The framework being used was developed for Google DeepMind's AlphaStar, which is a learning AI approach although obviously very different from their approach to chess.

But today the framework is used by rules-based bots largely competing against each other. This means unlike AlphaStar, which set out specifically with a human-like approach to beat excellent human players, the amateur bots are entirely focused on winning versus other bots by any means necessary. The most successful tend to have sprawling multi-theatre conflict as their end game, maximum army size, and a half dozen or more different small skirmishes happening at once, hard for the human observer to be sure who is better until suddenly there's a decisive outcome. That wouldn't be compatible with AlphaStar's mission at all, obviously human players can't fight these battles with success.

Their most obvious defect is they don't resign. A competent human player resigns hopeless positions in SC2 knowing quickly that they have lost, but most bots will stay in the game until destroyed which would be very rude for a human. They can be indecisive, attacking then pulling back, then attacking again in seconds, and they are much more easily thrown off by unexpected situations than a human - but overall they're a match for a good human player unless that player has prepared specifically to exploit a known weakness of a particular bot. (e.g. there are bots that do not understand why an enemy Nydus Worm in your base can't be allowed to complete... since that basically never happens)