Tag Archives: stats

nhl power rankings and projections: dec. 17

In this week’s edition of the power rankings, I have completely revamped the model that churns out the numbers. If you’re curious, this is a post explaining the new method, but the gist is that I’m now using score-adjustments rather than score-close. That plus a re-weighting of 5-on-5 and special teams data.

Here are last week’s rankings with the old method, and with the adjustments there’s obviously some big changes this week as some teams went up thanks to the adjustment, and some teams went down.

The biggest news is there’s a new number one this week as Pittsburgh’s long reign at the top is over thanks to scaling back the weight on special teams.

Continue reading nhl power rankings and projections: dec. 17

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a better playoff output projection

If you’ve been following me for a while, then you’re probably aware of a stat I created called POP which aims to predict the playoffs and more accurately forecast who the best teams in the league are.

There’s been some work done recently, as well as suggestions from smarter people, that’s made me consider making changes to the stat.

In its current iteration, POP is (Fenwick Close + ((0.6 x Goals Close)/PDO Close)) x (PP% + PK%). The first part of the equation is very similar to what Tom Tango is working on right now with weighted shot differential, so it was interesting to see someone else working on something similar.

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nhl power rankings and projections: dec. 10

In this week’s power rankings, Washington crawls back into the top five, Pittsburgh finally falls below 100 and the biggest drop of the week belongs to Carolina who fall into the bottom ten.

Meanwhile, the Leafs find themselves just outside the top ten and somehow ahead of St. Louis and Nashville.

If you haven’t read it yet, this is how I’ll be measuring each team this year. And here is last week’s rankings.

Continue reading nhl power rankings and projections: dec. 10

nhl power rankings and projections: dec. 3

In this week’s power rankings, Washington and Anaheim fall out of the top five, Pittsburgh loosens its stronghold on the number one spot and Dallas has the biggest drop of the week falling into the bottom 10.

Meanwhile, the Central division continues to show its strength while the Metro division is a downright laughingstock .

If you haven’t read it yet, this is how I’ll be measuring each team this year. And here is last week’s rankings.

Continue reading nhl power rankings and projections: dec. 3

nhl power rankings and projections: nov. 26

In this week’s edition of the power rankings, almost every team is in the same spot as last week, which means the rankings are stabilizing, which is only a good thing.

Pittsburgh continues its dominance, having spent every single week at the top as Chicago moves into No. 2 after finally getting some luck in the goal scoring department.

Anaheim is showing they’re for real this year as they slide into the top five at the expense of Tampa Bay, and Florida drops all the way to 22 after getting dominated territorially in just about every game this week.

If you haven’t read it yet, this is how I’ll be measuring each team this year. And here is last week’s rankings.

Continue reading nhl power rankings and projections: nov. 26

nhl power rankings and projections: nov 12

In this week’s edition of power rankings, Minnesota drops out of the top five, while St. Louis vaults right into it. The weeks biggest shock though belongs to the Leafs who find themselves projected for a playoff spot for the first time.

The Kings continue their surprising struggles and the Devils fall 12 spots almost to McDavid territory, and boy wouldn’t that be the worst team possible to draft him.

If you haven’t read it yet, this is how I’ll be measuring each team this year. And here is last week’s rankings.

Continue reading nhl power rankings and projections: nov 12

2013-2014 stanley cup final preview

The Stanley Cup Final is set and it’s a match made in TV heaven. The two biggest markets in the USA square off in what will likely be a ratings bonanza.

New York. Los Angeles. Somewhere Gary Bettman is smiling while a paid butler makes it rain. This matchup is probably all he ever wanted.

This is a matchup that many analytics types had predicted from the get go (one even made over $3,000 from a $75 bet on twitter dot com).

The Kings led the league in puck possession, and got even better after acquiring Marian Gaborik.  They were the fourth best POP team in the West and seventh in the entire NHL. But in their last 25 games they were second to only Boston in the entire league.

The Rangers were a Stanley Cup dark horse going in, quietly being the sixth best possession team in the league. They were right behind the Kings as the eighth best POP team, but also the fourth best in their last 25 games of the season (behind Boston, Los Angeles, and San Jose).

Coming in to this playoffs, POP was at 56-19 in accurately predicting series outcomes. This year it’s stumbled to an 8-6 record through three rounds after going 1-1 in Round 3 (POP over the last 25 games is 10-4 and was 2-0 in Round 3).

Five of those six losses came in a seventh game against a road team. A bounce the other way and that record would be a bit more respectable.

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2013-2014 nhl playoffs preview: round three

In case you haven’t read it yet, this is the system I’m rolling with this year that combines possession, talent, and special teams.

It’s going really well so far…

POP is currently 7-5 after going 2-2 in round two (goddamn east). Which is not very good. Before this year it went 56-19 since 2008-2009, so this year has been very crazy compared to other years in terms of upsets and a lot of series could’ve went the other way.

Take for example the six (!) series that went to seven games.

The home team is 1-5 in those games. They all had a 3-2 (or better) series lead. POP had them all to win except Anaheim in Round 2, so a 2-4 record in series that went to seven. Sometimes that’s the way it goes. In only one of those instances where the series went to seven, did the team that played better in that series win (Minnesota over Colorado) although you can say the San Jose-LA series was a toss-up.

Basically, a lot of bad luck going the home (and arguably better) team’s way, and in turn, my way as well.

Continue reading 2013-2014 nhl playoffs preview: round three

2013-2014 nhl playoffs preview: round two

Wow. That’s all I can say. Round 1 had some of the best hockey I’ve seen in a few years.

If you missed it, this is how I said I would be predicting the playoffs this year. To summarize I combined fenwick close (possession), goals close adjusted for PDO (talent), powerplay and penalty kill (special teams) to get a number that was accurate 75% (56-19) of the time over the last six years.

In Round 1 this year, it went 5-3. Which is okay, but definitely not great. It’s below the 75% average, so I’m a little disappointed. Especially considering it was 5-1 going into the last two game sevens where both teams were on home ice, had leads in the games, and 3-2 leads in the series. But thats sports. Anything can happen. Luck is a big part of the game and it’s something I mentioned in the last post.

That’s not to say the teams that won were lucky to win, it means that a bounce or two the other way and maybe San Jose wins in game 4…or 5… or 6… or 7 (jesus..) or Colorado puts it away in overtime. In any sense, stats are always a probability, not a destiny. Seeing a team go against the odds like LA (although it’s because of luck that they were down 3-0 in the first place) and win is what makes sports great. No one would watch if everything that happened was predictable.

With all that being said, here’s what I think will happen in round two, a round that’ll probably be much more cut and dry than round one.

Continue reading 2013-2014 nhl playoffs preview: round two

2013-2014 nhl playoffs preview: round one

I wrote something yesterday about how I would be predicting the playoffs this year, based on a combination of stats. That stat is better used over larger sample sizes especially with how volatile special teams can be. But just for fun, this is for the “what have you done for me lately crowd.”

Basically I took 25 game averages throughout the year of each team’s POP and compared it to the teams opponent. It’ll be interesting to see if this works better than looking at a team’s overall number, and it also shows how close the teams have been throughout the year. Also, due to the small sample size, some teams will be over 100%, which is pretty neat I guess. Also, for the record, anything below 70 is really bad. No team has ever made the playoffs with a POP below 70, and some of the teams below played like that for significant stretches of time.

Continue reading 2013-2014 nhl playoffs preview: round one

predicting the nhl playoffs

Using Stats to Predict the Playoffs

No single stat will ever tell you the entire story in hockey. And that’s especially true when you want to use them to to look at what the future holds. On any given night, any team can win. Luck plays a big factor in that.

Over a large enough sample size, some of that randomness will be tuned out.

But then we get to the playoffs and it’s decided in a gruelling seven game series, where luck again plays a huge role because of the small number of games. It’s why the playoffs are so exciting, they’re unpredictable.

And yet, everyone tries to predict them.

Some just say “well this team stacks nicely up against this team” with their chests puffed out, knowing full well they’ve probably seen both teams play two or three times a year when they came through Toronto to play.

Most people use what they remember from watching those past games and using any number of stats to fill in the blanks. Mostly because using just one stat won’t tell you the whole story.

If you did, these are the stories they would tell.

Continue reading predicting the nhl playoffs