[Mindless]

The only difference between my system and yours is that:

A) It doesn't limit who's allowed to battle who.

B) Doesn't add a bunch of code for a matchmaking system. We already have random battling. All you have to do is drop an open.

C) Only gives a number rank instead of a class and a number rank.

Did you bother to look at the pseudo code I posted? It's based on the ELO system which, again, uses points to determine classes. My formula is a simplified one based on the Estimated Skill Level of the battler (Something we already have that can be modified and is based on the ratings battlers get in battles.), as well as their current rank, w/l record and EloPoints (Which would determine their class if there were classes in the system) to determine how points are distributed to battlers who win. Which is exactly what an Elo system does.

Also, you must not understand what I'm saying if you don't get the law of diminishing returns. So I'll use your class names in my example so you can get it.

A person signs up for LB and is bronze. He battles bronze battlers and wins enough to become silver. He continues to battle bronze battlers. His w/l ratio goes up but as it does the number of points he gains from battling bronze battlers goes down because with every win the points value of taking on those bronze battlers decreases. Why? Because of this part of the algorithm after the part that makes a prediction about which battler will win based on a score created from the users stats:

    DetermineRankChange = {
    if Winner was predicted {
    pointModifier = LoserPredictionScore - WinnerPredictionScore;
    pointSubtraction = map(pointModifier, 0, currentUserCount, 0, 32)
    ELOAdded = MaxEloChange - pointSubtraction
}

If bronze sniper has a prediction score of 100 and new person has a prediction score of 3 the amount of points they would get would be 0 after we map the point modifier (-97) to the maximum point change range. (Mapping, in case you don't know is assigning one range of numbers to another. An example would be to assign 0-100 to 0-10 by having one represent ten, two twenty, three thirty, and so on and so forth.)

So, let's assume he does what you say and battles a hundred bronze level battlers. We set the max change at a range of -32 through 32 points. In my system, and I'm not going to extrapolate exactly here but, I don't think he gets past maybe 20 or 30 wins before it starts to not do anything significant for him and because he'd have started with 1 point, by the time he hits that amount he's still not moved up the rankings but a few spots.

[Mindless]

The only difference between my system and yours is that:

A) It doesn't limit who's allowed to battle who.

B) Doesn't add a bunch of code for a matchmaking system. We already have random battling. All you have to do is drop an open.

C) Only gives a number rank instead of a class and a number rank.

Did you bother to look at the pseudo code I posted? It's based on the ELO system which, again, uses points to determine classes. My formula is a simplified one based on the Estimated Skill Level of the battler (Something we already have that can be modified and is based on the ratings battlers get in battles.), as well as their current rank, w/l record and EloPoints (Which would determine their class if there were classes in the system) to determine how points are distributed to battlers who win. Which is exactly what an Elo system does.

Also, you must not understand what I'm saying if you don't get the law of diminishing returns. So I'll use your class names in my example so you can get it.

A person signs up for LB and is bronze. He battles bronze battlers and wins enough to become silver. He continues to battle bronze battlers. His w/l ratio goes up but as it does the number of points he gains from battling bronze battlers goes down because with every win the points value of taking on those bronze battlers decreases. Why? Because of this part of the algorithm after the part that makes a prediction about which battler will win based on a score created from the users stats:

    DetermineRankChange = {
    if Winner was predicted {
    pointModifier = LoserPredictionScore - WinnerPredictionScore;
    pointSubtraction = map(pointModifier, 0, currentUserCount, 0, 32)
    ELOAdded = MaxEloChange - pointSubtraction
}

If bronze sniper has a prediction score of 100 and new person has a prediction score of 3 the amount of points they would get would be 0 after we map the point modifier (-97) to the maximum point change range. (Mapping, in case you don't know is assigning one range of numbers to another. An example would be to assign 0-100 to 0-10 by having one represent ten, two twenty, three thirty, and so on and so forth.)

So, let's assume he does what you say and battles a hundred bronze level battlers. We set the max change at a range of -32 through 32 points. In my system, and I'm not going to extrapolate exactly here but, I don't think he gets past maybe 20 or 30 wins before it starts to not do anything significant for him and because he'd have started with 1 point, by the time he hits that amount he's still not moved up the rankings but a few spots.