EHM The Blue Line

I can understand that customization not being a priority for the first release of the game but I think that the progression/development and aging might be a smart thing to implement right away. Forwards tend not to play as long as defense and goalies. Defensemen take longer to develop or reach their peak than forwards and goalies take longer than both of them. I think this would really add a level of authenticity to the game. Of course, some players might not stick to this. You might have a goalie that develops quickly or a forward that plays a very long career. Still, it would be nice to have these as a general guideline more than a rule.

Of course we will consider the fact that players playing different positions generally peak at different ages, but making it customizable is another thing.

dabo wrote:Of course we will consider the fact that players playing different positions generally peak at different ages, but making it customizable is another thing.

well just consider it or have it in the back of your mind. For playing past years, say early 1950s or before players develop and progress much differently then they do now. That would be one major use for something like that. OOTP has now made those figures all dynamically changing through league history (fyi) and it just opens up alot of opportunitys and scenarios especially if you are starting leagues before 2010 (if that is even in your game..)


These are just the type of things that add so much more to these games, making things change every few years to decades.

Offtopic: Something like average salaries changing would be great too. Having a screen that shows each teams average salary along with the League Average salary..with a screen showing a breakdown of the avg salary per season. All these things make your hockey worlds feel real and just add tons of depth.

I don't know if this can be implemented but something that might be interesting might be random progression from players and random regression. A good example would be Derek Armstrong who was a career mionor leaguer before breaking out a 29 and becoming a solid NHLer for much of his 30's. Or regression could be Nils Ekman who at 31 just washed up very quickly after a 55 point season. Random occurances like that can create challenges with regards to now overpqaid contracts or surprise assets. In the same vein EHM had few players like Gustavsson, Leino, or Hiller undrafted guys who developed in Europe to be prized UFA.

I agree with HoldenC as that is something I really want to see represented in the game. I'm not sure what would be the best way to implement it though.

Late bloomers will be in and perhaps we could add "early regression" too. Dunno what a proper name for that would be though.

Early peak maybe?

Good point on the "regression". Look at Cheechoo. Sure, a lot of his success was due to playing with Thornton but he went from being a 50 goal scorer to... what is he doing now? He's not even playing in the NHL, is he?

Yup, he got 28 points in the AHL last year...

I'm elated to see that somebody's decided to take up the daunting task of developing a hockey manager from scratch, and you have my appreciation for it. Anyway, here's my two cents on the matter (WARNING: WALL OF TEXT):

One thing that always irked me about EHM 2007 was that development/regression was very linear and unrealistic (players would mostly peak around age 20-21 while they would only experience a very sharp skating regression around age 39-40). Add to this the fact that most attributes progressed at the same time (especially technical attributes), when it happened. Of course, this kind of development path is the exception, not the rule.

DEVELOPMENT: My idea would be to create a "Bell curve" regarding this, with the average age of a player reaching his "plateau" being around 24-26 (although the case could be made for earlier development peaks for wingers [early 20s] while it being later for defensemen and goaltenders [late 20's]) with the extreme fringes of development ranging from late teens to early thirties. Don't know how feasible it would be to develop a hidden attribute for individual development speed, but I would suggest something like a 1-20 rating for it (possibly affected by outside influences such as coaching, mental attributes, injuries, etc.).

1 (EXTREMELY RARE) - Player reaches peak development at age 15-16

2-3 (VERY RARE) - Player reaches peak development at age 17-19 (ex. Jason Bonsignore, Scott Scissons, [speculative] Angelo Esposito, etc.)

4-5 (RARE) - Player reaches peak development at age 20-22 (ex. Jim Carey, Jimmy Carson, Dino Ciccarelli, Dion Phaneuf, etc.)

6-8 (SOMEWHAT COMMON) - Player reaches peak development at age 22-24 (ex. Teemu Selanne, Jaromir Jagr, Kevin Lowe, Mark Recchi, Henrik Lundqvist, etc.)

9-12 (VERY COMMON) - Player reaches peak development at age 23-26 (ex. Joe Mullen, Kevin Stevens, Rob Blake, Danny Briere, etc.)

13-15 (SOMEWHAT COMMON) - Player reaches peak development at age 25-27 (ex. Pavel Datsyuk, Marc Savard, Zdeno Chara, Ryan Miller, etc.)

16-17 (RARE) - Player reaches peak development at age 28-30 (ex. Martin St. Louis, Andy McDonald, Johan Franzen, Dominik Hasek, etc.)

18-19 (VERY RARE) - Player reaches peak development at age 30-32 (ex. Jason Blake, Tomas Holmstrom, Mark Streit, Dwayne Roloson, etc.)

20 (EXTREMELY RARE) - Player reaches peak development at age 32-34 (ex. Tim Thomas)

REGRESSION: Like development, there should be a hidden attribute (1-20 range) for career longetivity, which can also be influenced by mental attributes, injuries, etc.

1 (EXTREMELY RARE) - Player begins skill atrophy at age 22-25 (ex. Jim Carey)

2-3 (VERY RARE) - Player begins skill atrophy at 25-28 (ex. Blaine Lacher, Jonathan Cheechoo, Jimmy Carson, etc.)

4-5 (RARE) - Player begins skill atrophy at age 28-30 (ex. Sami Kapanen, Brian Savage, Jeff O'Neill, etc.)

6-8 (SOMEWHAT COMMON) - Player begins skill atrophy at age 30-32 (ex. Dale Hawerchuk, Wendel Clark, Jeff Brown, Patrick Lalime, etc.)

9-12 (VERY COMMON) - Player begins skill atrophy at age 32-34 (ex. John LeClair, Dino Ciccarelli, Geoff Courtnall, Bryan Trottier, etc.)

13-15 (SOMEWHAT COMMON) - Player begins skill atrophy at age 34-36 (ex. Bernie Nicholls, Tom Barrasso, Mike Modano, etc.)

16-17 (RARE) - Player begins skill atrophy at 36-38 (ex. Larry Murphy, Wayne Gretzky, Ray Bourque, etc.)

18-19 (VERY RARE) - Player begins skill atrophy at age 38-40 (ex. Mark Recchi, Gary Roberts, Rod Brind'Amour, etc.)

20 (EXTREMELY RARE) - Player begins skill atrophy at age 40+ (ex. Nicklas Lidstrom, Chris Chelios, Gordie Howe)

Keep in mind that this doesn't mean that the player will just fall off the face of the map when he hits this point, it just signifies when attribute decline will begin. I also feel that the rate of attribute decline should be signified by another rating (probably 1-5 or 1-10), with 1 signifying that the player will literally fall off of the face of the map in less than a year (ex. Blaine Lacher, Wendel Clark) while 10 signifies that the player is all but an "ageless wonder" (ex. Ray Bourque, Patrick Roy).

Granted, those are extremes. A more reasonable decline would be, for example, a forward or defenseman going from star-caliber to depth piece (i.e. 3rd liner or third-pairing defenseman) in a few years (ex. Mike Modano, Chris Chelios, Kirk Muller, etc.).

Also what should be noted are that potential discrepancies should be avoided (ex. a player with a development speed rating of 20 shouldn't have a career longetivity of 1 or 2, a player with a development of 17 cannot have a career longetivity of 3, etc.), which might make this a nightmare to code. Just something to think about.

VOLATILITY: One inevitability of sport is that athletes can suddenly "boom or bust" at any given moment in their career. Players once thought of as afterthoughts when they were draft-eligible become top prospects or players of significant impact at the NHL-level (ex. Steve Duchesne, Martin St. Louis, Olli Jokinen, undrafted prospects such as Tyler Bozak, Fabian Brunnstrom and Teddy Purcell, etc.) while people wonder what happened to quality players at the NHL level due a sudden and significant regression (ex. Blaine Lacher, Jonathan Cheechoo, Stephan Lebeau, Jim Carey, Mike York, etc.). This is what I felt EHM lacked as well, but might be reasonable as it may be a little hard to code.

My idea is a random, albeit infrequent stream of "volatility rolls." I'm thinking of a monthly (bi-monthly?) event where CA and PA is randomly changed in a certain amount of players throughout the database (say 1-2% of players and staff per roll). A strong majority of these player's changes will be insignificant (CA/PA change +/- 1 to 3 [~99% of rolls]), but there will be a few that have a significant change to their abilities (CA/PA change +/- 5 to 10 [~.3 - .5%]) and, once in a full moon, the "boom" and "bust" (CA/PA change +/- 10 to 30 [~.1 - .01%]). The attributes won't take into consideration this change immediately, but the development/regression of said attributes would be influenced by the development speed/career longetivity rating of the player, coaching, mental attributes, injuries, etc.

Yeah... hope I didn't bore you with that. I have some other ideas as well, but I'm tired of writing. Don't know if it's feasible right now, but it's something to consider.

Hossmann wrote:I'm elated to see that somebody's decided to take up the daunting task of developing a hockey manager from scratch, and you have my appreciation for it. Anyway, here's my two cents on the matter (WARNING: WALL OF TEXT):

One thing that always irked me about EHM 2007 was that development/regression was very linear and unrealistic (players would mostly peak around age 20-21 while they would only experience a very sharp skating regression around age 39-40). Add to this the fact that most attributes progressed at the same time (especially technical attributes), when it happened. Of course, this kind of development path is the exception, not the rule.

DEVELOPMENT: My idea would be to create a "Bell curve" regarding this, with the average age of a player reaching his "plateau" being around 24-26 (although the case could be made for earlier development peaks for wingers [early 20s] while it being later for defensemen and goaltenders [late 20's]) with the extreme fringes of development ranging from late teens to early thirties. Don't know how feasible it would be to develop a hidden attribute for individual development speed, but I would suggest something like a 1-20 rating for it (possibly affected by outside influences such as coaching, mental attributes, injuries, etc.).

1 (EXTREMELY RARE) - Player reaches peak development at age 15-16

2-3 (VERY RARE) - Player reaches peak development at age 17-19 (ex. Jason Bonsignore, Scott Scissons, [speculative] Angelo Esposito, etc.)

4-5 (RARE) - Player reaches peak development at age 20-22 (ex. Jim Carey, Jimmy Carson, Dino Ciccarelli, Dion Phaneuf, etc.)

6-8 (SOMEWHAT COMMON) - Player reaches peak development at age 22-24 (ex. Teemu Selanne, Jaromir Jagr, Kevin Lowe, Mark Recchi, Henrik Lundqvist, etc.)

9-12 (VERY COMMON) - Player reaches peak development at age 23-26 (ex. Joe Mullen, Kevin Stevens, Rob Blake, Danny Briere, etc.)

13-15 (SOMEWHAT COMMON) - Player reaches peak development at age 25-27 (ex. Pavel Datsyuk, Marc Savard, Zdeno Chara, Ryan Miller, etc.)

16-17 (RARE) - Player reaches peak development at age 28-30 (ex. Martin St. Louis, Andy McDonald, Johan Franzen, Dominik Hasek, etc.)

18-19 (VERY RARE) - Player reaches peak development at age 30-32 (ex. Jason Blake, Tomas Holmstrom, Mark Streit, Dwayne Roloson, etc.)

20 (EXTREMELY RARE) - Player reaches peak development at age 32-34 (ex. Tim Thomas)

REGRESSION: Like development, there should be a hidden attribute (1-20 range) for career longetivity, which can also be influenced by mental attributes, injuries, etc.

1 (EXTREMELY RARE) - Player begins skill atrophy at age 22-25 (ex. Jim Carey)

2-3 (VERY RARE) - Player begins skill atrophy at 25-28 (ex. Blaine Lacher, Jonathan Cheechoo, Jimmy Carson, etc.)

4-5 (RARE) - Player begins skill atrophy at age 28-30 (ex. Sami Kapanen, Brian Savage, Jeff O'Neill, etc.)

6-8 (SOMEWHAT COMMON) - Player begins skill atrophy at age 30-32 (ex. Dale Hawerchuk, Wendel Clark, Jeff Brown, Patrick Lalime, etc.)

9-12 (VERY COMMON) - Player begins skill atrophy at age 32-34 (ex. John LeClair, Dino Ciccarelli, Geoff Courtnall, Bryan Trottier, etc.)

13-15 (SOMEWHAT COMMON) - Player begins skill atrophy at age 34-36 (ex. Bernie Nicholls, Tom Barrasso, Mike Modano, etc.)

16-17 (RARE) - Player begins skill atrophy at 36-38 (ex. Larry Murphy, Wayne Gretzky, Ray Bourque, etc.)

18-19 (VERY RARE) - Player begins skill atrophy at age 38-40 (ex. Mark Recchi, Gary Roberts, Rod Brind'Amour, etc.)

20 (EXTREMELY RARE) - Player begins skill atrophy at age 40+ (ex. Nicklas Lidstrom, Chris Chelios, Gordie Howe)

Keep in mind that this doesn't mean that the player will just fall off the face of the map when he hits this point, it just signifies when attribute decline will begin. I also feel that the rate of attribute decline should be signified by another rating (probably 1-5 or 1-10), with 1 signifying that the player will literally fall off of the face of the map in less than a year (ex. Blaine Lacher, Wendel Clark) while 10 signifies that the player is all but an "ageless wonder" (ex. Ray Bourque, Patrick Roy).

Granted, those are extremes. A more reasonable decline would be, for example, a forward or defenseman going from star-caliber to depth piece (i.e. 3rd liner or third-pairing defenseman) in a few years (ex. Mike Modano, Chris Chelios, Kirk Muller, etc.).

Also what should be noted are that potential discrepancies should be avoided (ex. a player with a development speed rating of 20 shouldn't have a career longetivity of 1 or 2, a player with a development of 17 cannot have a career longetivity of 3, etc.), which might make this a nightmare to code. Just something to think about.

VOLATILITY: One inevitability of sport is that athletes can suddenly "boom or bust" at any given moment in their career. Players once thought of as afterthoughts when they were draft-eligible become top prospects or players of significant impact at the NHL-level (ex. Steve Duchesne, Martin St. Louis, Olli Jokinen, undrafted prospects such as Tyler Bozak, Fabian Brunnstrom and Teddy Purcell, etc.) while people wonder what happened to quality players at the NHL level due a sudden and significant regression (ex. Blaine Lacher, Jonathan Cheechoo, Stephan Lebeau, Jim Carey, Mike York, etc.). This is what I felt EHM lacked as well, but might be reasonable as it may be a little hard to code.

My idea is a random, albeit infrequent stream of "volatility rolls." I'm thinking of a monthly (bi-monthly?) event where CA and PA is randomly changed in a certain amount of players throughout the database (say 1-2% of players and staff per roll). A strong majority of these player's changes will be insignificant (CA/PA change +/- 1 to 3 [~99% of rolls]), but there will be a few that have a significant change to their abilities (CA/PA change +/- 5 to 10 [~.3 - .5%]) and, once in a full moon, the "boom" and "bust" (CA/PA change +/- 10 to 30 [~.1 - .01%]). The attributes won't take into consideration this change immediately, but the development/regression of said attributes would be influenced by the development speed/career longetivity rating of the player, coaching, mental attributes, injuries, etc.

Yeah... hope I didn't bore you with that. I have some other ideas as well, but I'm tired of writing. Don't know if it's feasible right now, but it's something to consider.

Love it.

Great read and good points, I'm only not a fan of "volatility". For example, it's not that Cheechoo at one point un-learned how to play hockey, it's just that a group of events "happened" both before his booming and his busting. Having and not having good line mates means a lot.

Alessandro wrote:For example, it's not that Cheechoo at one point un-learned how to play hockey, it's just that a group of events "happened" both before his booming and his busting. Having and not having good line mates means a lot.

Coach's playing style affects also.

Alessandro wrote:Great read and good points, I'm only not a fan of "volatility". For example, it's not that Cheechoo at one point un-learned how to play hockey, it's just that a group of events "happened" both before his booming and his busting. Having and not having good line mates means a lot.

I can see how Volatility becomes a bit redundant in a game that has development speed and career longetivity ratings, but it's simply trying to find an explanation for the sudden dropoff. Also probably would be a nightmare to code, so best bet would be to scrap that idea.

I do have a few more ideas for consideration, however.

MULTIPLE CA/PA RATINGS: As I mentioned in my previous post, one thing that I found unrealistic was the fact that technical attributes usually progressed all at once (making them merely the same player, just better). What I suggest is to divide CA/PA into several categories that each have their own unique rating:

SKATERS:

SKATING CA/PA (Speed, Acceleration, Agility, Stamina)
PHYSICAL CA/PA (Strength, Checking, Fighting, Hitting, Balance, Aggressiveness)
MENTAL CA/PA (Bravery, Determination, Adaptability, Influence, Work Ethic, Creativity)
DEFENSIVE CA/PA (Anticipation, Pokecheck, Bravery, Positioning)
TECHNICAL CA/PA (Faceoffs, Deflections, Positioning, Passing, Getting Open, Teamwork)
STICKHANDLING CA/PA (Stickhandling, Wristshot, Slapshot, Deking, Flair)

GOALIES

SKATING CA/PA (Speed, Acceleration, Agility, Stamina)
PHYSICAL CA/PA (Strength, Balance, Aggressiveness)
MENTAL CA/PA (Bravery, Determination, Adaptability, Influence, Work Ethic, Creativity)
TECHNICAL CA/PA (Anticipation, Pokecheck, Positioning, Passing, Rebound Control)
GOALTENDING CA/PA (Blocker, Glove, Reflexes, Stickhandling, Recovery)

Granted, there's a little bit of overlap with these attributes (mainly with mental attributes such as Flair, Anticipation, Creativity, Aggressiveness, etc.), but I feel they're necessary to give an accurate image to a player. Take, for example, a player like Rico Fata. He was a very terrific skater (i.e. Skating CA/PA is ~ 190), but he didn't bring much else to the table (his mental, technical and stickhandling CA/PA's would be far lower [~ 100-120]). A "soft" European player could have solid skating, mental, technical and stickhandling CA/PA's (let's say ~ 130-150), but his physical CA/PA would be significantly lower than the rest (~ 80-90). Meanwhile, a defensive defenseman like Hal Gill has great physical, mental and defensive qualities (CA/PA at 140-160), his skating, technical and stickhandling abilities leave a lot to be desires (CA/PA at 80-90).

INJURIES: Another thing that irked me about EHM was the unrealism of injury recovery, as they would recover to full strength, no matter a bruised elbow or torn ACL. The sad fact of the matter is that injuries destroy careers (just ask Gord Kluzak, Brett Lindros [even Eric Lindros, for that matter], Jason Allison, or any other promising player that was ravaged by them). There should be some sort of variable that measures the amount of recovery a player can make from such an injury (especially if serious).

For example, Player X suffers a torn rotator cuff and is out for 4 months. The player is at risk of his physical and stickhandling attributes atrophying (such as checking, hitting, and even some mental attributes like aggression and bravery) due to the location of the injury. There are several ways he could be penalized for such an injury (with definite variables such as player age, work ethic, determination and whether or not the injury is chronic or recurring). Lets say that Player X is 22 years old, has a solid work ethic and has no injury history in that particular area:

100% recovery (let's say there's a 60-65% chance of this happening)
90-95% recovery (20-25% chance)
80-90% recovery (5-10% chance)
70-80% recovery (1-2% chance)
60-70% recovery (.1 - 1% chance)
Less than 60% recovery (very miniscule chance).

Although, if he re-agitates the injury several years down the road (age 25), his chances of recovery could be like this:

100% recovery (35-40%)
90-95% recovery (30-35% chance)
80-90% recovery (15-20% chance)
70-80% recovery (3-5% chance)
60-70% recovery (1-2% chance)
Less than 60% recovery (.1 - 1% chance).

This would continue (with lesser chance of recovery increasing as he ages) until Player X eventually retires.

Well I also think that some serious injury should cut some physical parameters permanently.

23qwerty wrote:

Hossmann wrote:I'm elated to see that somebody's decided to take up the daunting task of developing a hockey manager from scratch, and you have my appreciation for it. Anyway, here's my two cents on the matter (WARNING: WALL OF TEXT):

One thing that always irked me about EHM 2007 was that development/regression was very linear and unrealistic (players would mostly peak around age 20-21 while they would only experience a very sharp skating regression around age 39-40). Add to this the fact that most attributes progressed at the same time (especially technical attributes), when it happened. Of course, this kind of development path is the exception, not the rule.

DEVELOPMENT: My idea would be to create a "Bell curve" regarding this, with the average age of a player reaching his "plateau" being around 24-26 (although the case could be made for earlier development peaks for wingers [early 20s] while it being later for defensemen and goaltenders [late 20's]) with the extreme fringes of development ranging from late teens to early thirties. Don't know how feasible it would be to develop a hidden attribute for individual development speed, but I would suggest something like a 1-20 rating for it (possibly affected by outside influences such as coaching, mental attributes, injuries, etc.).

1 (EXTREMELY RARE) - Player reaches peak development at age 15-16

2-3 (VERY RARE) - Player reaches peak development at age 17-19 (ex. Jason Bonsignore, Scott Scissons, [speculative] Angelo Esposito, etc.)

4-5 (RARE) - Player reaches peak development at age 20-22 (ex. Jim Carey, Jimmy Carson, Dino Ciccarelli, Dion Phaneuf, etc.)

6-8 (SOMEWHAT COMMON) - Player reaches peak development at age 22-24 (ex. Teemu Selanne, Jaromir Jagr, Kevin Lowe, Mark Recchi, Henrik Lundqvist, etc.)

9-12 (VERY COMMON) - Player reaches peak development at age 23-26 (ex. Joe Mullen, Kevin Stevens, Rob Blake, Danny Briere, etc.)

13-15 (SOMEWHAT COMMON) - Player reaches peak development at age 25-27 (ex. Pavel Datsyuk, Marc Savard, Zdeno Chara, Ryan Miller, etc.)

16-17 (RARE) - Player reaches peak development at age 28-30 (ex. Martin St. Louis, Andy McDonald, Johan Franzen, Dominik Hasek, etc.)

18-19 (VERY RARE) - Player reaches peak development at age 30-32 (ex. Jason Blake, Tomas Holmstrom, Mark Streit, Dwayne Roloson, etc.)

20 (EXTREMELY RARE) - Player reaches peak development at age 32-34 (ex. Tim Thomas)

REGRESSION: Like development, there should be a hidden attribute (1-20 range) for career longetivity, which can also be influenced by mental attributes, injuries, etc.

1 (EXTREMELY RARE) - Player begins skill atrophy at age 22-25 (ex. Jim Carey)

2-3 (VERY RARE) - Player begins skill atrophy at 25-28 (ex. Blaine Lacher, Jonathan Cheechoo, Jimmy Carson, etc.)

4-5 (RARE) - Player begins skill atrophy at age 28-30 (ex. Sami Kapanen, Brian Savage, Jeff O'Neill, etc.)

6-8 (SOMEWHAT COMMON) - Player begins skill atrophy at age 30-32 (ex. Dale Hawerchuk, Wendel Clark, Jeff Brown, Patrick Lalime, etc.)

9-12 (VERY COMMON) - Player begins skill atrophy at age 32-34 (ex. John LeClair, Dino Ciccarelli, Geoff Courtnall, Bryan Trottier, etc.)

13-15 (SOMEWHAT COMMON) - Player begins skill atrophy at age 34-36 (ex. Bernie Nicholls, Tom Barrasso, Mike Modano, etc.)

16-17 (RARE) - Player begins skill atrophy at 36-38 (ex. Larry Murphy, Wayne Gretzky, Ray Bourque, etc.)

18-19 (VERY RARE) - Player begins skill atrophy at age 38-40 (ex. Mark Recchi, Gary Roberts, Rod Brind'Amour, etc.)

20 (EXTREMELY RARE) - Player begins skill atrophy at age 40+ (ex. Nicklas Lidstrom, Chris Chelios, Gordie Howe)

Keep in mind that this doesn't mean that the player will just fall off the face of the map when he hits this point, it just signifies when attribute decline will begin. I also feel that the rate of attribute decline should be signified by another rating (probably 1-5 or 1-10), with 1 signifying that the player will literally fall off of the face of the map in less than a year (ex. Blaine Lacher, Wendel Clark) while 10 signifies that the player is all but an "ageless wonder" (ex. Ray Bourque, Patrick Roy).

Granted, those are extremes. A more reasonable decline would be, for example, a forward or defenseman going from star-caliber to depth piece (i.e. 3rd liner or third-pairing defenseman) in a few years (ex. Mike Modano, Chris Chelios, Kirk Muller, etc.).

Also what should be noted are that potential discrepancies should be avoided (ex. a player with a development speed rating of 20 shouldn't have a career longetivity of 1 or 2, a player with a development of 17 cannot have a career longetivity of 3, etc.), which might make this a nightmare to code. Just something to think about.

VOLATILITY: One inevitability of sport is that athletes can suddenly "boom or bust" at any given moment in their career. Players once thought of as afterthoughts when they were draft-eligible become top prospects or players of significant impact at the NHL-level (ex. Steve Duchesne, Martin St. Louis, Olli Jokinen, undrafted prospects such as Tyler Bozak, Fabian Brunnstrom and Teddy Purcell, etc.) while people wonder what happened to quality players at the NHL level due a sudden and significant regression (ex. Blaine Lacher, Jonathan Cheechoo, Stephan Lebeau, Jim Carey, Mike York, etc.). This is what I felt EHM lacked as well, but might be reasonable as it may be a little hard to code.

My idea is a random, albeit infrequent stream of "volatility rolls." I'm thinking of a monthly (bi-monthly?) event where CA and PA is randomly changed in a certain amount of players throughout the database (say 1-2% of players and staff per roll). A strong majority of these player's changes will be insignificant (CA/PA change +/- 1 to 3 [~99% of rolls]), but there will be a few that have a significant change to their abilities (CA/PA change +/- 5 to 10 [~.3 - .5%]) and, once in a full moon, the "boom" and "bust" (CA/PA change +/- 10 to 30 [~.1 - .01%]). The attributes won't take into consideration this change immediately, but the development/regression of said attributes would be influenced by the development speed/career longetivity rating of the player, coaching, mental attributes, injuries, etc.

Yeah... hope I didn't bore you with that. I have some other ideas as well, but I'm tired of writing. Don't know if it's feasible right now, but it's something to consider.

Love it.

Me too, thanks a lot for your input Hossmann.

Hossmann wrote:Also what should be noted are that potential discrepancies should be avoided (ex. a player with a development speed rating of 20 shouldn't have a career longetivity of 1 or 2, a player with a development of 17 cannot have a career longetivity of 3, etc.), which might make this a nightmare to code. Just something to think about.

Don't worry, this part is already going to be a nightmare to code.

Hossmann wrote:MULTIPLE CA/PA RATINGS: As I mentioned in my previous post, one thing that I found unrealistic was the fact that technical attributes usually progressed all at once (making them merely the same player, just better). What I suggest is to divide CA/PA into several categories that each have their own unique rating:

SKATERS:

SKATING CA/PA (Speed, Acceleration, Agility, Stamina)
PHYSICAL CA/PA (Strength, Checking, Fighting, Hitting, Balance, Aggressiveness)
MENTAL CA/PA (Bravery, Determination, Adaptability, Influence, Work Ethic, Creativity)
DEFENSIVE CA/PA (Anticipation, Pokecheck, Bravery, Positioning)
TECHNICAL CA/PA (Faceoffs, Deflections, Positioning, Passing, Getting Open, Teamwork)
STICKHANDLING CA/PA (Stickhandling, Wristshot, Slapshot, Deking, Flair)

GOALIES

SKATING CA/PA (Speed, Acceleration, Agility, Stamina)
PHYSICAL CA/PA (Strength, Balance, Aggressiveness)
MENTAL CA/PA (Bravery, Determination, Adaptability, Influence, Work Ethic, Creativity)
TECHNICAL CA/PA (Anticipation, Pokecheck, Positioning, Passing, Rebound Control)
GOALTENDING CA/PA (Blocker, Glove, Reflexes, Stickhandling, Recovery)

Granted, there's a little bit of overlap with these attributes (mainly with mental attributes such as Flair, Anticipation, Creativity, Aggressiveness, etc.), but I feel they're necessary to give an accurate image to a player. Take, for example, a player like Rico Fata. He was a very terrific skater (i.e. Skating CA/PA is ~ 190), but he didn't bring much else to the table (his mental, technical and stickhandling CA/PA's would be far lower [~ 100-120]). A "soft" European player could have solid skating, mental, technical and stickhandling CA/PA's (let's say ~ 130-150), but his physical CA/PA would be significantly lower than the rest (~ 80-90). Meanwhile, a defensive defenseman like Hal Gill has great physical, mental and defensive qualities (CA/PA at 140-160), his skating, technical and stickhandling abilities leave a lot to be desires (CA/PA at 80-90).

I agree, in fact I have thought about something like this and started to look at how this could be implemented. Right now I have scrapped CA/PA though. More info will be released once I have seen if it works ok or not.

Hossmann wrote:INJURIES: Another thing that irked me about EHM was the unrealism of injury recovery, as they would recover to full strength, no matter a bruised elbow or torn ACL. The sad fact of the matter is that injuries destroy careers (just ask Gord Kluzak, Brett Lindros [even Eric Lindros, for that matter], Jason Allison, or any other promising player that was ravaged by them). There should be some sort of variable that measures the amount of recovery a player can make from such an injury (especially if serious).

For example, Player X suffers a torn rotator cuff and is out for 4 months. The player is at risk of his physical and stickhandling attributes atrophying (such as checking, hitting, and even some mental attributes like aggression and bravery) due to the location of the injury. There are several ways he could be penalized for such an injury (with definite variables such as player age, work ethic, determination and whether or not the injury is chronic or recurring). Lets say that Player X is 22 years old, has a solid work ethic and has no injury history in that particular area:

100% recovery (let's say there's a 60-65% chance of this happening)
90-95% recovery (20-25% chance)
80-90% recovery (5-10% chance)
70-80% recovery (1-2% chance)
60-70% recovery (.1 - 1% chance)
Less than 60% recovery (very miniscule chance).

Although, if he re-agitates the injury several years down the road (age 25), his chances of recovery could be like this:

100% recovery (35-40%)
90-95% recovery (30-35% chance)
80-90% recovery (15-20% chance)
70-80% recovery (3-5% chance)
60-70% recovery (1-2% chance)
Less than 60% recovery (.1 - 1% chance).

This would continue (with lesser chance of recovery increasing as he ages) until Player X eventually retires.

I like this too, but cannot promise this will be included from day one though.

I am looking to spend all my project time on this for the forseeable future and set up a simulation environment (more info in the next blog entry) for this part only and tweak the system until it gives an adequate result. This will take a lot of time but fortunately we are three people working on the project so other parts will not stand still. This part of the game is both scary and one of my favourites at the same time.

I love the Development and Regression attributes! Those would really add a lot to the game to make players more unique.

I also like the multiple PA/CA idea but I worry that it would be just too hard to research. You need a bunch of actual scouts to rate all of the players for the DB. It makes perfect sense. I just think it would be too difficult to implement.

First of all it awesome to this progressing into this stage, this is IMO the most important part of the game. Player development is the most important thing in simulation games, without it the game becomes pointless beyond a couple of seasons. The above issues have looked really great, the "bell curve" idea looks darn near perfect, IMO. This would very high draft busts, and some undrafted guys who can develop into players. The real problem like Hossman said is the percentages. This would need lots of research and programming hell. Although I not much of a programmer (only have some first year university courses in programming) I would be willing to help with research if you would like. Let me know.

Anyways, just an idea to keep in mind as I do not know if it is feasible at the current time but the Volatility that Hossman mentioned might be a good idea and tie it to performance. Let's say I draft offensive C John Smith with the 3rd overall pick in the draft. Now he is coming off of a 92pt 17 year old year in junior. Let's say in the next year for some reason he struggles consistantly playing some bad games and only registers 66pts. Then he "may" get a small potential draft. Then the next year he struggles again getting only 71pts. Again he may get a small potential drop. If you look at it this way he would no longer be looked upon in real as top prospect right if he has not performed as well as his draft year. Same thing then if Smith then turns pro and puts up 66pts in the AHL in his rookie season he may get a "small" potential" boost.

Basically this would not replace overall potential and make it performance based, but several bad seasons could ruin a prospects chances while a couple of great seasons can greatly increase it. Just tweaking the potential as it goes. Same idea with attributes in the NHL. One frusterating this was like if Souray was rated as a top defenseman, then had say horrible back to back seasons, well he was still a top defenseman? This just comes into the regression thing I guess, but maybe to make it more based on the actual gameplay rather than arbitrary numbers programmed into code.

To sum up, it might be better to try to get performance at least tied into the progression/regression coding, although which one leads and follows would be up to you.

This afternoon I entertained myself by using Hossmann ideas together with my percentage estimates to try and generate a good (realistic) career curve for players. I created a small program that generates a number of players (with a development- and regression attribute each) and prints two charts displaying when players reach their peak and begin to atrophy. For the latter I did take into account what Hossmann mentioned, namely the fact that players cannot start atrophying until they have reached their peak. When it comes to the percentages I have to admit I am not an expert and I am prepared to tweak them. Have a look at the screenshot below and let me know what you think.



Remember, since this is randomized it doesn't look exactly the same every time I run the program; but using 1000 players the curves are fairly stable. Also, I did not take into account parameters such as injuries which obviously could change when a player starts to regress.

HoldenC wrote:First of all it awesome to this progressing into this stage, this is IMO the most important part of the game. Player development is the most important thing in simulation games, without it the game becomes pointless beyond a couple of seasons. The above issues have looked really great, the "bell curve" idea looks darn near perfect, IMO. This would very high draft busts, and some undrafted guys who can develop into players. The real problem like Hossman said is the percentages. This would need lots of research and programming hell. Although I not much of a programmer (only have some first year university courses in programming) I would be willing to help with research if you would like. Let me know.

Anyways, just an idea to keep in mind as I do not know if it is feasible at the current time but the Volatility that Hossman mentioned might be a good idea and tie it to performance. Let's say I draft offensive C John Smith with the 3rd overall pick in the draft. Now he is coming off of a 92pt 17 year old year in junior. Let's say in the next year for some reason he struggles consistantly playing some bad games and only registers 66pts. Then he "may" get a small potential draft. Then the next year he struggles again getting only 71pts. Again he may get a small potential drop. If you look at it this way he would no longer be looked upon in real as top prospect right if he has not performed as well as his draft year. Same thing then if Smith then turns pro and puts up 66pts in the AHL in his rookie season he may get a "small" potential" boost.

Basically this would not replace overall potential and make it performance based, but several bad seasons could ruin a prospects chances while a couple of great seasons can greatly increase it. Just tweaking the potential as it goes. Same idea with attributes in the NHL. One frusterating this was like if Souray was rated as a top defenseman, then had say horrible back to back seasons, well he was still a top defenseman? This just comes into the regression thing I guess, but maybe to make it more based on the actual gameplay rather than arbitrary numbers programmed into code.

To sum up, it might be better to try to get performance at least tied into the progression/regression coding, although which one leads and follows would be up to you.

I agree with your idea to an extent, but I don't believe a big season or terrible season should have much or any affect towards potential ability (although I believe it could have an impact towards a player's confidence or work ethic [does it motivate him to work harder on his flaws or does the bad season rattle him to the point of all repair?]).

What a good or bad season (particularly whether or not a player shows a significant improvement or decline in statistics [i.e. Goals, points, GAA, SV%]) should definitely impact is the scout's projection of current & future ability. Take, for example, Dany Roussin. He was once considered a fringe prospect (picked in the seventh round of the 2003 draft), but once he started playing on a line with Sidney Crosby (thus, his statistical output increased dramatically), his player "stock" rose dramatically to the point where he was re-selected by the LA Kings in the second round as a 20-year-old. Did it affect his potential? Absolutely not (case in point, he became a great scorer... at the ECHL level). Did it affect how scouts projected his potential? Definitely.

Same goes for the opposite. If a player shows stagnation or decline in performance (especially in a big event such as the WJC or playoffs), the player's stock will plummet (ex. Angelo Esposito during the 2006-2007 year, Jean-Phillipe Levasseur during his draft year, etc.).

dabo wrote:This afternoon I entertained myself by using Hossmann ideas together with my percentage estimates to try and generate a good (realistic) career curve for players. I created a small program that generates a number of players (with a development- and regression attribute each) and prints two charts displaying when players reach their peak and begin to atrophy. For the latter I did take into account what Hossmann mentioned, namely the fact that players cannot start atrophying until they have reached their peak. When it comes to the percentages I have to admit I am not an expert and I am prepared to tweak them. Have a look at the screenshot below and let me know what you think.



Remember, since this is randomized it doesn't look exactly the same every time I run the program; but using 1000 players the curves are fairly stable. Also, I did not take into account parameters such as injuries which obviously could change when a player starts to regress.

The only things I'd say are that the "extremely rare" and "rare" occurrences in both categories for peak/atrophy are too close together. I'm not a man of percentages, either, but I'd reallocate a small share of "very common" player occurrence (guessing around 5% or 25/1000 players) and split them between both "rare" settings in development (12-13 players each).

For atrophy, I'd put the occurrence of "very common" of atrophy at around 45% and reallocate that towards both "rare" settings as well. I'd also increase the occurrence of the "very rare" atrophy, albeit very slightly (say, 10-15/1000 players). The "extremely rare" atrophy (22-25) should probably be at 1 out of every 2000-2500 players (because, let's be honest, players of Jim Carey-esque decline do not grow on trees).

Otherwise, looking good, man.

Thanks for the feedback, will tweak it tomorrow and increase the precision. For the screenshot above I was using:

Peak:
1 (Extremely rare, 1%)
2 - 3 (Very rare, 2%)
4 - 5 (Rare, 4%)
6 - 8 (Somewhat common, 18%)
9 - 12 (Very common, 50%)
13 - 15 (Somewhat common, 18%)
16 - 17 (Rare, 4%)
18 - 19 (Very rare, 2%)
20 (Extremely rare, 1%)

Atrophy:
Depends on peak (since not all combinations are possible) but is similar.

But there's one thing I feel we're missing here, i.e. the case of all those youth who fail to be drafted by CHL teams/make an NCAA team/end up unable to play for a team above the 3rd of 4th national level of competition in Europe. How should those lads be classified? Very early peakers (in which case the curve would be an upside-down bell with the peak centering at/near the minimum age)? Anywhere in the curve but with a very low peak value? How would their suckiness then be determined? I have a feeling there'll probably also need some sort of a randomly assigned PA to every kid, that will be very plastic in his first couple of years (depending on his mental attributes, physical attributes and on external events such as being a bench-warmer on a powerful midget/junior team, getting a very bad injury or spawning at a small team with dismal training facilities) and rather rigid after the kid has reached some threshold age. Most of those bad players will soon give up and be recycled, the others will fill the rosters of the worst local senior leagues.


@ Hossmann: I don't know, Carey was quite the hockey equivalent of a one-hit wonder, but did his career decline because of his skills actually dwindling fast, or because of external factors that got in his head and destroyed his focus? In 1996-97, after two stellar ones, he was having an average season (more or less playing for .500, which isn't that bad either), then got shipped to the abysmal Bruins where there's not so much he could do and fared badly. Can't his performance in Boston (or the trade itself) have destroyed his confidence so much he just couldn't retrieve his form again ('til an injury almost left him deaf from one ear and had him stop playing)? Was he only comfortable as an underdog? Things like that should happen in-game.

- YZG

Hossmann wrote: I agree with your idea to an extent, but I don't believe a big season or terrible season should have much or any affect towards potential ability (although I believe it could have an impact towards a player's confidence or work ethic [does it motivate him to work harder on his flaws or does the bad season rattle him to the point of all repair?]).

What a good or bad season (particularly whether or not a player shows a significant improvement or decline in statistics [i.e. Goals, points, GAA, SV%]) should definitely impact is the scout's projection of current & future ability. Take, for example, Dany Roussin. He was once considered a fringe prospect (picked in the seventh round of the 2003 draft), but once he started playing on a line with Sidney Crosby (thus, his statistical output increased dramatically), his player "stock" rose dramatically to the point where he was re-selected by the LA Kings in the second round as a 20-year-old. Did it affect his potential? Absolutely not (case in point, he became a great scorer... at the ECHL level). Did it affect how scouts projected his potential? Definitely.

Same goes for the opposite. If a player shows stagnation or decline in performance (especially in a big event such as the WJC or playoffs), the player's stock will plummet (ex. Angelo Esposito during the 2006-2007 year, Jean-Phillipe Levasseur during his draft year, etc.).

Fair enough, this is a very good point. And I do agree with you, to a point as you say. But the two examples you used after(Esposito and Levasseur) prove more so the point that they now do not have the potential they once had. Maybe they never had it and only appeared to. And I for sure want this is in there as these are two guys you could argue peaked at 16 years old. I mean they have not progressed much since then have they?
What I don't want is say a guy who is dominating every level, comes into the NHL and is say dominant for a couple of seasons yet his ratings still say he is barely an NHLer just because he potential originally had been limited. Or let's say Nylander goes and has seasons like he has the last couple of years. His ratings should be dropped to the appropriate level, there is no way he will just go back to the form he used to have, even if his ingame coding says his regression says it should. His regression should either be leading this dropoff in performance, or the performance should demand the dropoff.

Just saying basically that performance and potential/regression should be tied together somehow. So that they make sense and players ratings don't randomly start to regress even when his performance is still just as good. Players should not develop or regress without reason.

Hossmann wrote: The only things I'd say are that the "extremely rare" and "rare" occurrences in both categories for peak/atrophy are too close together. I'm not a man of percentages, either, but I'd reallocate a small share of "very common" player occurrence (guessing around 5% or 25/1000 players) and split them between both "rare" settings in development (12-13 players each).

For atrophy, I'd put the occurrence of "very common" of atrophy at around 45% and reallocate that towards both "rare" settings as well. I'd also increase the occurrence of the "very rare" atrophy, albeit very slightly (say, 10-15/1000 players). The "extremely rare" atrophy (22-25) should probably be at 1 out of every 2000-2500 players (because, let's be honest, players of Jim Carey-esque decline do not grow on trees).

Otherwise, looking good, man.

I like what dabo is doing but I think you might be right. And I think the peak at 16-18 in particular might need to be a little higher since that is what creates draft busts (players that peak at 18).
And the regression might need to be a little younger like 30-32 and not be as steep. Just my opinion as lots of players seem to play their 20's in the NHL (particularly 3rd-4th liners) then as they become extra parts at 27-30 (teams realize they will never become any better) they head overseas to finish careers. Although you could argue that this is a way for NHL teams to save money(turn to the younger cheaper guy with the potential to be better) rather than regression. So this point might be moot.

Anyways, dabo it looks good!

YZG wrote:But there's one thing I feel we're missing here, i.e. the case of all those youth who fail to be drafted by CHL teams/make an NCAA team/end up unable to play for a team above the 3rd of 4th national level of competition in Europe. How should those lads be classified? Very early peakers (in which case the curve would be an upside-down bell with the peak centering at/near the minimum age)? Anywhere in the curve but with a very low peak value? How would their suckiness then be determined? I have a feeling there'll probably also need some sort of a randomly assigned PA to every kid, that will be very plastic in his first couple of years (depending on his mental attributes, physical attributes and on external events such as being a bench-warmer on a powerful midget/junior team, getting a very bad injury or spawning at a small team with dismal training facilities) and rather rigid after the kid has reached some threshold age. Most of those bad players will soon give up and be recycled, the others will fill the rosters of the worst local senior leagues.

- YZG

These curves have nothing to do with the quality of players. Two players peaking at 18 could be completely different, one could be NHL-ready while the other could be useless and never amount to anything. This is just to estimate player career curves.

I have tweaked the peak percentages to the following:

1 (Extremely rare, 0.1%)
2 - 3 (Very rare, 2%)
4 - 5 (Rare, 7%)
6 - 8 (Somewhat common, 15.9%)
9 - 12 (Very common, 50%)
13 - 15 (Somewhat common, 15.9%)
16 - 17 (Rare, 7%)
18 - 19 (Very rare, 2%)
20 (Extremely rare, 0.1%)

I tweaked all the combinations of atrophy percentages too.

New


Old


If anyone have any percentages in mind that may work better please post them according to the format above.

HoldenC wrote: Fair enough, this is a very good point. And I do agree with you, to a point as you say. But the two examples you used after(Esposito and Levasseur) prove more so the point that they now do not have the potential they once had. Maybe they never had it and only appeared to. And I for sure want this is in there as these are two guys you could argue peaked at 16 years old. I mean they have not progressed much since then have they?
What I don't want is say a guy who is dominating every level, comes into the NHL and is say dominant for a couple of seasons yet his ratings still say he is barely an NHLer just because he potential originally had been limited. Or let's say Nylander goes and has seasons like he has the last couple of years. His ratings should be dropped to the appropriate level, there is no way he will just go back to the form he used to have, even if his ingame coding says his regression says it should. His regression should either be leading this dropoff in performance, or the performance should demand the dropoff.

Just saying basically that performance and potential/regression should be tied together somehow. So that they make sense and players ratings don't randomly start to regress even when his performance is still just as good. Players should not develop or regress without reason.

I can see what you're saying, give players a slight deviation in CA/PA based on performance (something like, for example, a 120 CA can "evolve" into a maximum 135 CA if he proves to be a complimentary top six forward in the NHL or "regress" to a minimum 105 CA if his style of play does not convert to the NHL level). Makes a little sense, but could the performance be considered as a mere "flash in the pan" or simply development/regression. Although, I feel that this could work as a "hot/cold streak." A player playing totally out of his mind (ex. Ruslan Fedotenko during the 2004 NHL Playoffs) gets an attribute/confidence/CA boost for a given amount of time while a player going through a prolonged slump (ex. Marc-Andre Fleury post-2010 Winter Olympics into late October) CA/attributes/confidence is penalized for a given amount of time. Whether or not they work themselves or are coached out of this slump is another matter entirely, however.

I still feel, as with the examples of Esposito and Levasseur, those stagnations of development were them reaching their individual peaks instead of a freak CA/PA drop. When they were both 16/17, their perceived potentials were far greater than (what appear) to be their actual potentials. Let's say, for example, both of their PA's are 110 (i.e. fringe NHL players).

- At age 16/17, their perceived PA's by many scouts were that of top-tier talent in the NHL (PAs ~160-170), scouts project them to become first-round talent.
- At age 17/18, however, they experience bad or disappointing seasons, and scouts temper their projections of the players (they become "boom-or-bust" prospects)
- At age 20/21, due to injuries (in Esposito's case) or bad play (in Levasseur's case), their projections at the NHL level drop even further. While some scouts still hold on to the idea that they have a chance at regaining their former potential, many believe they only have an outside chance at becoming NHL regulars.

dabo wrote: I have tweaked the peak percentages to the following:

1 (Extremely rare, 0.1%)
2 - 3 (Very rare, 2%)
4 - 5 (Rare, 7%)
6 - 8 (Somewhat common, 15.9%)
9 - 12 (Very common, 50%)
13 - 15 (Somewhat common, 15.9%)
16 - 17 (Rare, 7%)
18 - 19 (Very rare, 2%)
20 (Extremely rare, 0.1%)

I tweaked all the combinations of atrophy percentages too.

New


If anyone have any percentages in mind that may work better please post them according to the format above.

The only thing I'd do for the percentages (although this could just be me talking out of my ass) would be this:

1 (Extremely rare, 0.2%)
2 - 3 (Very rare, 2%)
4 - 5 (Rare, 7%)
6 - 8 (Somewhat common, 17.8%)
9 - 12 (Very common, 46%)
13 - 15 (Somewhat common, 17.8%)
16 - 17 (Rare, 7%)
18 - 19 (Very rare, 2%)
20 (Extremely rare, 0.2%)

This change is mainly to make the "somewhat common" ratings deviate a little more from the "rare" ratings.

Otherwise, the only thing to do is see how the theory works in-game (regarding ratios regarding what players peak where and so on). Looks promising, though.