Sabre-Metrics: A closer look at Buffalo’s Advanced Stats

<em>Fire up your calculators, dust off the abacus, and get a pencil. We’re going in….</em>

We are 14 games into the 2021-22 NHL season and the Buffalo Sabres continue to surprise fans and pundits alike. It’s been a rollercoaster ride to date, with the 6-6-2 Sabres tallying upset wins against powerhouse teams such as the Tampa Bay Lightning and Edmonton Oilers, while laying eggs against the Sharks, Kings and Kraken.

So, with 17% of the season in the books (just warming up the calculator here), I figured I would take a look at the team’s statistical leaders and, furthermore, take a dip into some advanced analytics to see which players are driving Buffalo’s surprisingly successful start to this season.

Over the last few years, an increasingly popular grouping of player statistics called “advanced stats” has spread throughout almost every major sport. The methodology behind using advanced statistics to analyze a player’s productivity was made wildly popular by both the Michael Lewis book “Moneyball” and the subsequent Brad Pitt film of the same name. The story described how the Oakland Athletics, and their GM Billy Beane, pioneered the use of advanced statistics in baseball to put together a low budget yet successful team of players who excelled in various unheralded categories of baseball that actually affected the game more so then the usual glorified stats like home runs and strikeouts.

Collectively called “sabremetrics,” the term is perfect for a title piece on the DBTB site, but nevertheless, is not named after our beloved Buffalo hockey team. The term is actually derived from the acronym SABR which stands for the Society for American Baseball Research.

Fast forward from the 2011 film and the ripple effect from the A’s low budget success has made it’s way through every major sport, to include the NHL. As a result, fans have seen the rapid development and usage of such advanced hockey stats as CORSI and PDO.

Aside from their unusual names, the actual underlying equations behind CORSI and PDO are very intriguing in the never-ending quest to quantify how effective a player is on the outcome of a game. In hockey terms, trying to establish how much better a team is when said player is on the ice.

Given how dynamic of a sport hockey is, I do appreciate the idea behind this. Not every successful player scores bundles of goals or racks up gaudy point totals. Most hockey fans know that successful teams are littered with players who excel at the “little things” such as winning puck battles, getting pucks on the net and making smart plays that don’t necessarily show up on the stat sheet.


CORSI, named after former Sabres’ Goalie coach, Jim Corsi, was originally developed to measure the workload of a goaltender during a game. A CORSI rating is the measure of a team’s shot attempt differential, at 5 on 5, while a particular player is on the ice. So a player’s CORSI rating, usually listed as a percentage (CF% in the stat column), utilizes the total number of shots on goal, missed shots and blocked shots to quantify whether or not a team is successfully controlling a game while that player is on the ice. A player with a CORSI rating above 50% means that while he or she is on the ice, their team is controlling the puck over 50 % of the time and, therefore, more likely to succeed over the long haul.

Of course, there are numerous variables that can slant or slope a player’s CORSI rating. Certain line-mates, defensive matchups and sheltered playing time will always affect a players CORSI rating, but over an 82-game season, one can stipulate how the stat is useful in examining a player’s overall effectiveness on the game. (All advanced stats courtesy of

Top 5 Buffalo Sabres in CORSI Ratings (CF%)

1. F Rasmus Asplund    55.0

2. F Tage Thompson     54.6

3. F Victor Olofsson      54.1

4. F Jeff Skinner             54.1

5. D Colin Miller             52.2

Bottom 5 Buffalo Sabres in CORSI Ratings (CF%)

15. F Zemgus Girgensons      48.6

16. D Robert Hagg       47.5

17. F Anders Bjork        47.4

18. F John Hayden       46.4

19. F Drake Caggiula   45.8

*(Mittelstadt, Jokiharju, Murray and Wolanin are NOT included on any lists in this article due to limited playing time.)

Not all that surprising for those who have watched the Sabres this seasons, winger Rasmus Asplund is the team leader with a 55.0 CF% followed by top point getters, Tage Thompson, Victor Olofsson and Jeff Skinner. Perhaps most surprising to me is that winger Drake Caggiula sits at the bottom of the list with a 45.8 CF%. Given Head Coach Don Granato’s penchant towards keeping lines and D-pairs together (the most recent defensive shuffle notwithstanding) analyzing the CF% can be particularly useful when comparing a player against his or her respective line-mates.

For example, centreman Arttu Ruotsalainen holds a 49.1 CF% while his line-mates, wingers Anders Bjork and John Hayden, are at 47.4 and 46.4 CF% respectively. Given CORSI is a summation of stats at 5 on 5, this tells us that Ruotsalainen has excelled off of the 4th line and is perhaps likely to drive play higher up in the lineup when given the chance.


Another common advanced hockey statistic is called PDO or SPSV%. This stat measures the sum of a team’s shooting percentage and save percentage when the player in question is on the ice. The term PDO actually doesn’t stand for anything (although it sounds like PDA) and according to the all-knowing Wikipedia, was actually named after a video gaming handle. Another commonly used acronym, that is interchangeable with PDO is SPSV% (Shooting Percentage + Save Percentage) which makes way more sense to me, but I digress.

To be clear, PDO takes into account all 5 skaters’ shooting percentages while that specific player is on the ice, not just the individual player’s shooting percentage. So, with that in mind, here are the top 5 and bottom 5 of the Sabers’ roster in PDO ratings.

Top 5 Buffalo Sabres in PDO (SPSV%)

1. F Victor Olofsson 104.6

2. D Mark Pysyk 103.8

3. F Anders Bjork 103.8

4. F Tage Thompson 102.3

5. F Drake Caggiula 101.6

Bottom 5 Buffalo Sabres in PDO (SPSV%)

15. F Jeff Skinner 97.8

16. F Vinnie Hinostroza 97.8

17. D Will Butcher 96.2

18. F Cody Eakin 92.9

19. F Dylan Cozens 92.5

For some perspective, a player’s PDO, stepping onto the ice for the first game of the season is 100, since their shooting percentage is 0 and the team’s save percentage is at 100. So when looking at a players PDO, a score of over 100.0 means that your team is making more saves and scoring more while you’re on the ice. Conversely, a PDO score under 100.0 relays that opposing teams are more effective at scoring while you’re on the ice. Interestingly enough, this stat line turns some of the CORSI stats upside down. However, when looking at both PDO and CORSI in conjunction with each other, they can actually tell a very interesting story.

A perfect example is Drake Caggiula. The winger has the lowest CORSI rating on the team at 45.8%  but is fifth on the team with a 101.6 PDO. This could imply that Caggiula is often playing against an opposing team’s top players and therefore is on the ice for more shots against. However, given his high PDO, he appears to be limiting the opposing team’s shot effectiveness, while adding to his own line’s shooting success. It’s an interesting dichotomy which clearly displays the disadvantages of relying on one stat line to evaluate a player’s effectiveness. Another interesting case is winger Anders Bjork, who like Caggiula, is on the bottom of the Sabres’ CORSI list at 47.4% but tied for second in PDO with a 103.8. This contradiction in stats tells us that Bjork is an effective counter puncher and while teams control the puck more often while he is on the ice, the Sabres winger is effective in limiting quality chances while driving his own line’s scoring chances.

A look out to the blue line shows defenseman Mark Pysyk scoring impressive marks in both CORSI and PDO. Lucky number 13 is standing out in both categories, slightly tilting the ice in CORSI at 50.5, and very effective in PDO at 103.8. Having watched every game this season so far, I can’t say I’m surprised. Pysyk has been good.


Overall, I find advanced statistics very interesting but, like all stats, will never rely on them to tell the whole story. With sports awash in statistics of every kind these days, I do believe that it’s noteworthy and relevant to at least know about a few of them. When looking at these unique stats together, they do expose certain aspects of a player’s game that are intriguing to me as a fan. However, in my opinion, hockey is such a complicated sport that a player’s performance can never be successfully evaluated by one metric system. At the end of the day, I still trust my evaluations from the cheap seats.