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@Riot - changes that realy are needed about this game

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Adrenalotr

Senior Member

02-02-2015

I think Riot are rather bad at addressing problems in Champ Select, and I've made no secret of this (http://forums.eune.leagueoflegends.com/board/showthread.php?t=685396).

But that's not the whole answer. You are, because everyone is, suffering from negativity bias, where we remember negative experiences better than positive ones. You are statistically likely to benefit more from leavers and other problematic players, and over a large enough number of games, this will show.

You also have no idea, most of the time, what your opponents are going through. They might be having similar issues. While this doesn't really make the overall situation better, your problems are balanced by problems on the enemy team.

Riot punishes people _after_ they've done something bad. Not before. And not every disagreement about positions is punishable, nor every instance of offensive language, since a lot of them can come out of generally well-behaved players simply having a bad day. Riot isn't interested in punishing those players unless they find that there's some improvement to be had. Where there _is_ improvement to be had, Riot does warn and punish, and for downright toxic players, they aren't afraid of banning players and all known alt accounts of theirs.

That there's little feedback as to the results of reports, and little information available as to what becomes of these reports in terms of improved behavior or removed players. That's definitely something Riot could improve.


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Celebloth

Senior Member

02-02-2015

Lyte said in one of the videos, that they know that the draft pick (I think either for normal or ranked) needs a bit of time adjustment, and should be increased, not as much as for the team builder though.

And MMR is invisible, as far as I know what LOLKing writes out is not actually your real MMR. Correct me if I know it wrong.

You can't possibly win all your normal matches, unless you play a very few. I mostly play normal drafts, and hell, it is 50-50, more or less.

Riot wants to reform players, not taking them out of the game, aka banning them. And this new leaver buster system is severly punishing those who do it in ranked games.
As for those guys who are not able to change, they are issuing short term bans or permabans.


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Lamcho

Junior Member

02-03-2015

I'm currently in so low tear that i can win easily 90% of the games 5v5, hell even couple of 4v5, but guess what, i just had my 4th promo match and guess what for 3rd time in a row we ware 4v5, so please tell me where are your statistics now? What are the chances a player having 4 out of 10 games afk in placement matches and in 3 out of 4 games in division promo, how so i'm not the only one that is happening to, how so last year I had a division promo with 3 afks out of 5 games again, and i was able to win next one just because there ware only 2 afks, guess what i didn't play for 5 months after that, and guess what I'm taking my next promo and i'm not cumming back for at least 5 months again. This game is pure poison.

Imagine that all the enemy team is get boosted for free, so they are many players that experience the opposite of my experience, they get boosted to a level that they can not compete with and they start to get crushed, they start to get angry they are crushed even harder, than they drag down with them other players, the other players get angry too and flame.
All players that are graded down start dominating the games, i had a games that i can solo vs 2 players on the enemy team at early the levels, so their team start to flame hard at them, they become aggressive and lose even harder, they get mad and start flaming in their games, meanwhile their team gets punished and my team get boosted without deserving it, players that are dragged too low buy afks and other similar evens also boost their teams and it all becomes such mess that nobody is on his right place.

May be you will tell me that statistically this "noise" will auto correct itself with the time but, i do not agree! How many ranked games an average LoL player play per season? 100 games, 200 games.. 300 games, may be after 2000 games you have a semi-good chance but the hell who plays 6 ranked games EVERY single day?

I've experienced many games silver vs diamond, hell i've even seen some silver vs masters games where the lower tier was dominating or equal which should not be possible at all.
I keep my pinon that the system is too broken to work for much more and predict that we are at the downfall of LoL.


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Lamcho

Junior Member

02-03-2015

Just after i did my previous i started writing a script that calculates the fowling:
- You have the categories from bronze to diamond
- You have pool of players (100'000 in my tests)
- You make them all play equal number of games (200 in my tests)
- You assigns skill value to every category, for the purpose of the test we will greatly exaggerate players skills assigning 1 to bronze, 2 to silver, .. 5 to diamond. i.e. team of 5 bronze players is equal to team of 1 diamond player, 2 silvers are equal to bronze and gold ant etc.
- All players start with the same elo points.
- All players are grouped in pairs of teams in such way, that the teams in each pair have as close as possible elo that can be found in certain elo range.
- A game is "simulated" in each pair, The simulation is the flowing:
* the team with larger skill sum wins (note that ELO rating is not included in any calculations)
* if both teams have equal skill sum it is randomly decided which team wins (both have 50%, 50% chance)
* each team have X% chance to have an AFK player, if it have it, their skill sum is reduced by 20%.
* each team have Y% chance to have troll player (or not fully functioning player), if they have it, their skill sum is reduced by 5%
- After the matches all players have their ELO points updated by flat amount subtracted added depending on lose / win.
- Players are paired in teams again, and the loops go on for as many iterations entered.
- After all N matches have been played for every player all of then are sorted by their ELO value, and divided in the described divisions (for example you you had 100 positions for diamond at start the 100 player will highest elo will be placed there, if you had 1000 positions for bronze the 1000 players with lowest elo will be placed and so on for every division).
- The new position for every person is reviewed and compared to his skill. (The skill that match calculations depend on) This rules should describe much stable system than LoL ladders system, however after running many simulations here are the results:
- Placement in low tiers (bronze, silver, gold) is getting worse when increase AFKs, Trolls and surprisingly played games.
- Placement in high tiers (platinum, diamond) is improving when increase played games, AFKs & Trolls have low impact.

The numbers:
I've used some stats from last year for people / division distribution:
Bronze - 47900,
Silver - 42100,
Gold - 7500,
Platinum - 1900,
Diamond - 600

If you consider you will have only 1 AFK every 20 games (i wish..) and 1 Troll every 20 games and every player makes 200 games you get that you have estimated correctly about 75% (most simulations ware actually lower percentage) of the players in your game.
26% (12682 people) of all people in Bronze are not supposed to be here but they are.
28% (11744) are not supposed to be in Silver (Some of them are from Bronze, Gold and Plat)
7% (544) are not supposed to be in Gold.
6% (119) in Patinum
2% (13) in Diamond

If you pump up the AFKs and Trolls up to 1 every 5 games you end up with numbers around 30 - 35% for bronze and silver, 10 - 12% in gold and plat and diamond stay almost the same. Overall there are about 20-28% of the people displaced incorrectly (up or down) only with 1 division and 2-5% displaced with 2 or more, however 2% of 10,462,982 (all ranked players) are 209,260 people. The simulation do not consider into effect thinks like tilting, anger, frustration and etc.
In conclusion, to have a good time in the game you need to be Korean with lots of free time.


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Adrenalotr

Senior Member

02-04-2015

Awesome, someone else who does simulations and math experiments.

Quote:
Lamcho:
Just after i did my previous i started writing a script that calculates the fowling:
- You have the categories from bronze to diamond
- You have pool of players (100'000 in my tests)
- You make them all play equal number of games (200 in my tests)
- You assigns skill value to every category, for the purpose of the test we will greatly exaggerate players skills assigning 1 to bronze, 2 to silver, .. 5 to diamond. i.e. team of 5 bronze players is equal to team of 1 diamond player, 2 silvers are equal to bronze and gold ant etc.
- All players start with the same elo points.
- All players are grouped in pairs of teams in such way, that the teams in each pair have as close as possible elo that can be found in certain elo range.
- A game is "simulated" in each pair, The simulation is the flowing:
* the team with larger skill sum wins (note that ELO rating is not included in any calculations)
* if both teams have equal skill sum it is randomly decided which team wins (both have 50%, 50% chance)
* each team have X% chance to have an AFK player, if it have it, their skill sum is reduced by 20%.
* each team have Y% chance to have troll player (or not fully functioning player), if they have it, their skill sum is reduced by 5%
- After the matches all players have their ELO points updated by flat amount subtracted added depending on lose / win.
- Players are paired in teams again, and the loops go on for as many iterations entered.
- After all N matches have been played for every player all of then are sorted by their ELO value, and divided in the described divisions (for example you you had 100 positions for diamond at start the 100 player will highest elo will be placed there, if you had 1000 positions for bronze the 1000 players with lowest elo will be placed and so on for every division).
- The new position for every person is reviewed and compared to his skill. (The skill that match calculations depend on) This rules should describe much stable system than LoL ladders system, however after running many simulations here are the results:
- Placement in low tiers (bronze, silver, gold) is getting worse when increase AFKs, Trolls and surprisingly played games.
- Placement in high tiers (platinum, diamond) is improving when increase played games, AFKs & Trolls have low impact.

The numbers:
I've used some stats from last year for people / division distribution:
Bronze - 47900,
Silver - 42100,
Gold - 7500,
Platinum - 1900,
Diamond - 600

If you consider you will have only 1 AFK every 20 games (i wish..) and 1 Troll every 20 games and every player makes 200 games you get that you have estimated correctly about 75% (most simulations ware actually lower percentage) of the players in your game.
26% (12682 people) of all people in Bronze are not supposed to be here but they are.
28% (11744) are not supposed to be in Silver (Some of them are from Bronze, Gold and Plat)
7% (544) are not supposed to be in Gold.
6% (119) in Patinum
2% (13) in Diamond

If you pump up the AFKs and Trolls up to 1 every 5 games you end up with numbers around 30 - 35% for bronze and silver, 10 - 12% in gold and plat and diamond stay almost the same. Overall there are about 20-28% of the people displaced incorrectly (up or down) only with 1 division and 2-5% displaced with 2 or more, however 2% of 10,462,982 (all ranked players) are 209,260 people. The simulation do not consider into effect thinks like tilting, anger, frustration and etc.
In conclusion, to have a good time in the game you need to be Korean with lots of free time.


You're not taking in to account that a player may be excellent on one champion in one position, but completely inept at others. I don't think that should matter in this simulation since flexibility could just be part of the "skill" stat, but it's a variable that might change things. As is the ability to work together when there's three players who want the same position.

200 games might not be enough. I played around 300 games last season, and I think I could still have climbed a few divisions if I had played more.

Your system of assigning integer skill values to players might skew the stats. I don't think there are Diamond players who belong in Bronze and vice versa, not in your simulation nor in the game for real, but there might be low Silvers in high Bronze and vice versa, which would look no different in the numbers of players who aren't where they belong.

I don't think the 20% reduction of skill sum is a good approximation of what an afk does to a game. Rather, I would just ignore the afker's contribution to the skill sum entirely.

A "troll player" can be anything from an intentional feeder to a Twisted Fate adc. I think you should use different categories of "trolls", from the types that effectively turn the game into a 4v6, the ones who take something experimental that didn't work out, and the ones who take something unconventional that the enemy team doesn't know how to deal with. These would all potentially (and erroneously) be called trolls.

Your simulation is more in-depth than mine, and I'd really like to see the code behind it.


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Lamcho

Junior Member

02-04-2015

Quote:
You're not taking in to account that a player may be excellent on one champion in one position, but completely inept at others. I don't think that should matter in this simulation since flexibility could just be part of the "skill" stat, but it's a variable that might change things. As is the ability to work together when there's three players who want the same position.

Quote:
Your system of assigning integer skill values to players might skew the stats.

You are right all this things are done to simplify the concept, therefore better differentiate the players. I can easily add more parameters to be taken into consideration but that will make the data even more fuzzy and the elo error even bigger.
AFKs effect on the game is greatly reduced to make certain that the statistics we get are aways better than these in the real game.


Quote:
Your system of assigning integer skill values to players might skew the stats. I don't think there are Diamond players who belong in Bronze and vice versa, not in your simulation nor in the game for real, but there might be low Silvers in high Bronze and vice versa, which would look no different in the numbers of players who aren't where they belong.

All players having the same skill also makes the chance for statistical error smaller, if there are players with float skill values (1.134, 1.4634, 3.14, 4.72 etc.) that will cause players with less skill to drop even easier there fore the elo error bigger.

Based on that i assume that in Bronze, Silver and Gold in real life there are nearly 50% percent chance you are in the wrong division but that's just my assumption, however the numbers above (in my previous post) can not be ever reached by the LoL system, the error will away be bigger, hate will always be generated and so on, the only way out of the situation is better skill evaluation you can not have normal system based only on WIN / LOSE scenario.


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Adrenalotr

Senior Member

02-05-2015

Quote:
Lamcho:
All players having the same skill also makes the chance for statistical error smaller, if there are players with float skill values (1.134, 1.4634, 3.14, 4.72 etc.) that will cause players with less skill to drop even easier there fore the elo error bigger.


All players in a tier having the same skill doesn't, imo, make the chance for statistical error smaller, since it's not representative of the players in the actual game. MMR and rank are a continuum, not stepwise tiers. A player with skill equivalent to an MMR to 1200 is more skilled than one with 1170.

Quote:
Based on that i assume that in Bronze, Silver and Gold in real life there are nearly 50% percent chance you are in the wrong division but that's just my assumption, however the numbers above (in my previous post) can not be ever reached by the LoL system, the error will away be bigger, hate will always be generated and so on, the only way out of the situation is better skill evaluation you can not have normal system based only on WIN / LOSE scenario.


I disagree. With a continuum of skills (floats rather than integers), you can't have players who barely or nearly made it to another tier skew the stats. You can then calculate how far from their true MMR they are, rather than how many aren't in the tier they belong.

I might try to simulate this myself. We'll see.


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Lamcho

Junior Member

02-05-2015

I tried using float values for the players skill just for the sake of it, as i expected even when troll & afk coefficients are 0 the system start generating some noise, but when i turn them back on to normal the percentages grow

Not in bronze 16553 35%
Not in silver 15207 36%
Not in gold 865 12%
Not in patinum 74 4%
Not in diamond 25 4%


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Adrenalotr

Senior Member

02-05-2015

I was expecting this change to make the system more accurate. Interesting.

How many of the players in Bronze belong to Gold or higher?

What happens if you do 300 games instead of 200?

Are the afk and trolling instances applied to games or to players?


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Lamcho

Junior Member

02-05-2015

According to my results 2308 out of 47'900 (4.81%) that should be in bronze are in fact in gold, however each simulation varies with up to ±0.5%.
I tried all of your suggestions, calculated AKFs and trolls to be personal, went even over 500+ games per person and still nothing can balance the system.

The system clears out the noise only if i bump the reward/penalty to be 20% of the opposite team elo rating, which can not work ever because in couple of matches you can go from bronze to diamond and back to bronze.

I suggest someone else to do a simulation independent from mine, so we can compare the numbers.