Loading...
  OR  Zero-K Name:    Password:   

Post edit history

Zero-K v1.9.6.5 - Handicap and Matchmaking Experiment

To display differences between versions, select one or more edits in the list using checkboxes and click "diff selected"
Post edit history
Date Editor Before After
6/30/2021 2:39:23 PMAUrankAdminGoogleFrog before revert after revert
Before After
1 I have watched the 1v1s of the past few days and tweaked the handicap numbers. Games at the top of the ladder were interesting in that sometimes they would have economic parity while the player with the bonus built up an army advantage, and sometimes the player with the bonus would run away economically. In both cases the bonus seemed far too large and has been halved. 1 I have watched the 1v1s of the past few days and tweaked the handicap numbers. Games at the top of the ladder were interesting in that sometimes they would have economic parity while the player with the bonus built up an army advantage, and sometimes the player with the bonus would run away economically. In both cases the bonus seemed far too large and has been halved.
2 \n 2 \n
3 Games at the lower end of of the ladder were quite chaotic, mostly depending on whether the skillset of the players lined up with using the bonus. The bonus here has also been slighted reduced. Most of the halving of the bonus happens between games where the lower player is rated from 1500 to 2000. 3 Games at the lower end of of the ladder were quite chaotic, mostly depending on whether the skillset of the players lined up with using the bonus. The bonus here has also been slighted reduced. Most of the halving of the bonus happens between games where the lower player is rated from 1500 to 2000.
4 \n 4 \n
5 I also widened the definition of "1v1 Narrow" from an effective gap of 270 to 330. To put this in perspective, for games from this year: 5 I also widened the definition of "1v1 Narrow" from an effective gap of 270 to 330. To put this in perspective, for games from this year:
6 * 62.6% were matches within 270 elo. 6 * 62.6% were matches within 270 elo.
7 * 12.8% of matches outside 270 elo were won by lower rated player. 7 * 12.8% of matches outside 270 elo were won by lower rated player.
8 * 73.2% were matches within 330 elo 8 * 73.2% were matches within 330 elo
9 * 11.1% of matches outside 330 elo won by lower rated player. 9 * 11.1% of matches outside 330 elo won by lower rated player.
10 \n 10 \n
11 The UI also auto-joins people who click "1v1" into "1v1 Narrow" as the former should be a superset of the latter. 11 The UI also auto-joins people who click "1v1" into "1v1 Narrow" as the former should be a superset of the latter.
12 \n 12 \n
13 = Zero-K v1. 9. 6. 5 = 13 = Zero-K v1. 9. 6. 7 =
14 * "1v1 Narrow" range 17.5% win chance -> 13% win chance (matching range 270 -> 330). 14 * "1v1 Narrow" range 17.5% win chance -> 13% win chance (matching range 270 -> 330).
15 * Handicaps tweaked as per the lists below. They are now dependant on the rating of the lower rated player. 15 * Handicaps tweaked as per the lists below. They are now dependant on the rating of the lower rated player.
16 * Clicking "1v1" also selects "1v1 Narrow". 16 * Clicking "1v1" also selects "1v1 Narrow".
17 * Fixed Azure Rampart Shadows. 17 * Fixed Azure Rampart Shadows.
18 * Gunship descriptions now refer to Locust rather than Banshee. 18 * Gunship descriptions now refer to Locust rather than Banshee.
19 \n 19 \n
20 The previous win prediction to handicap function was as follows: 20 The previous win prediction to handicap function was as follows:
21 * 15% to 17.5% -> 1.15 handicap. 21 * 15% to 17.5% -> 1.15 handicap.
22 * 10% to 15% -> 1.2 handicap. 22 * 10% to 15% -> 1.2 handicap.
23 * 5% to 10% -> 1.25 handicap. 23 * 5% to 10% -> 1.25 handicap.
24 * 0% to 5% -> 1.3 handicap. 24 * 0% to 5% -> 1.3 handicap.
25 \n 25 \n
26 Now when the lower rated player has at most 1500 elo: 26 Now when the lower rated player has at most 1500 elo:
27 * 10% to 13% -> 1.15 handicap. 27 * 10% to 13% -> 1.15 handicap.
28 * 5% to 10% -> 1.2 handicap. 28 * 5% to 10% -> 1.2 handicap.
29 * 0% to 5% -> 1.25 handicap. 29 * 0% to 5% -> 1.25 handicap.
30 \n 30 \n
31 The winrate thresholds are scaled down to 2/3 as the elo of the lower rated player rises from 1500 to 2000. This uses the 15% -> 20% bracket that technically exists at 1500: 31 The winrate thresholds are scaled down to 2/3 as the elo of the lower rated player rises from 1500 to 2000. This uses the 15% -> 20% bracket that technically exists at 1500:
32 * 10% to 13% -> 1.1 handicap. 32 * 10% to 13% -> 1.1 handicap.
33 * 6.6% to 10% -> 1.15 handicap. 33 * 6.6% to 10% -> 1.15 handicap.
34 * 3.3% to 6.6% -> 1.2 handicap. 34 * 3.3% to 6.6% -> 1.2 handicap.
35 \n 35 \n
36 The thresholds are then shifted down by 2% as the lower rating rises from 2000 to 2500, ending up at: 36 The thresholds are then shifted down by 2% as the lower rating rises from 2000 to 2500, ending up at:
37 * 8% to 13% -> 1.1 handicap. 37 * 8% to 13% -> 1.1 handicap.
38 * 4.6% to 8% -> 1.15 handicap. 38 * 4.6% to 8% -> 1.15 handicap.
39 * 1.3% to 4.6% -> 1.2 handicap. 39 * 1.3% to 4.6% -> 1.2 handicap.