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eneubaue · 09-23-2002, 07:14 PM

ScottVib,

I agree in principle, but with caveats. It works well from the perspective of a "real" person trying to train a player at a different position (1B to C) in that it prevents the human from cheating (gaining an advantage of playing a player out of position). However, it doesn't necessarily work all that well internally. I don't want the AI to play a player out of position if it has someone on the roster (or a player in the minors) who has a rating (either primary or secondary) who can step in and play the position when a player goes down with an injury (This is when I primarily see the phenomenon occur).

I don't mind the AI training players at different positions; I also don't mind when the computer AI assigns a fielding percentage of .000 for players being trained at new positions (like 1B to C). I understand the logic. I just don't want it training players at new positions at the major league level. Real teams and managers wouldn't continue to play a player at a position in which he commits 30 errors in 10-20 games (which I've seen happen when the AI assigns a fielding percentage of .000 to a player playing out of position at the major leagues). They would trade for a replacement player or bring one up from the minors, which is what I want the AI to do (that is, of course, if there is a player available who can play the postion as either a primary or secondary position).

I'm pretty sure an issue (at least for me) is whether or not there are enough players on the rosters (majors and minors) who can replace injured players. I'm going to try out expanded rosters (more players in the minors) to see if it alleviates the problem. I think if the computer AI has more players to work with, then the training problem (and fielding pct of .000) won't be a major issue. That is, if training players occur, then it occurs at the minor league level where the fielding results aren't an issue.

09-23-2002, 07:14 PM	#6
eneubaue Minors (Double A) Join Date: Dec 2001 Posts: 156	ScottVib, I agree in principle, but with caveats. It works well from the perspective of a "real" person trying to train a player at a different position (1B to C) in that it prevents the human from cheating (gaining an advantage of playing a player out of position). However, it doesn't necessarily work all that well internally. I don't want the AI to play a player out of position if it has someone on the roster (or a player in the minors) who has a rating (either primary or secondary) who can step in and play the position when a player goes down with an injury (This is when I primarily see the phenomenon occur). I don't mind the AI training players at different positions; I also don't mind when the computer AI assigns a fielding percentage of .000 for players being trained at new positions (like 1B to C). I understand the logic. I just don't want it training players at new positions at the major league level. Real teams and managers wouldn't continue to play a player at a position in which he commits 30 errors in 10-20 games (which I've seen happen when the AI assigns a fielding percentage of .000 to a player playing out of position at the major leagues). They would trade for a replacement player or bring one up from the minors, which is what I want the AI to do (that is, of course, if there is a player available who can play the postion as either a primary or secondary position). I'm pretty sure an issue (at least for me) is whether or not there are enough players on the rosters (majors and minors) who can replace injured players. I'm going to try out expanded rosters (more players in the minors) to see if it alleviates the problem. I think if the computer AI has more players to work with, then the training problem (and fielding pct of .000) won't be a major issue. That is, if training players occur, then it occurs at the minor league level where the fielding results aren't an issue.