, Mats Zuccarello, and Brandon Montour were all tied with the largest % of points scored on the PP at 56%. At the time Zuc had 50 point, 28 coming from the PP.
Compare this with Brandon Hagel, who had 6 pts on the PP of his total 60 points (coupled with his relatively low PP TOI). I would posit that Hagel, despite being a well regarded, is perhaps an under appreciated player.
I update this spreadsheet before the trade deadline and after the season to look and see what players might be underrated or overrated. It could also tip you off to players that might made a huge jump in points if given the right opportunities.
What do I do with this information and why do I keep these spreadsheets? My wife asks me the same thing. I don’t have an answer for you.
I wouldn’t say the Rangers are “actually” any particular ranking for xG%, and no one from that ESPN article made anything up (unless you just don’t believe in math as a concept). All the sites calculate xG a bit differently, and private models will typically have better data than public models that rely on the NHL tracking info. That doesn’t invalidate any of them, you just need to evaluate them with context.
For Vally’s Clear Sight Analytics in particular, they value cross ice/slot passing a lot. 10-16-13 are amazing at it, but it’s an area the team overall is good at.
I feel like when people are criticizing NYR and 5 on 5 they really mean Zibanejad and Kreider because BLT is dope.
But specifically criticizing two fan favorites is a sure way to get your take thrown out.
General statement: Public xG models are severely limited by what data the NHL provides to them. I find far more value in manually tracked numbers like CSA and A3Z.
Vally’s pod is based on his CSA numbers, which we don’t have access to. I did a rebuttal based on the data we all have access to: [https://blueseatblogs.com/2024/04/11/rangers-smoke-mirrors-goaltending-powerplay/](https://blueseatblogs.com/2024/04/11/rangers-smoke-mirrors-goaltending-powerplay/)
Rush chances against are a problem, but we don’t have that kind of info available publicly, and definitely not when we factor in post-deadline acquisitions, which for the Rangers, changed the entire complexion of the team.
Thanks, although after tonight…🫤