New player evaluation algorythms
The core of the AI in a baseball game is it's player evaluation algorythm.
We have used modern reasearch and player evaluation concepts (i.e. value over replacement players) in order to rework
the player evaluation in OOTP 6.5, resulting in smarter AI throughout the game. This influences trades, signings and
basic roster AI, for example lineups or pitching staff settings.
Smarter roster handling AI
The new roster handling AI does not only benefit from the new player evaluation,
it was almost completely reworked and now feels more realistic, resulting in less waiver moves and a better understanding
of the roster structure.
New team focus
In previous versions, teams did not really understand their position in the league and therefore
did not adjust their free agent signings or trades to the state of the organization. Now teams have a focus, which is
either 'normal', 'win now' or 'rebuild'. This focus influences the trading as well as roster AI. Teams which are rebuilding
may give their rookies more playing time and may trade ageing players when they are out of the pennant race early in
the season. 'Win now'-teams may trade a prospect or two in order to get an established player for the final push for the
playoffs.
Player popularity
Players now have a national and local popularity rating, which has impact on the team if
the player leaves or gets added to it. If you sign a very popular superstar, your fan interest may get a boost. But
if you trade one of your most popular local players, fans may may be upset and stay home.
Modified player development algorythms
Player development is also one of the most important parts of a career
baseball game. We have further enhanced the algorythms of OOTP so that the game now offers even more variation in career
curves and more realism overall.
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