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Two suggestions to improve Matchmaking

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  • Two suggestions to improve Matchmaking

    1. New player experience through learning queue based on statistics from played matches

    New players pick a hero they want to play/read about/practiced with bots/are comfortable, and then queue up with that hero regardless of draft, think most new players have no clue about drafting or understand enough about heroes to draft properly so its irrelevant anyway.

    A way to make it work would be to build a relevant sample from recently played ranked games with same hero combination that were balanced for both sides at similar skill levels, then new players could "replay" the same match by picking one of the heroes.

    These premade games would be offered to new players and change regularly depending on actual played games to accompany the meta.

    Example:
    1. Week 1 looking at the database of <1k mmr games the most balanced games played were team pairings X Y and Z, each XYZ means a matchup of 5 heroes in 5 specific roles that were played against other 5 heroes in 5 roles n times, resulting on average on balanced games.
    2. New players can play a "learning queue" during Week 2 where they pick one of the available 10 heroes for specific positions and queue as such.

    Maybe we could have same heroes on different combinations of teams and positions (eg two different teams with sniper playing with and against different heroes and on different roles) again depends on the statistical significance of how balanced the games were (on average of 1000 games, does this specific matchup result in a balanced game? how significantly?). The number of possible combinations offered each week depends on how good the stats are which in turn depends on how large the game pool is, don't have the numbers. I don't know how many games happen in a week with each exact combination maybe the sample is too small to be significant, then we can extend sampling period for a month instead.

    I would keep this off mmr and just for new players only as a learning experience where they can just read and play a hero and don't worry about drafting.

    Matchmaking time will be shorter assuming a significant number of players are interested in this game mode since they would be corraled into playing the same 10 heroes, can adjust number of offered team combinations & corresponding available hero pool size to accommodate this. If the statistics are not very significant everyone has the same combination for a month, if not maybe n combinations can be offered.

    2. Hero based mmr adjustment by auto banning

    People smurf because they want to play at lower skill levels with heroes they are not used to spamming and use it to practice new heroes. This relates to the problem mmr is in reality hero related for most of the player base and your mmr doesn't capture hero skill level assymetries.

    The way I see it each player has an mmr value that resulted from all the matches he played with different heroes (lets not consider recalibration) so in a sense each played match with a given hero contributed to the current mmr in the proportion of games played with that hero versus total number of games played. Maybe win rates with some heroes are higher than with others, but for most of the heroes the win rates are going to be around 50% by design so total number of games played should be a good enough proxy.

    My suggestion is that on the hero screen before queuing players can pre ban heroes in secret, when they do this their mmr will be adjusted downwards by the proportion of games played with that hero versus his overall total of games played with all heroes. When the player queues up for a game with heroes prebanned he will then queue at a lower mmr, note none of his opponents know about this and they can still ban the hero again. This has to be calibrated with numbers to introduce a limit, need statistics to check for any given player, on average, how worse is he on less played heroes than with more played heroes.

    On the hero screen (the one with all the heroes on the home screen, not after queuing up) there would be a box with your current mmr and by banning heroes it would go lower so you would know by how much you were lowering your mmr by preventing yourself in advance from playing those heroes, maybe we could show a % total of games played with all heroes and by removing heroes it would go down by the % of games played with that hero.

    Example: a player has 1000 mmr and 100 games, 90 with sniper 1 with 10 other different heroes. Prebannning sniper will adjust his mmr downward by the maximum extent possible (tbd), prebanning any other of the 10 heroes will adjust his mmr downward by 1%, prebanning all the other heroes will adjust his mmr downward by 10%, prebanning any other hero will have no impact - making it linear but it should be a curve that levels as we approach the max value that has to be calibrated with actual stats.

    What I haven't figured out, assuming any of the above makes sense, is how to treat mmr adjustment post game. It seems obvious that if you lose you should still lose mmr to make the game count, further considering you had the advantage of playing at a lower mmr. If you win, however, I don't think you should win the same amount of mmr as if you were playing with all the heroes at your actual mmr. Maybe adjust the mmr increase by the % of games with heroes that were still available in the pool and not prebanned versus overall total games played.

    Example, continued: if you lose you get less 30 mmr, if you win your mmr increase is adjusted to 10% only gain if you banned sniper (+3), 90% if you banned all heroes but sniper (+27). Note that the mmr adjustment compensates the mmr increase, if you don't ban sniper you get +27 mmr but the lowered mmr amount is also very small so in practice you will be playing at your current mmr almost.

    Hope that was clear, think prebanning to lower mmr can work don't know about the mmr gain/loss math though.
    Last edited by 2d34dly4u; 02-05-2021, 04:35 PM.
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