Putting it all together: A hockey systems, stats, tools, and talent evaluation primer


Last summer, I was asked to provide some insight into which stats I use, how I use them, and why I use them. I held off on writing that post until now for a few reasons, most importantly being my personal use of the stats available. This is going to be a very long post about how I use stats, why I use them, and how my use of them evolved over time.

First things first, I am not a statistician. For the most part, I do not understand a lot of the stat posts I see that dive into r-squared calculations. I read the first paragraph, I skim through the meat –which is where these posts begin to lose me– and then I read the conclusion. I also read what the trusted minds say about these pieces, and I draw my conclusions from there. But generally speaking, the “mainstream” stats have been peer reviewed multiple times. In any field, from math to medical to business, peer review is essential, which is why these are the ones that hit mainstream.

Why/How I use stats

I think this is a good place to begin. When I first began blogging in 2008, I had no insight into stats other than what I saw on the stat sheet. It wasn’t until the 2013-2014 season when I started to understand what Corsi was and why it was important, and how deployment –quality of teammates, quality of competition, zone starts– was important. The more I read, the more I used it in my posts. The more I used it, the deeper the dive I took into the stats as a critical analysis tool.

Sometime during the 2014-2015 season, I had hit the point where I was using stats for roughly 80-90% of my analysis. Generally speaking, the conclusions weren’t too far off from accurate, but it wasn’t the right approach for me. I started tying systems into my player analysis, and how each player’s skill set fit into a system. From a Rangers perspective, this meant focusing on the guys who could skate and keep up with a difficult hybrid man/zone defensive zone system. After identifying those players with that skill set, then I would look at the stats to see if my eyes matched the data. It wasn’t until I saw how far off I was with Marc Staal that I realized I was on to something.

A little backstory on Staal: I am still an unabashed Staal fan. I thought he was truly the next great Rangers defenseman, and there’s a good chance he could have been if not for injuries. His poor play was masked by Anton Stralman. And it wasn’t until Dan Boyle started to fade that his deficiencies, the ones on paper I ignored prior, started to show for my eyes to see.

Fast forward to today, and we have so much more available. For players that I watch regularly, I follow the above style of matching what I watch regularly to what I see on paper. If my eyes don’t match what I see on paper, I trust the paper and try to see where I was wrong. Using Staal as the example here, I spent more time focusing on him, and realizing that while still a good skater, he couldn’t pass the puck in a manner that warrants his ice time or salary. It’s a tough pill to swallow, that the paper knows more than your eyes, but it’s true when you use the paper correctly.

One last aspect that is absolutely critical is that these are all generalizations. There are exceptions to the “rules,” or outliers as they are called in stats. There are no absolute statements. These tools are used to evaluate the lower 90% of players to get an edge, not the upper 10% that are the elite players in the league.

The stats I use


Perhaps the biggest misconception with stats, specifically Corsi, is that many think it is the one stat that tells you if a player is good or bad – that the stat is comparable to WAR in baseball.

Corsi is not WAR. It’s not even close. Corsi should not be used on its own as an evaluation tool. Any stats person who shouts Corsi at you without stating anything else is doing it wrong. Corsi is a tool to be used in conjunction with deployment, effect on teammates, points, and rate stats (per 60 minutes of  play stats). But what exactly is Corsi, and why does it matter?

Corsi is a registered shot attempt (on net, post, missed, blocked) for your team or against your team while you are on the ice. If your team takes more shot attempts while you’re on the ice, then you have the puck more, and you could be a reason why your team has the puck. The opposite is also true. The best players in the league are those that register many shot attempts for while limiting shot attempts against.

For forwards, this is pretty straight forward. You want a player that has the puck a lot and drives these attempts. As Wayne Gretzky said, you can’t score on 100% of the shots you don’t take. There are nuances for sure, and not all shots are created equal, but as long as you have the puck, the other team can’t score and you will generate more quality chances.

For defense, it’s a little tricky. The game has evolved from the two roles of offensive defenseman and shutdown defenseman. The guys perceived as shutdown defensemen are viewed that way because they block shots and deliver hits. However if you are doing these while on the ice, you don’t have the puck. That’s not to say there isn’t value in blocking shots and delivering timely hits. They are a skill set that every team needs. However it is not the best evaluation of a defenseman in today’s NHL. You want players that can block shots and deliver hits as a complement to other skills, not as their primary skill.

That’s where CF (Corsi-For) and CA (Corsi-Against) come into play. It helps you split your paper evaluation of defensemen into two segments: Does he push offense, and does he stifle the opposition? The critical piece here is realizing that CF and CA numbers are the result of smaller plays that many say the stat doesn’t evaluate. Such plays that actually show up in CF/CA:

  • Gap control
  • Going to the corner for a loose puck
  • Tying someone up along the boards, and kicking the puck to a teammate
  • That first pass from behind the net to a teammate at the half boards to start the rush
  • A good stick check to break up a play at the blue line
  • An active stick in a passing lane
  • Using the body to protect the puck

I’m sure I missed some, but these are the plays that I see in my mentions on Twitter as being the flaws of Corsi. It’s actually the opposite. These plays are Hockey 101 plays, and while there is no direct stat for each one, they are all inputs into CF/CA. Players with good CF/CA generally make these kinds of plays.

The interesting part here is that in today’s NHL, the same skill sets are required universally to survive in this league. Quick feet, good skating, good hockey IQ, quick hands, good vision, and solid passing. Skills and Corsi are not mutually exclusive.

Scoring Chances

Scoring chances are just like Corsi, except these are chances –missed, blocked, posts, on net– that are defined by distance from net and type of play. Same concepts above apply, just for a better quality chance.

You expect your better forwards to have better scoring-chance-for (SCF) numbers. You expect your best defensemen to have great scoring-chance-against (SCA) numbers.

High Danger Scoring Chances

Another type of scoring chance, but these are generally your point blank shots. Same concepts above apply.


Deployment is a critical aspect of talent evaluation, and where things start to get a little tricky. As mentioned above, using Corsi on its own is flawed. There needs to be an understanding of how a player is used to get a full understanding of the numbers. Is a player being dragged down by defensive zone starts and playing against the best quality competition? Is a player being dragged down by bad linemates?

The basics of deployment are simple for forwards. The most skilled players get the most ice time in the offensive zone, and their numbers show. Those that are supposed to excel defensively are given defensive zone starts, with the job of limiting shot attempts –thus preventing quality chances and goals– and pushing the play up to the offensive zone, where the scorers can light the lamp. Every player has a role.

Measuring effectiveness in this role is where a lot of confusions lies. If a player is being deployed against top competition in the defensive zone, then he is expected to have good CA numbers. The logic is simple: He is being deployed this way because he limits shots and goals against. He uses all those little plays listed in the bullet points above to frustrate the opposition, force a turnover, push the play up the ice, and then get off the ice for the scorers. A good CA reflects all this, but they may not have a good CF. This is what you expect of players like Marc Staal, and Dan Girardi. And therein lies the critical aspect: Deployment doesn’t deliver results. Skill and effectiveness deliver results.

On the flip side, a good CF is expected from someone who is charged with driving offense, getting the puck to the net, and putting up points. This is what you expect of your guys like Keith Yandle, who will drive possession but may not limit shot attempts against. Yandle isn’t viewed as great in his own zone when pinned there, but once he gets the puck, it’s a calm and controlled zone exit to get the puck up the ice. Yandle has great CF numbers, but his CA numbers are average.

Now there is a specific subset of players that don’t put up points, but have great CF and CA numbers. Prior to signing with the Lightning, Anton Stralman was one of these players. When a player has great CF and CA numbers, he excels at the little things in the bullet point list above, but also excels at setting up his team for chances in the offensive zone. Theoretically with more playing time and the right deployment, these players deliver more points. This is especially true for Stralman.

Rate Stats

If you have two players that have similar skill sets, but Player A gets more ice time than Player B, then you expect Player A to have more points. It’s a relatively simple concept, but one that is often misconstrued. Sexy point totals are nice, but ice time can sway any point totals. Just look at Mikkel Boedker.

That’s why rate stats –goals, assist, and points per 60 minutes of ice time— are a better evaluation tool. It evens the playing field for players receiving top line minutes and those receiving third line minutes. With ice time equal you can start evaluating who is a passenger on a team benefiting from big minutes (Boedker), and who is playing beyond their role and may put up sexier numbers with more ice time (Kevin Hayes).

When you combine great CF/CA numbers with great rate stats, you get a potentially great player. Victor Hedman excels at everything listed in this post so far, and it’s clear he’s an elite defenseman. But this is where you can start seeing why players like Shea Weber may currently be viewed as slightly overrated and/or slipping in production from what he once was.

WOWYS – Effect on teammates

The last piece is the effect a player has on his own teammates. The good players are those that have positive impacts in shot attempts –both for and against– while on the ice. Again, all of the little plays mentioned above are accounted for in these numbers. The best teammate is someone who does all these little things effectively, thus creating more chances for and limiting chances against.

A player that goes to the corner, battles, and successfully gets the puck to his teammates is the ultimate teammate. He’s doing the little things to stop the opposition and transition to offense. This is the same type of player that can use his body to protect the puck and draw attention to himself in the offensive zone before dishing to a teammate for a look.

Systems matter – Relative stats

This is the piece that is missing from the majority of fans that use these stats regularly. Hockey is not a cookie cutter sport. What works for one player may not work for another. The most polarizing player for the Rangers is Dan Girardi, and for good reason. Under Tom Renney and John Tortorella, who played conservative defensive zone systems that focused on collapsing low, Girardi was the rock that solidified the defense. Under Alain Vigneault and his hybrid overload/man coverage system, Girardi’s faults were exposed from day one. Systems matter.

Without getting into a huge primer on systems (all laid out here, or just follow Prashanth Iyer), each coach plays a different system, and each system has a different effect on a player’s numbers. A player in a low zone collapse system is expected to have worse CA numbers than a player in a more aggressive overload or man coverage system.

Comparing players within the same system is difficult, but relative stats –comparing teammates to each other– help bridge that gap. These numbers are generally a positive or negative number. A player with positive relative stats compares favorably to his teammates, and may be a better fit for that system. Think of this as the new plus/minus.

Some of this is guesswork, which is where evaluating the skills of the player comes into play. Sticking with Girardi as the example, there’s a chance he may be a serviceable defenseman for a team that does not have a defensive zone system that relies so heavily on skating. A system that relies on shot blocking likely suits his skills better. However the opposite can likely be said for Anton Stralman, who is such a smooth skater that he can disrupt the rush and transition to offense seamlessly.

The tools – Putting it all together

There’s a lot to digest here, and looking at it all may be difficult to understand. Luckily there are some great minds that have made visuals instead of tables to put it all together for you.

First and foremost is Manny Perry (@MannyElk), who owns Corsica Hockey, the replacement. This is where you can view all the rate stats, how a player has progressed/regressed over time, and team stats. 99% of the people listed below use Corsica as the base for all their visuals. Manny’s website is an invaluable resource.

Next is Domenic Galamini (@MimicoHero), who runs Own The Puck. This is where we get our HERO charts from. These charts evaluate one player or compares two players side by side. Here’s an example of how Shea Weber compares to P.K. Subban:

Untitled copy

After reading the above, and then viewing this chart, it’s clear to see that Montreal didn’t get enough in return for Subban. It’s not that Weber is bad. He’s still an elite scorer and shot generator for his team. However he’s not the complete package. He appears to be fading quite terribly in his own end. Meanwhile Subban, four years younger, is the complete package. This is why the trade was laughed at.

Up next Micah Blake McCurdy (@IneffectiveMath), who runs There are so many visuals available it’s incredible, but perhaps the best resource for me is the WOWY chart for each team.

Click to enlarge

Everything is laid out with clear cut definitions. Good/bad sections are clearly marked. Blue and red sections for how that player effects the team are clearly marked. And this is just one level. Micah has these visuals for defense pairings and forward combinations as well. This really drives home the impact of a player on his teammates

Carolyn Wilke (@Classlicity), who manages Today’s Slap Shot, puts together charts like this one:

Like Micah and Domenic, everything is clearly labeled, easy to read, and easy for us colorblind folks to follow. This is just one of the many charts she puts together, and then explains in later tweets. It really drives home the deployment and effectiveness of players. And she regularly tweets these for all 30 NHL teams.

Perhaps the best part about this quintet (Prashanth makes five) is that all five answer questions in a manner that is easy to understand. There are certainly more great minds than these five, but these are the five that I personally rely on. They have provided a wealth of knowledge in bridging the gap between the paper analysis, the systems analysis, the skill analysis, and then tying it all together to give a fair, objective scouting report for teams and players.

This is a 3,000 word answer to a question and request made of me last year. I hope that I have adequately answered the question, and helped drive more discussion about the game, the stats, the systems, and tying it all together. Let’s make hockey great again.

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  • Dave

    That was one tough mathematical problem, took me some time to figure it out!!!!

    LOL…thanks for all the work!

  • Dave – very good of you to put this out there.

    A couple of questions that may seem silly but I just don’t have the knowledge and there are others out there may have the same questions.

    On the Hero Charts:
    There are different shades of blue and sometimes orange compared to blue. Is there some significance to this?

    Where does the following season probability come from and how is it computed? And how is it useful?

    What is top 2,4,6 depth- referring to? I would think defensive pairings but not sure. It shows up in both Production/60 and Possession/60 as well as the probabilities.

    Other questions:
    Who decides if a shot is a high danger scoring chance? It would seem to be pretty subjective and potentially have some bias built in.

    I was watching your twitter debate recently on Girardi’s usefulness and his stats vs. McD. I believe you said that to really understand McD’s you have to look at his time when his was not on the ice with Girardi.

    I understand how you can view the team performance without an individual, but how do you get stats on Player A (McD) when Player B (Girardi) is or is not on the ice?

    Thanks again for taking the time to get into all of this.

    • On the HERO charts the different shades of blue/orange just correspond with how good/bad on of the measures is – higher ratings in any given category come up as blue, and the lower it goes the more orange it gets.

      The following season probabilities are basically the likelihood that a player is played on the top pairing, second pairing, third pairing, or used as depth based on the stats listed in parenthesis as compared to other players’ stats.

      The notches in the bars correspond to top pairing, second pairing, third pairing as compared to stats around the league. I believe the way this is calculated is by regression.

      Shots are designated scoring chances/high danger shots based on location. There’s a set area (looks like a home plate) that counts as a scoring chance, and then shots way in close in the slot are high danger.

      As far as how to tell how a player plays with/without another player on the ice – lines and pairings are more generalizations than strict rules. Guys are swapped in and out based on who’s got fresh legs, who just had abad shift, which opponents are out there, etc. This time spent apart drives the difference in stats when the two players aren’t on ice together. It’s worth checking also when look at a player’s stats without their usual linemates/partner how much time they’ve spent apart. See if it’s substantive, see how much as a percentage of total playing time it is, etc.

      Hope that all helps!

  • Dave, first let me say excellent post.

    I have two problems with all of this. First, there are things which really don’t show up in these stats. The fact that the skeptics don’t give the right examples doesn’t negate this. OTOH, whether such things are common enough to be relevant is less clear.

    I will give one example from a Ranger game this year. An opposing player had the puck around one of the circles and wanted to take a shot. Marc Staal stood in front of him in such a way that Hank could see the shooter but the shooter had a clear shot to Staal’s left. The effect was that the shooter was shooting at the left side of the net and Hank knew that he only had to cover half of the net. Easy save.

    This was only one play and hardly proves Staal is good. I feel certain that these small plays are important in one respect. I am sure that there are Corsi-good players who are so deficient in other matters that good coaches realize they don’t belong in the NHL. However, whether or not they are worthy of consideration when we restrict to the pool of players that actually play is less clear.

    My second concern is a question. Has the validity of these methods been checked statistically recently? Someone here directed me to a study some years back that said that knowing team Corsi for the first 20 or 40 games of the season actually predicted team success over the rest of the season better than team +/-. However, that study occurred in a world in which scoring and preventing goals was the objective. Now though, GMs and coaches and even players are trying to maximize Corsi; that changes the world. Would the previous results still hold?

    I’d like to see a study which ranks organizations according to commitment to new stats and then compares success.

    Finally, your BEST point. If the numbers, any reasonable numbers, tell you something that you don’t want to hear, analyze and listen. The statement “Marc Staal is a top defenseman because he is” doesn’t cut it.

    • To your first point, I think you bring up a good example, but to me at least if a guy is good on stuff like you mentioned but bad on shot counting metrics he’s only doing part of his job. We might disagree as to the relative importance of the former to the latter, or whether one makes up for the other, and that’s fine. Just my two cents, but that’s a good example to bring up, and is also why video analysis is so important (and why I love doing goal breakdowns).

      As far as your second concern goes I would say that scoring and preventing goals is still the primary goal of most GMs and coaches, and maximizing possession is secondary. It’s also worth noting that when we’re talking about possession we’re not talking about the Sedins cycling the puck around with no action – we’re talking about offensive results. One of the reasons Corsi is a valuable stat is because it predicts goals, to the point where sites like Corsica use it to come up with regression based “expected goals” ratings. The usefulness of those stats is a discussion for another day, but suffice to say Corsi is not its own category apart from goals, it’s intimately linked.

      I would imagine, if that same study we’re conducted today then that it would yield similar results. For example, the Pittsburgh Penguins had the second best CF% as a team from the All-Star Game on last year, and they won the Cup. Most of the other teams in the top ten were serious playoff contenders. Each year more and more we see teams with league high CF%s making deep runs into the playoffs. It’s also worth noting that two of the teams who were earliest to commit to analytics were Chicago and LA, both bordering on dynastic at this point. I think you bring up a good point about circumstances dictating a lot of results in terms of these kinds of studies, but I think circumstances have not changed too much over recent years as far as teams and how they approach winning.

      As always, appreciate the honest discourse.

      • I’m not sure you got my second point. Five or ten years ago, Corsi was a very good coincidental indicator which showed how well people were doing their job and it had less sample size error than goal-based stats. However, if you change your approach to maximize Corsi and goals will follow, you risk getting things that are Corsi-good and goal-bad.

        One quick example – shoot the puck, hold it, or pass. All three are correct in different circumstances. Bot shooting is always Corsi-correct. From a player perspective, more shots are in order, not higher quality shots. From a GM perspective, a Yandle-type player is better than a Girardi-type player Corsi-wise always, but this is not always true (not considering these two specific players). Hence a GM can improve his Corsi while hurting his team.

        • But this is under the assumption that coaches and players game the system. They don’t. This is within the confines of the systems used by the coaches, which is why you can’t use Corsi alone as an indicator of talent.

          • It isn’t about just gaming the system. If you value Corsi, you will try to improve it and there is a danger that you will improve it in ways that don’t help or even hurt the team.

            I am drawing no conclusions. What is absolutely true is that the world of 2016 is different than the world of 2010. Consequently, it is important to repeat studies done in 2010 to see if the results are still valid.

          • The whole premise of this is that Corsi isn’t everything. You’re focusing on the wrong thing here Ray.

    • I used Staal as the example because I was one of the last “stats” guys to reconsider my position on him. I was convinced he was better than his numbers suggested. This year is when I really focused on his passing and his play when the puck was on his stick. That’s what made me realize he may not be salvageable.

      • No qualms about using Staal. To be fair though, this year a lot of things highlighted Staal negatively. He was +2 on a superb even strength +/- team and made enough blunders that the eye test also gave him poor grades.

  • Do any of these statistics take into account outliers?

    Like say a dman lets in 7 goals one night. Do we take that into the calc? Is there a measurement to see how tight the stats groupings are?

    • Outliers are taken into account in these kinds of statistics and groupings, but generally even outliers are not so drastic as to throw the whole thing off, at least the way I see it. A guy like Erik Karlsson certainly brings up the average points a top pairing defenseman puts up, but there’s only one Erik Karlsson, so it kind of washes out to a certain extent when you average things all together.

      You bring up a good point though that outliers are important to keep in mind when looking at stats – when a guy’s shooting percentage is 30% for example and the average is something like 8%, you know that he’s unlikely to keep scoring on every third shot he takes. Similarly if a guy puts up a 75% CF% for a game, he’s probably not going to do so next game (although if he’s the real deal, there’s a good chance it’s over 50%).

    • To the second point, the one bad night of allowing seven goals is usually offset over the course of a season by, say going 13 straight games without allowing one. That’s 7 goals in 14 games, or one every other game.

      Our eyes are prone to catching that one big mistake, but missing the smaller, subtle plays or streaks that don’t get publicized that often.

    • Statistics never account for outliers. There is just one important rule of statistics to remember – namely watch out for outliers.

      However, sample size is critical. With small sample sizes, outliers are very far out. With large sample sizes, outliers are not so extreme. The big advantage possession stats have on goal-based stats is exactly the situation you describe. A guy who has a bad night and gives up seven goals is hard pressed to recover from it. when you count shots, the numbers are so much bigger.

  • Dave, are a lot of these stats biased based on zone starts?

    Yandle was a fancy stat darling last season and you said several times that he made anyone he was paired with better. While I agree somewhat with this I still can’t help but believe that everyone of his partners had an uptick in their fancy stats because AV started Yandle in the O-zone far more than anyone else. And therefore whoever he was partnered with had much more favorable zone starts. When you see an increase of O-zone vs D-zone starts aren’t you going to also increase you shot attempts for vs against? Of course DMac is going to look better when paired with Yandle and he starts the majority of the time in the offensive zone.

    This isn’t to rip apart Yandle or anything. I just feel that a lot of these stats can be skewed by how the players are deployed.

    • So zone starts are important but not hugely so – when you compare regular CF% and zone start adjusted CF% for example, they’re different, but not too different.

    • Zone starts play a role, but generally speaking most shifts are started on the fly.

      Yandle’s partners saw an uptick because Yandle is a great defenseman. One of the elite puck carriers in the game.

  • Eddie, Eddie Eddie
    Here is one opinion which is far from yours because you are a reporter and are take logic and throw it out the window like most media people. You repeat lies and believe it for real. Real is not what you stand for but make believe. You are a Democrat so that is the reason you lie and belittle good and great players and call them B liners.
    Dominic Moore says that in his opinion, Kreider is the most “explosive skater in the history of the NHL” (

    Moore said that Kreider is a “game-changer” and can do “amazing things” because he is a “freak athlete.” (

    He added that guys like Kreider “don’t grow on trees” and that he has become a “valuable player in the league.” (

    Who am I to believe me or your lieing eyes? Kreider is great though you don’t believe it. You belittle great players and defend shitty coaches.

    An example of your logic, you are mad the way the coach handled the Hays benching. The problem was other players were playing worse than Hays and he benches Hays. G and Stahl were playing much worse than Hays and he benches the young guy.
    Kreider is a game changer and finally someone finally recognizes that and its not the coach. You can’t recognize it because you are too busy defending incompetence. Incompetence is indefensible. The coach sucked even with hurt players he was unable to adjust.

    • Underscore – Dude in general I try to avoid being judgemental although at times I struggle.

      In this case though it’s clear your post is way out of line for this forum.

      I hope you have a better day tomorrow.

      • Yes I was drinking yesterday. I still agree with what I said, but some things should not be said. Should I apologize or keep silent like the coach and not have any consequence for the presumed error? If I continue to make such presumed errors for an entire season, would I still be able to post here? Though you think I am crazy I have been right about the coach for approx 3 seasons (my opinion) and my record is amazing. Why not tolerate and ignore so many of my presumed mistakes? Would you do that for me?
        Like wise I try not to be judgmental, but for some reason in Hockey and politics and religion and the medical industries, I struggle mightily.
        No I am not above the rules like AV. From now on I will have a 2 drink maximum for posting. I am sorry for bringing politics into the conversation. We have enough Hockey politics to deal with. I don’t want anyone calling Eddie, Lying Eddie.
        By the way what part bothered you? The statement about the lying media or that I made a blanket statement about the media? Or was it that I assumed Eddie was a Democrat? Or the part where I said Eddie lies and belittle good and great players and call them B liners? Is that what I do with Leopold?
        This is what Eddie said;
        These guys are good young players, but they have done nothing to prove they are great. Your definition of great needs a little work I think. Other than Hank, we have no great players at the moment. We have good players. You may disagree, but then I think you owe it to everyone to explain who you think is “great” and what your definition of “great” is. Certainly, based on what we’ve seen and heard in trade rumors, few if any talent evaluators think our players are “great”. I suggest you heed the words of Bill Parcells….”you are what your record says you are”. So who has a “great record”? The coach, the goalie, and an argument can be made for Nash, (but not recently). That’s it. Who is great beyond that?
        So I wanted to shove back at the comment that Eddie the great talent evaluator had by belittling our players.
        The only reason we made it to the finals was because of the coach and I see it the other way around.
        If Eddie was right we should make back to the finals but the players quit on the coach because the coach quit on them by playing inferior players in wrong positions like Fast and one inept player named Glass and many more defensive mistakes.

        • What pisses me off is that you pass your opinion off as fact.

          The player quit on AV because he quit on them. They were pissed off because of who played on a nightly basis?

          That’s your opinion and there is zero evidence that any of the players feel the same way.

          • Thank you for your reply.
            I never posted anything as fact. Fact is in the math. I judge human character as poorly as everyone else. I thought the players gave up on AV. I assumed no one would say otherwise.
            I was displaying my evidence about Eddie saying we only have B-liners by what Moore said about Kreider. But it still is not fact. Perception is in the eye of the beholder and thats why we disagree. No one here has the only fact. Some comments said by players may not be honest because no one wants to look disgruntled in the lying media. No one wants to look like TO. Yet he was honest. Who is going to say I don’t want to play on Glasses line because he only plays 5 minutes?

    • Underscore – first and final warning. I don’t tolerate this. Not only because you provoked, but because you also copy/pasted an entire post from a separate website.

      Don’t do that.

  • Underscore – It’s not my blog but this is how I see it.

    Everyone is free to express their own opinion and disagree with other’s opinions in constructive debate like fashion. The back and forth point/counterpoint debate that goes on is what makes the blog work.

    We are all NY Ranger fans, we all bleed blue, and we all want the team to win the Cup every year. But we all have a different view of how that should be attained. Thanks to Dave and his merry band of bloggers this forum gives us each a chance to be Glen Sather and Jeff Gorton every day.

    I certainly don’t agree with many of the blog posts that are released nor with the way they are presented. But again – The BSB staff are the ones taking the time to put all this content together and we should all be respectful of that. I can’t imagine the time it took Dave to pull together this Analytics post in particular.

    Awhile back, A certain post caught me the wrong way and I said something about it. Should I have done it? Maybe/maybe not or perhaps in a different way. Point it is – I said it – and once it hits the internet it doesn’t go away.

    I am a “call them as you see them” kind of guy myself. Because of that I typically try to restrain myself in forums such as these because it just makes more sense to.

    I am not the BSB Police by any means. There is certainly some stuff that I have read here that I thought was inappropriate, but it is not my place to say so. So it was rather untypical of me to comment on your post yesterday. And I probably shouldn’t have.

    That being said, I read it and felt very upset by the overall slant and tone of it – the blatant accusation that was made and then made again by bringing politics into it. In my own humble opinion, that kind of stuff has no place here and I said so.

    I enjoy interacting with the group here because very hockey knowledgeable and passionate NYR fans are the participants. But at the same time it is not so pretentious as to not be able to poke fun at someone because of their opinion. I read some other blogs and can’t believe what people say and I hope that the BSB never gets there.

    So Underscore, Walt, Fotiu, Dr Paul, Merchant Sal, Ray, Mikeyyyyy, Amy, Chis, Hatrick, Spozo, Eddie, et al – let’s move on to another day of healthy debate and not so subtle digs with and at each other.

    You asked and I answered – I consider what happened to be between you and Eddie.

    Enough said…..

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