Ideas for Future Studies

[Czech Your Math]

Colorado had a 77 PPO disparity between Philadelphia in both team's home games.
65 disparity on the road.

Overall? 7 of the top 10 PPO teams were playoff teams. And 11 of the top 15.

I'd highly dispute that actually.

A more interesting point would be to look into the trend of Carolina leading the league (or close to) in opportunities per year. This year was the only time they were not top 3 in the league since 01-02.

IDK why Carolina has been near the top although they have not been to the playoffs much lately.

I'm not sure when the effect I was talking about disappeared, but it was prevalent into the 90s at least.

 

[Czech Your Math]

I had an idea of a measure allocating points to a player for his team's wins/losses based on his time on ice.

These are some issues with the measure:
- treatment of OT/shootout
- offensive players usually have lower TOI in wins than in losses
- doesn't consider magnitude of wins/losses (by how many goals). Could add a factor
- can't be quickly calculated. Could approximate with average TOI

I am not sure if this measure already exists or if it would give meaningful results.

Have you looked at GVT? See the "All-in-one metric" thread in this forum for a link. It's quite complicated, so it takes some time to understand. I think if you're going to use TOI, it should be done more similar to the methods in GVT. If TOI by situation is available by player, I would take it a step further than GVT, and use situational TOI to calculate player shares that credit players for success in each situation for the entire season.

As far as shootouts, GVT also addresses it. I haven't looked at those calculations, because to me it's an artificial part of the game, so I stubbornly choose to ignore it.

 

[Mayor Bee]

I have an idea for one.

Bill James once looked at Hall of Famers in baseball as expressed by number of at-bats taken in a given year by a future HOFer. The purpose was to point out that the 1925-1935 players had about twice the number of HOFers as they should, but it might have value as an expression of overall caliber of play.

Specifically in hockey, I was wondering if using shots on goal by HOFers in place of at-bats might have some value. Admittedly, this wouldn't be available until 1967-68 and thus is self-limiting, but there might be something to derive from it. Specifically, it may be able to address the idea of how quickly "talent dilution" is alleviated in a post-expansion period.

Thoughts?

 

[TheDevilMadeMe]

I have an idea for one.

Bill James once looked at Hall of Famers in baseball as expressed by number of at-bats taken in a given year by a future HOFer. The purpose was to point out that the 1925-1935 players had about twice the number of HOFers as they should, but it might have value as an expression of overall caliber of play.

Specifically in hockey, I was wondering if using shots on goal by HOFers in place of at-bats might have some value. Admittedly, this wouldn't be available until 1967-68 and thus is self-limiting, but there might be something to derive from it. Specifically, it may be able to address the idea of how quickly "talent dilution" is alleviated in a post-expansion period.

Thoughts?

I'm not sure I understand what you are saying, but wouldn't ice time be a closer analogy to times at bat?

 

[Mayor Bee]

I'm not sure I understand what you are saying, but wouldn't ice time be a closer analogy to times at bat?

In James' case, it was expressed as percentage of leaguewide at-bats taken by HOFers. In any given year, it was around 10% of total at-bats that were taken by HOFers, with a massive upward tick in the 1925-34 time frame.

I think ice time would be too limiting, since we'd only be able to look at the last 13 years.

 

[Hockey Duckie]

On HFBoards, there are two commonly accepted theories that are seemingly at odds with each other:

--Elite players produce on their own, regardless of talent, and;

--Players produce more with a (relatively) better supporting cast.

An interesting study would involve looking at "elite players" and just how much their fellow teammates factored into their production, and in turn, how much said players factored into their teammates production.

Perhaps an indicator of an elite player is not how much he and he alone produces, but how much he is able to increase the production of his teammates.

(If this is all a blinding flash of the obvious, then please forgive me)

I did do some research on scoring for the Anaheim Ducks from 2008 - 2011 in depth and added in a few stats from 2006/07 and 2007/08. Click here for the article I wrote up.

In that study, the top 7 Duck scorers from 2006 - 2011 have consistently score 62% or more of the total team's output. The actual scoring output does differ, but the rate of scoring from the top 7 remains at 62% or higher. The roster does change throughout the years, but it's this team's top 7 scoring output that remains the same. Usually, your top 7 often are part of the PP unit. The Ducks have had the same coach for all those years, with exception of the last year where they fired their coach early into the season. With that said, the top 7 scorers still carried 62.5% of the scoring load of the team.

Note, this stat only covers the Ducks.

If you like that article here's another stat frenzied article I wrote up:
1. Obstruction, the Power Play, and Lack of Scoring...
It's a look at how PPO's have dropped drastically and, again, looks at the Ducks' production at the same time.

 

[Czech Your Math]

In James' case, it was expressed as percentage of leaguewide at-bats taken by HOFers. In any given year, it was around 10% of total at-bats that were taken by HOFers, with a massive upward tick in the 1925-34 time frame.

I think ice time would be too limiting, since we'd only be able to look at the last 13 years.

You could use goals, points, TGF, TGF+TGA, etc. for forwards, and games, wins, minutes, etc. for goalies. Defensemen are generally the most difficult for which to find a proper metric.

Te reason for the big uptick in baseball HOFers was the surge in offense in the Roaring 20s. Batters got great stats and pitchers could still pile up wins, even if their ERAs suffered.

An equivalent time would be the 70s and especially 80s in the NHL. They had both dynasties and a surge in offense. Goalies seem to have tougher standards and d-men aren't judged so much on offense, so they are much less affected I would guess.

The difference is that baseball kept the number of teams static for a long period, while hockey expanded rapidly during the late 60s and 70s, which will complicate things on a % of players basis.

 

[Czech Your Math]

In that study, the top 7 Duck scorers from 2006 - 2011 have consistently score 62% or more of the total team's output. The actual scoring output does differ, but the rate of scoring from the top 7 remains at 62% or higher. The roster does change throughout the years, but it's this team's top 7 scoring output that remains the same. Usually, your top 7 often are part of the PP unit. The Ducks have had the same coach for all those years, with exception of the last year where they fired their coach early into the season. With that said, the top 7 scorers still carried 62.5% of the scoring load of the team.

Note, this stat only covers the Ducks.

If you like that article here's another stat frenzied article I wrote up:
1. Obstruction, the Power Play, and Lack of Scoring...
It's a look at how PPO's have dropped drastically and, again, looks at the Ducks' production at the same time.

That is rather consistent, but I would think it could vary from team to team, although it may not be unusual for a team to have a relatively fixed % of offense by its top X players. I've done some work on league scoring by tiers (top 30, #31-60... #331-360 in a 30 team league). You can find a couple graphs at the end of my "Improving Adjusted Scoring" thread.

Why does the league not consistently enforce its own rules? From what I can tell, the league should expand in the near future, due to talent compression from lack of team expansion. That might help scoring slightly in the short term, but a better solution might be to reduce the size of goalie pads and enforce the rules fairly.

 

[Mayor Bee]

You could use goals, points, TGF, TGF+TGA, etc. for forwards, and games, wins, minutes, etc. for goalies. Defensemen are generally the most difficult for which to find a proper metric.

I guess it would depend on what the purpose was.

Te reason for the big uptick in baseball HOFers was the surge in offense in the Roaring 20s. Batters got great stats and pitchers could still pile up wins, even if their ERAs suffered.

An equivalent time would be the 70s and especially 80s in the NHL. They had both dynasties and a surge in offense. Goalies seem to have tougher standards and d-men aren't judged so much on offense, so they are much less affected I would guess.

James' theory, which I believe to be accurate, is that the huge number of players from that era was a structural one. Players from that era were on the early ballots for the BBWAA to select them that way, and then years later they also had the Veterans Committee have a crack at them. It just happened that the Veterans Committee of the 1970s was largely stocked with players and writers who came of age in the 1920s and 1930s, and thus had these warm and fuzzy memories of their youth. In addition, the MacMillan Encyclopedia had come out in 1969, so now there were weak statistical arguments to go with it.

Basically, it would be Frankie Frisch leafing through it and saying, "Look, this guy hit .356 and had home runs to go with it! I don't see the modern ballplayer doing that!"

The difference is that baseball kept the number of teams static for a long period, while hockey expanded rapidly during the late 60s and 70s, which will complicate things on a % of players basis.

The periods I'd be most intrigued by would be 1979-80 to 1990-91, mostly because I'm curious to see how long it took everything to kind of normalize. Or maybe it didn't at all.

 

[CC321]

Here is a simple one. Compare giveaways to points produced, to measure a players puck handling efficiency. Assuming giveaways are related to how often a player handles the puck and how risky his behavior is with it, player A with 70 giveaways to 50 pts (70/50 1.4) is a worse puck handler than player B with 30 GvA to 50 pts (30/50 0.6 = more efficient).

 

[Czech Your Math]

I guess it would depend on what the purpose was.

Certainly, the point is that there are ways to measure the effect. Even using games played would work pretty well.

James' theory, which I believe to be accurate, is that the huge number of players from that era was a structural one. Players from that era were on the early ballots for the BBWAA to select them that way, and then years later they also had the Veterans Committee have a crack at them. It just happened that the Veterans Committee of the 1970s was largely stocked with players and writers who came of age in the 1920s and 1930s, and thus had these warm and fuzzy memories of their youth. In addition, the MacMillan Encyclopedia had come out in 1969, so now there were weak statistical arguments to go with it.

Basically, it would be Frankie Frisch leafing through it and saying, "Look, this guy hit .356 and had home runs to go with it! I don't see the modern ballplayer doing that!"

I had forgotten about the timing aspect, that's very important as well.

The periods I'd be most intrigued by would be 1979-80 to 1990-91, mostly because I'm curious to see how long it took everything to kind of normalize. Or maybe it didn't at all.

Who's to say what's normal? It's always changing. I think it would be better to look at a longer period and let the evidence speak for itself. You can then refine your analysis based on what you have learned to that point about the effect you are studying.

 

[Hivemind]

Here is a simple one. Compare giveaways to points produced, to measure a players puck handling efficiency. Assuming giveaways are related to how often a player handles the puck and how risky his behavior is with it, player A with 70 giveaways to 50 pts (70/50 1.4) is a worse puck handler than player B with 30 GvA to 50 pts (30/50 0.6 = more efficient).

I like the general thought behind this, but giveaway tracking is far too subjective and inconsistent for that stat to have any real merit at this point.

 

[Hockey Duckie]

That is rather consistent, but I would think it could vary from team to team, although it may not be unusual for a team to have a relatively fixed % of offense by its top X players. I've done some work on league scoring by tiers (top 30, #31-60... #331-360 in a 30 team league). You can find a couple graphs at the end of my "Improving Adjusted Scoring" thread.

Why does the league not consistently enforce its own rules? From what I can tell, the league should expand in the near future, due to talent compression from lack of team expansion. That might help scoring slightly in the short term, but a better solution might be to reduce the size of goalie pads and enforce the rules fairly.

One reason why the league doesn't enforce rules could be stoppage time. May be they thought there were too many penalties called that ruined the ebb and flow of the game. Although, in the article, it revealed there are much less infractions being called today than there was being called pre-lockout year, about 2000 less calls. In 2011-12 season there were 8,132 Power Play Opportunities (PPO). While in 2003-03 season, there were 10,425 PPO. So maybe it could be something else altogether.

Scoring is down because PPO are down considerably. The goalie pads don't matter if the refs aren't letting players play without obstruction. If they speed the game up, then there are less chances of head shots. When you limit the ice size so players can't utilize their speed, then speed doesn't become an issue and one becomes a sitting duck more often than not.

Anyhow, try not to mistake the argument of huge goalie pads the reason for lack of scoring. I've heard that argument with JS Giguere during the 2002-03 cup run as a Duck. Funny thing is the following year JS' skill wasn't up to par that year with those same pads. Since then, there was never an issue with JS and his pads. Goalies can be great from time to time.

 

[Jumptheshark]

I think one think that could be usefull and fun is looking at say the last 15 years of drafting per team to see who has been the most successful at the draft table.

I think the bench marks would be for the players drafted
- Total games played
- Goals, assists and pts
- Wins. loses and shutouts bu goalies
- Looking how many draft picks teams had to get the above stats

any other ideas

 

[Zombie Mike Murphy]

I think one think that could be usefull and fun is looking at say the last 15 years of drafting per team to see who has been the most successful at the draft table.

I think the bench marks would be for the players drafted
- Total games played
- Goals, assists and pts
- Wins. loses and shutouts bu goalies
- Looking how many draft picks teams had to get the above stats

any other ideas

Sounds like a good one - I might even step up to the plate on that one.

Would probably also be good to break it down by which ones produced for their team, versus the ones that were traded as prospects.

 

[SaskRinkRat]

I have a couple of ideas that I think are a ways off given the type of data that is currently [not] available:

1) Dump and chase vs. puck possession. This is a constant debate, particularly among people interested in the tactical side of the game. The puck possession side thinks the dump and chase side is crazy because "why would you give the other team the puck when you know that having the puck is the main predictor of net goal production?" The dump and chase side says "I agree, that's why we dump and chase, because we can get it in the zone and go get it rather than turn it over at the blueline."

2) Relative likelihood of a goal being scored based on where the puck is on the ice and which team has possession. I feel like this type of analysis could provide a really solid foundation for more "in the moment" analysis. The idea would be to figure out, given where the puck is on the ice and which team has possession, what is the likelihood of the ensuing play resulting in a goal (both for and against the team with possession).

3) Building on #2, player proficiency at advancing the puck into areas more advantageous to his team (i.e., more likely to result in a goal for, less likely to result in a goal against). I think this would be the ultimate individual metric: can you make it more likely your team will score and / or less likely the other team will score.

 

[Czech Your Math]

I have a couple of ideas that I think are a ways off given the type of data that is currently [not] available:

1) Dump and chase vs. puck possession. This is a constant debate, particularly among people interested in the tactical side of the game. The puck possession side thinks the dump and chase side is crazy because "why would you give the other team the puck when you know that having the puck is the main predictor of net goal production?" The dump and chase side says "I agree, that's why we dump and chase, because we can get it in the zone and go get it rather than turn it over at the blueline."

2) Relative likelihood of a goal being scored based on where the puck is on the ice and which team has possession. I feel like this type of analysis could provide a really solid foundation for more "in the moment" analysis. The idea would be to figure out, given where the puck is on the ice and which team has possession, what is the likelihood of the ensuing play resulting in a goal (both for and against the team with possession).

3) Building on #2, player proficiency at advancing the puck into areas more advantageous to his team (i.e., more likely to result in a goal for, less likely to result in a goal against). I think this would be the ultimate individual metric: can you make it more likely your team will score and / or less likely the other team will score.

Interesting ideas.

Like you say, #1 is difficult to quantify. I think it makes sense for a team to dump and chase if they have inferior or perhaps equal players on the ice as their opponents, or have players particularly suited to that type of game. If they have skill players on the ice, then I don't like it much as a constant strategy.

It's still difficult to quantify #2, since the positions and quality of various players on the ice come into play. Still, I see the parallel to baseball, where such situational expectations are measured more easily. For instance, runners on first and third with one out is the initial situation, and has an run expectation of X, and after a player's at bat there is a run scored and runner on first and second with one out, which has a run expectation of Y. So the net run effect is (Y + 1 - X).

 

[Gobias Industries]

I think one think that could be usefull and fun is looking at say the last 15 years of drafting per team to see who has been the most successful at the draft table.

I think the bench marks would be for the players drafted
- Total games played
- Goals, assists and pts
- Wins. loses and shutouts bu goalies
- Looking how many draft picks teams had to get the above stats

any other ideas

I'll work on the Bruins now...Anyone else want to get in on this, with a 1979 start year?..

I'm also going to break down points with team vs. points with other teams and how many were traded...

 

[hawksfan50]

There are lots of stats the NHL could provide over and above those it does show on its website...


Certainly I'd like to see a "splits" points tracking for each player and in relation to his position and ranking both in absloute terms and in ranking relative to TOI ...Also broken down for ES, PK, and PP --and all this shown in graph/chart form so you can see instantly the progression or regression over a whole season...the splits could be
for 11 segments of 7 games each plus a final 5 game segment or 8 segments of 10 games each plus a final 2 game segment that won't provide much meaning or 7 segments of 10 games each plus a final stretch segment of the last 12 games played by that player in the reg. season.
Injuries and consequent missed games obviously could effect the comparisons but and skew some of the time segments due to none or less games played in those segments ..

BUT assuming a player did not get injured or missed only a few games in a segment or two ,you could get valueable information on how a player trended through a season ..

FOR instance --take my pet peeve of last season Patrick Kane--we all know he regresssed in total points (just 66) but it would be interesting seeing his "splits" over the course of the 82 games he played...MY hunch was that he started off ahead of point a game pace for a time (about the first 15 games or so,slacked off badly till about the end of February,then picked up a bit more scoring pace at the end...SO it would be interesting to see what actually happened in say each 10 game split (say we go with the 7 ten game splits and a final 12 game segment model )...
This would SHOW what happened with hm over the course of a season and you could see it clearly if shown say in bar chart form....YOU might compare to prior seasons again showing splits for each with diferent coloured bars and maybe some pattern emerges -or if not that too could be useful information for coaching staff to evaluate... IF these are compared to league averages for his POSITION or to say just the top 30 scorers at forward ---those too would be further valueable info in assessing his season ...For instance if his pattern showed so much difference from the league average for the position or from the top 30 forwardscorers -then very valuable information is revealed ...if--barring injury reasons that effected the pattern, there is some big skew off from the top positional scorerrs or top 30 forward scorers in a certain players pattern THEN perhaps coaches could make adjustments in pattern scorings dips negative to those pattern averages for a certain segment or segments in a season.
ALSO you could adjust these charts for TOI to see if that would make any difference .. You could also do all this not just for total points scored by segment by that player but also tracking multi-point games per segment.

Agaim my perception was that Kane had very few multi-points games last year -it wan mostly one point and out type games with just a few eexceptions... WAS this off from his pattern of prior years? Which segments had more multi-points and is there a pattern over several years or is strength of opponent's in a segment more determinative for this ..

So with such deeper info tracking and analysis perhaps important patterns are revealed and certainly you could perhaps make stronger conclusions about a player and changes (good or bad) in his game both relative to others and to himself of prior years...


Is there any consistent pattern during a season or where is he trending and is there some huge change over prior years?

So IF a player say shows consistent pattern of more multi-point games
in the first 2 and last 2 segments and if that pattern is different from the "normal" average for his position or for the top 30 forward scorers in the league (29 if that player is a top 30 scorer himself)---THEN the coaches would use that info to try to get the player on the more "normal" track against the peer group he is measured against..

Perhaps some interesting segmental patterns willbe revealed ..For instance (no saying it is true) but what if the normal average pattern of multi-points fromthe top 30 forward scorers is a consistent level of multi-points scoring accross all the segmenets over a season,but your player skewed his multi-point games heavily at the beginnig and ending portions of the season....then as a coach you would ant to get him to be more "normal" in multi-point games consistency over segments..
IF "fall -off" in multi-points games becomes a pattern in the middle 5 ten gamesegments each season THEN that player must correct this else as a coach you have to reduce his TOI in those middle 5 segments of ten games each because your player just has proven he won't be as effective in those segmentsas in earlier or later segments.. BUT you have to also see if the fall-off pattern in the middle portion of the season was becaue you reduced that player's TOI -if not there is some other cause to his pattern over the seasons (assuming there is such a pattern) ..

Anyway all this is valueable information for both coaches AND for fans ..

We have been toold for years that after the all-star break,certainly after the trade deadline ,down the home stretch games get more competitive as teams jockey for playoff positions...so we intuitively expect tighter defenses ,less scoring and less multi-points games by players ..BUT if a player bucks that exectation but does score at a faster pace again and with more multi=pont efforts AND also did that to start the year in the eraliest segments of the season -you wonder how could such player slack off the scoring and multi-points games in the middle portion segments say from mid-nov till the all-star break when presumably opposing defenses in games should slack off -that should be the time "offensive players" do most damage in scoring because this segment of the season SHOULD be the expected "easy' part where defenses are playing less meaningfull games (to start the year there should be enthusiastic energy and desire to get off to good starts and pile up a lead in points in the standings--then as the 2nd quarter arives you get settled into "routine" games where you are just punching the clock in another city ,anoter game to clear off the schedule,then looking forward to Christmas break ,then after that more routine "grind" till theall-star break, only afterwards of the all-star breal is it supposed to get more tight and contested as teams try to hold playoffs spots and get the advantage in those spots ...so IF an offensive player cannot take advantage of this long stretch of games from mid-nov. till the all-star break or till the trade deadline to elevate his scoring pace again sat less contesting defenses (on average) -there is something dradtically wrong with such a player...IT SHOULD be easier to score in that long stretch of routine games..IF he slacks off then instead but ups his pace again when the games get harder in March and April ,then it is clear that it is not ability that was slacking in the middle portion of the season,but rather simply motivation and will (ie. effort)... IF this is indeed a pattern with such player,then no caoach can live with that ..for a player not perforoming to his ability when it should be easier ,is a double slap in the face to his team..
If he instead showed up more in this period,then that should help get more scoring and more wins..

SO i) is there such a persistent year to year pattern of teams slacking off defensively in the 2nd and 3rd quaters of the season? ii) Is there a consistent prior or a recent change of pattern in a player such that his scoring and multi-point contribution has gotten worse precisely when you expect it least (IF there is a defensive falling -off in the 2nd and 3rd quater of seasons or 4-5 middle segments of ten games each during a season? iii) IF so -what can be done to get such player to perform to his ability in a time we expect scoring to come easier?

Whether my intuition about middle portion of the season defensive slack-off and offensive highest scoring on average is true or false --I do not know ...I do know that last year Pat Kane was ahead of a point a game pace tillabout mid-November then started regressing down below PPG pace only picking it up again late down into the home stretch ...SO IF the middle parts of the season should be the easiest parts to score in -he certainly took no advantage of that easier opportunity to score...Is this just a 1 year aberration? Did it happen to the average of his peers by position or to the top 30 scorers in the league too? Was last year an aberration just for kane or was there some big change going on league-wide that effected the pace of scoring and multipoints to significantly lower them for almost everyone -if so we can criticize Kane less,if not he should be criticized even more for his slack-off in that portion if the season last year...

TO get such prper critical analysis,we need better data than we currently get from the NHL -they SHOULD be providing this more detailed segmental scoring data for each player and in the leaders by position or in te overall top 30 scoring inthe league.

 

[SaskRinkRat]

Interesting ideas.

Like you say, #1 is difficult to quantify. I think it makes sense for a team to dump and chase if they have inferior or perhaps equal players on the ice as their opponents, or have players particularly suited to that type of game. If they have skill players on the ice, then I don't like it much as a constant strategy.

It's still difficult to quantify #2, since the positions and quality of various players on the ice come into play. Still, I see the parallel to baseball, where such situational expectations are measured more easily. For instance, runners on first and third with one out is the initial situation, and has an run expectation of X, and after a player's at bat there is a run scored and runner on first and second with one out, which has a run expectation of Y. So the net run effect is (Y + 1 - X).

These are good comments. Thanks for responding.

The reason that I give the dump and chase guys a bit of the benefit of the doubt is because it seems that they wouldn't do it if they thought it meant they were less likely to retain possession. The logic behind it seems to be that you give up possession now (i.e., this second) to increase your chances of having possession later (i.e., 5 seconds from now). I think it would be really interesting to test this theory. The research question would be something like: "Given a player has possession between the red line and the opposition blue line, is his team more likely to have the puck 5-7 seconds later if he dumps it in to the opposing zone, or tries to make a move, pass, etc?"

I think quantifying #2 would be much easier if there were some sort of optical tracking system in place (i.e., sensors in player jerseys and in the puck). I think that would be a revolutionary statistic.

 

[Czech Your Math]

The reason that I give the dump and chase guys a bit of the benefit of the doubt is because it seems that they wouldn't do it if they thought it meant they were less likely to retain possession. The logic behind it seems to be that you give up possession now (i.e., this second) to increase your chances of having possession later (i.e., 5 seconds from now). I think it would be really interesting to test this theory. The research question would be something like: "Given a player has possession between the red line and the opposition blue line, is his team more likely to have the puck 5-7 seconds later if he dumps it in to the opposing zone, or tries to make a move, pass, etc?"

I think quantifying #2 would be much easier if there were some sort of optical tracking system in place (i.e., sensors in player jerseys and in the puck). I think that would be a revolutionary statistic.

It certainly would be helped by more advanced ways of measuring such things.

The D&C players may be more likely to retain possession, but does that mean they are more effective or better players? I guess it depends, partially on what the goal is for each line.

This relates to something I was just thinking about as an extreme example. TB was criticized for basically stalling at times. Why is this not a viable strategy and how can it reasonably be prevented? For instance, let's say a team has 1-2 very good lines, and a couple stinkers. Why not just stall with the weak lines until the good lines are rested? This is essentially what checking lines and lower lines often do by dump and chase and grinding along the boards. They are (or probably should be in many cases) trying to negate the other teams' good lines and waste time, not so much try to create large advantages which may not be that valuable with their limited skill.

 

[seventieslord]

I think one think that could be usefull and fun is looking at say the last 15 years of drafting per team to see who has been the most successful at the draft table.

I think the bench marks would be for the players drafted
- Total games played
- Goals, assists and pts
- Wins. loses and shutouts bu goalies
- Looking how many draft picks teams had to get the above stats

any other ideas

I'll work on the Bruins now...Anyone else want to get in on this, with a 1979 start year?..

I'm also going to break down points with team vs. points with other teams and how many were traded...

Already done, and it took me over a year. It's also more nuanced than just looking at point totals. I just need to organize the results.

 

[Shrimper]

Tempted to look at the spending efficiency of teams (i.e Who got the most for their money) over the past 5 years. I'd look at the player history and their pts/$m.

What other stats should I look at to get a good picture.

 

[Czech Your Math]

I tried to do a study on consistency, deducting the player's top X% of performances against single teams (e.g. all of Mike's games vs. Columbus, Toronto, Winnipeg and Islanders) or his best X% of games and measuring the % of his overall PPG he maintained in the remaining games. I think it's biased for players with a higher PPG. Anyone have a better idea for a more unbiased metric?

 

[Czech Your Math]

I'm looking for any studies of value or total number of players by age.

The more comprehensive (by position, various metrics, etc.) and more historical, the better.