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- Joined: Mon Nov 11, 2013 11:21 am
Fri Mar 21, 2014 9:33 pm
Here's a restatement of my proposed major tweak to the online game (not that I have any say or would ever approach the game company, of course) that involves potential re-randomization of a star player's mystery card during the season. Just curious if the rest of you have an opinion and would vote "yes" or "no" to this idea. For arguments for and against you may refer to the "Player Cards After Dropped" topic from another thread.
viewtopic.php?f=9&t=635290
Re-randomization of star players
Potential re-randomization of players who are placed on waivers and have >$7m salary as described below:
a. Manager acquiring player off waivers is granted a 5-10% reduction in salary requirement depending on factors yet to be determined.
b. The player acquired via waivers will have a 10% probability of his mystery card being re-randomized prior to acquisition by the new manager.
c. Should the player be waived a second time, then no possibility of salary reduction of the original price or re-randomization will occur. The salary and mystery card of the waived player would revert to the original.
d. The waiving manager may not reacquire the waived player in order to benefit from a re-randomization.
e. Only one re-randomization potential per waiving manager would exist per season.
Here are examples of how it might work.
Example #1:
1. Manager A places Yastrzemski ($10m) on waivers because he is hitting .214.
2. Manager B does due dilligence in analyzing performance and determines that the worst mystery version is linked to the player.
3. Manager B acquires Yastrzemski at a discount for risk compensation. For example, $9M, instead of $10M.
4. Yastrzemski's mystery card would have a 10% chance of being re-randomized by the game engine.
5. After an extended period of play, Manager B concludes that Yastrzemski is still performing poorly (90 % chance of no re-randomization) and waives him again.
6. No potential for re-randomization of the player waived a second time. The mystery version reverts to its original status (worst mystery card) and his salary reverts to $10m.
Example #2:
1. Manager A places Yastrzemski ($10m) on waivers because he is hitting .214.
2. Manager B does due dilligence in analyzing performance and determines that the worst mystery version is linked to the player.
3. Manager B acquires Yastrzemski at a discount for risk compensation. For example, $9M, instead of $10M.
4. Yastrzemski's mystery card has a 10% chance of being re-randomized by the game engine prior to acquisition by Manager B.
The 10% probability "kicks in" and the game engine does a re-randomization of Yastrzemski's mystery card.
Example #3:
1. Manager A places Yastrzemski ($10m) on waivers because he is hitting .214.
2. Manager B does due dilligence in analyzing performance and is of the opinion that Manager A used poor judgement in waiving the player. His mystery card could be much better than his worst.
3. Manager B acquires Yastrzemski at a discount for risk compensation. For example, $9M, instead of $10M.
4. Yastrzemski's mystery card would have a 10% chance of being re-randomized by the game engine. The 10% probability "kicks in" and the game engine does a re-randomization of Yastrzemski's mystery card.
5. After an extended period of play, Manager B sees Yastrzemski hitting .183. Possibly, the re-randomization made the card worst for Manager B than for Manager A.
viewtopic.php?f=9&t=635290
Re-randomization of star players
Potential re-randomization of players who are placed on waivers and have >$7m salary as described below:
a. Manager acquiring player off waivers is granted a 5-10% reduction in salary requirement depending on factors yet to be determined.
b. The player acquired via waivers will have a 10% probability of his mystery card being re-randomized prior to acquisition by the new manager.
c. Should the player be waived a second time, then no possibility of salary reduction of the original price or re-randomization will occur. The salary and mystery card of the waived player would revert to the original.
d. The waiving manager may not reacquire the waived player in order to benefit from a re-randomization.
e. Only one re-randomization potential per waiving manager would exist per season.
Here are examples of how it might work.
Example #1:
1. Manager A places Yastrzemski ($10m) on waivers because he is hitting .214.
2. Manager B does due dilligence in analyzing performance and determines that the worst mystery version is linked to the player.
3. Manager B acquires Yastrzemski at a discount for risk compensation. For example, $9M, instead of $10M.
4. Yastrzemski's mystery card would have a 10% chance of being re-randomized by the game engine.
5. After an extended period of play, Manager B concludes that Yastrzemski is still performing poorly (90 % chance of no re-randomization) and waives him again.
6. No potential for re-randomization of the player waived a second time. The mystery version reverts to its original status (worst mystery card) and his salary reverts to $10m.
Example #2:
1. Manager A places Yastrzemski ($10m) on waivers because he is hitting .214.
2. Manager B does due dilligence in analyzing performance and determines that the worst mystery version is linked to the player.
3. Manager B acquires Yastrzemski at a discount for risk compensation. For example, $9M, instead of $10M.
4. Yastrzemski's mystery card has a 10% chance of being re-randomized by the game engine prior to acquisition by Manager B.
The 10% probability "kicks in" and the game engine does a re-randomization of Yastrzemski's mystery card.
Example #3:
1. Manager A places Yastrzemski ($10m) on waivers because he is hitting .214.
2. Manager B does due dilligence in analyzing performance and is of the opinion that Manager A used poor judgement in waiving the player. His mystery card could be much better than his worst.
3. Manager B acquires Yastrzemski at a discount for risk compensation. For example, $9M, instead of $10M.
4. Yastrzemski's mystery card would have a 10% chance of being re-randomized by the game engine. The 10% probability "kicks in" and the game engine does a re-randomization of Yastrzemski's mystery card.
5. After an extended period of play, Manager B sees Yastrzemski hitting .183. Possibly, the re-randomization made the card worst for Manager B than for Manager A.