War.app Wiki - User contributions [en]

User:84.10.210.79

2012-01-22T15:48:18Z

84.10.210.79:

It's me, when I forget to log in --[[User:Grzechooo|Grzechooo]] 13:07, 11 August 2011 (BST)
:Confirming --[[Special:Contributions/84.10.210.79|84.10.210.79]] 13:07, 11 August 2011 (BST)
::I can also try to spam a bit, to check if the spamfilters/CAPTCHA/whatever is good --[[Special:Contributions/84.10.210.79|84.10.210.79]] 15:48, 22 January 2012 (UTC)

Combat Basics

2011-08-21T15:49:57Z

84.10.210.79: /* Note */

The attack system is very simple. Each army that attacks has a 60% chance at killing one defending army. If all the defending armies are killed, the territory is captured and all the attacking armies move to occupy the destination territory.

For example, if you attack with 10, you will kill, on average, 6 armies. This is why you generally want to attack with at least double the number of armies the defender has.

Defenders also get an opportunity to kill attacking armies. Each defending army has a 70% chance at killing one of the attacking armies.

Generally, you always want to have overwhelming numbers in every battle you participate in. Clearly, however, this isn't always possible, so you must pick and choose your fights to make the most effective use of your armies.

==Example 1==
15 armies attack a territory that has 6 armies.
The attacking 15 armies could have killed between 0 and 15, but on average they will kill 9 (60% of 15). Let's say they kill 9 armies.
The defenders could kill between 0 and 6 of the attacking 15 armies, but on average they will kill 4 or 5 (70% of 6). Let's say they kill 5 armies.
5 of the attacking armies die and all 6 of the defending armies die. Since all the defenders died, the remaining 10 attacking armies take control of the defending territory.

==Example 2==
25 armies attack a territory that has 20 armies.
The attacking 25 armies could have killed between 0 and 25, but on average they will kill 15 (60% of 25). Let's say they kill 15 armies.
The defenders could kill between 0 and 20 of the attacking 25 armies, but on average they will kill 14 (70% of 20). Let's say they kill 15 armies.
15 of the attacking armies die and 15 of the defending armies die. Since 5 defenders lived, the territory is not captured. The remaining 10 attacking armies retreat back to their territory of origin.

==Note==
The calculations on this page assume that the game's luck modifier is set to 100%. To see how the [[Luck Modifier|luck modifier]] changes the calculations, see the [[Luck Modifier|Luck Modifier Page]]. Also, the [[offense and defense kill rates]] can be overridden by game creators, so check the settings on your game to be sure.

==Analyze==
Within the game, WarLight supplies an Analyze function. This function can be accessed when attacks/transfers are defined (Phase 2 of a turn) by pressing the Analyze button of the Attacks/Transfers - pop-up window and shows how probable it is for an attack to succeed. This function takes the luck modifier into account.

For example, in a game with following settings:

75% luck / 60% attack kill rate / 70% defense kill rate (default settings)

* attack with '''3''' troops on a neutral with 2 troops succeeds with '''69%''' probability
* attack with '''4''' troops on a neutral with 2 troops succeeds with '''88%''' probability
* attack with '''5''' troops on a neutral with 2 troops succeeds with '''95%''' probability
* you need at least '''8''' troops to attack a neutral to get a '''100%''' probability of success

==See Also==
* [[Luck Modifier]]
* [[Offense and defense kill rates]]

[[Category:Gameplay]]

User:84.10.210.79

2011-08-11T12:07:59Z

84.10.210.79:

It's me, when I forget to log in --[[User:Grzechooo|Grzechooo]] 13:07, 11 August 2011 (BST)
:Confirming --[[Special:Contributions/84.10.210.79|84.10.210.79]] 13:07, 11 August 2011 (BST)

Medium Earth Traditional

2011-08-11T10:56:36Z

84.10.210.79: /* Advanced tips */

The Strategic 1 v 1 [[Templates|template]] is one of the built-in templates to WarLight. This template attempts to be produce the best settings for a two-player heads-up duel.

These are the same settings used by the [[1 v 1 Ladder]].

==Territory Distribution==

This template uses the [[Random Warlords and Random Cities|Random Warlords]] distribution option, which means that the territories available for distribution will be different for each game. Further, the use of [[wastelands]] ensures that the map is sufficiently randomized that a one-size-fits-all strategy is not possible.

Here is an example of a possible map distribution using the Strategic 1 v 1 template:

http://blog.warlight.net/Images/ImpallerPicks0.png

In this setup, note that the green territories (one per bonus) are the ones available for starting. Each neutral starts with 2, except for the [[wastelands]] which start with 10. Further, any green territories that neither player starts in will be replaced by a 4 - these are called cities.

==Newbie Tips==

* You'll want to pick 6 territories. Picking beyond 6 doesn't do anything, and picking fewer than 6 could cause you to get random territories, which is always bad.
* Try to get your first bonus as quickly as possible. While the big +5 bonuses may look tempting, you'll be better off if you can take a smaller bonus faster and then use its income to take bigger ones.
* Don't attack wastelands. Expanding as efficiently as possible is key, and spending armies on wastelands that could be spent elsewhere is inefficient.
* Don't start in a bonus that has a wasteland. The bonuses you start in will be the cheapest to take, so by starting in a bonus with a wasteland you're removing that efficiency.
* Although your early bonuses can be taken faster when picks are close to each other, it is usually recommended to keep your options open and try start in bonuses which lie pretty far from each other. This helps ensure that you can expand safely somewhere far from early battles as much as possible.
* Make sure to use the [[Analyze Tool]] to check the odds of your attacks. These games use a 16% luck level, which means that 2v1s and 4v2s are guaranteed wins. New players sometimes think they need to attack 1s with 3s or 2s with 5s just to be sure they win, but this isn't necessary at the 16% luck level.

==Advanced tips==
===Picking territories===
* Always take at least one easy bonus that is somewhat protected (two or more turns away from the enemy). You assume that your opponent will want the same spot, so pick it as your first pick.
* Your second and third picks could be a balance between: easy bonuses, territories that will prevent your opponent to get a bonus that you expect him to choose.
* Through your picks, you can figure out where your opponent is. It matters to stop one minute at the beginning and come up with a strategy to get the combat going in your opponent's border, not yours.
* It is worth picking two warlords that are so close together that you can get a bonus in the first round. That happens in Africa and Asia, mostly. The only problem is that it might make you vulnerable, if your opponent expects you to choose that strategy.

===Combat===
* Try to figure out as fast as possible your opponent's income. That information will allow you to choose between an offensive or defensive strategy.
* Most of the time, it is worth growing - either slowly or quickly - even if you are fighting your opponent. It increases your income and gives you cards.

==See also==

* [[Ladders]]
* [[1 v 1 Ladder]]
* [[Templates]]

[[Category:Templates]]

Bayeselo

2011-08-09T11:46:26Z

84.10.210.79: Undo revision 353 by 84.10.210.79 (talk)

WarLight uses an ELO rating system, similar to what is used in Chess.

==How Ranks and Ratings are calculated==

More specifically, WarLight uses Bayesian Elo Rating, which has several advantages over other ELO rating systems:
* Beating the same opponent multiple times gives you more rating than beating them once. In most ELO systems, only a win or loss is considered for each opponent.
* This system allows giving an advantage to players that pick first, as described above.
* Bayeselo behaves correctly when opponents' ratings are far apart
* Ratings are calculated based on final ratings, not just what the rating was when the game took place.

The exact algorithm used by this tool is documented on their page, and is not repeated here. The source code is also available for the truly nerdy.

==Run your own Ladder Simulations==

You can run your own ladder simulations which help to understand how the ratings are calculated. This can be used to answer questions like:

* How would the ratings be different if I had won versus X instead of lost?
* How would the ratings change if I win or lose this in-progress game?
* How would the ratings be different if first-pick advantage was higher or lower?

Here’s the process to re-produce the current rankings:

* Download Bayeselo.exe from [http://remi.coulom.free.fr/Bayesian-Elo/ remi.coulom.free.fr].
* Download BayeseloLog.txt from the links below. This file is automatically generated each time the ladder updates and contains all of the commands needed to re-produce the current ladder rankings.
* Run Bayeselo.exe. You’ll be left at a prompt that says
ResultSet>

* Copy the entire contents of BayeseloLog.txt to your clipboard, and paste it into the Bayeselo application. (Note: To paste into a console app on windows, you can right-click on the titlebar, select Edit then Paste)

BayeseloLog can be obtained separately for each ladder. Here are the links:

1v1 ladder: http://warlight.net/Data/BayeseloLog0.txt

2v2 ladder: http://warlight.net/Data/BayeseloLog1.txt

This will produce rankings like the following:

Rank Name Elo + - games score oppo. draws
1 Waya 303 457 341 1 100% 179 0%
2 Fizzer 302 412 285 2 100% 115 0%
3 Soyrice 218 297 240 2 100% 87 0%
4 FBGDragons 181 494 353 1 100% 52 0%
5 NoZone 179 219 235 3 33% 220 0%
6 FBGMoDogg 110 326 421 1 0% 218 0%
7 Ruthless 83 410 281 2 100% -99 0%
8 GuyMannington 65 311 312 2 50% 45 0%
9 deweylikedonuts 55 304 304 2 50% 59 0%
10 Perrin3088 52 222 217 5 60% -45 0%
11 sue 50 457 340 1 100% -69 0%
...

==Making changes==

Now that you can re-produce the existing ladder rankings, you can try making changes and seeing how they affect the results. Here’s the process:

* First, ensure you are on the “ResultSet>” prompt. If you’re in “ResultSet-EloRating>”, enter a command of just “x” to go back up one.
* Enter the command “reset” to clear the previous results. This ensures you’re starting from a clean slate.
* Modify BayeseloLog.txt depending on what you want to try (see below).
* Copy/paste the modified BayeseloLog.txt back into Bayeselo.exe to see the results. Compare to your previous run to see how they changed. In BayeseloLog.txt, you’ll find two large sections – first, a bunch of addplayer commands, then a bunch of addresult commands.

==Players==

Each addplayer line corresponds to a player participating (or that has participated at one time) in the ladder. They are also numbered, starting at zero and going up.

addplayer Fizzer ;0
addplayer Knoebber ;1
addplayer FBGDragons ;2
addplayer CuChulainn ;3
...
addplayer Perrin3088 ;7
...

==Results==

After the players, there are a bunch of addresult commands. Each addresult corresponds to one finished ladder game. In these numbers, we tell Bayeselo what two players fought eachother, who got first pick, and who won. Let’s examine this in detail.

addresult 0 7 2
addresult 1 4 2
addresult 2 7 2
addresult 3 7 0
addresult 4 18 0
...

http://blog.warlight.net/images/addresult.png

By changing these, you can simulate new wins/losses or change existing games to see how they would affect the results.

=See Also=

* [[Ladders]]

[[Category:Ladders]]

Bayeselo

2011-08-09T11:39:13Z

84.10.210.79: /* Run your own Ladder Simulations */

WarLight uses an ELO rating system, similar to what is used in Chess.

==How Ranks and Ratings are calculated==

More specifically, WarLight uses Bayesian Elo Rating, which has several advantages over other ELO rating systems:
* Beating the same opponent multiple times gives you more rating than beating them once. In most ELO systems, only a win or loss is considered for each opponent.
* This system allows giving an advantage to players that pick first, as described above.
* Bayeselo behaves correctly when opponents' ratings are far apart
* Ratings are calculated based on final ratings, not just what the rating was when the game took place.

The exact algorithm used by this tool is documented on their page, and is not repeated here. The source code is also available for the truly nerdy.

==Run your own Ladder Simulations==

You can run your own ladder simulations which help to understand how the ratings are calculated. This can be used to answer questions like:

* How would the ratings be different if I had won versus X instead of lost?
* How would the ratings change if I win or lose this in-progress game?
* How would the ratings be different if first-pick advantage was higher or lower?

Here's the process to re-produce the current rankings:

* Download Bayeselo.exe from [http://remi.coulom.free.fr/Bayesian-Elo/ remi.coulom.free.fr].
* Download BayeseloLog.txt from the links below. This file is automatically generated each time the ladder updates and contains all of the commands needed to re-produce the current ladder rankings.
* Run Bayeselo.exe. You’ll be left at a prompt that says
ResultSet>

* Copy the entire contents of BayeseloLog.txt to your clipboard, and paste it into the Bayeselo application. (Note: To paste into a console app on Windows, you can right-click on the titlebar, select Edit then Paste)

BayeseloLog can be obtained separately for each ladder. Here are the links:

1v1 ladder: http://warlight.net/Data/BayeseloLog0.txt

2v2 ladder: http://warlight.net/Data/BayeseloLog1.txt

This will produce rankings like the following:

Rank Name Elo + - games score oppo. draws
1 TheImpaller 2087 196 150 20 85% 1792 0%
2 Heyheuhei 2027 100 88 58 79% 1776 0%
3 zaeban 1991 123 109 37 73% 1779 0%
4 chas 1990 267 229 6 67% 1884 0%
5 bostonfred 1966 145 122 32 78% 1713 0%
6 Oliebol 1947 126 114 33 70% 1768 0%
7 Troll 1945 176 158 14 64% 1842 0%
8 gilgamesz 1910 270 233 6 67% 1796 0%
9 TypeSomething 1880 175 152 18 72% 1690 0%
10 Fizzer 1875 138 129 23 61% 1788 0%
11 MathWolf 1872 119 107 38 71% 1686 0%
...

==Making changes==

Now that you can re-produce the existing ladder rankings, you can try making changes and seeing how they affect the results. Here’s the process:

* First, ensure you are on the “ResultSet>” prompt. If you’re in “ResultSet-EloRating>”, enter a command of just “x” to go back up one.
* Enter the command “reset” to clear the previous results. This ensures you’re starting from a clean slate.
* Modify BayeseloLog.txt depending on what you want to try (see below).
* Copy/paste the modified BayeseloLog.txt back into Bayeselo.exe to see the results. Compare to your previous run to see how they changed. In BayeseloLog.txt, you’ll find two large sections – first, a bunch of addplayer commands, then a bunch of addresult commands.

==Players==

Each addplayer line corresponds to a player participating (or that has participated at one time) in the ladder. They are also numbered, starting at zero and going up.

addplayer Fizzer ;0
addplayer Knoebber ;1
addplayer FBGDragons ;2
addplayer CuChulainn ;3
...
addplayer Perrin3088 ;7
...

==Results==

After the players, there are a bunch of addresult commands. Each addresult corresponds to one finished ladder game. In these numbers, we tell Bayeselo what two players fought eachother, who got first pick, and who won. Let’s examine this in detail.

addresult 0 7 2
addresult 1 4 2
addresult 2 7 2
addresult 3 7 0
addresult 4 18 0
...

http://blog.warlight.net/images/addresult.png

By changing these, you can simulate new wins/losses or change existing games to see how they would affect the results.

=See Also=

* [[Ladders]]

[[Category:Ladders]]