The Elo rating system has some weaknesses that can make it unsuited to Forged Alliance. For example, ELO is unable to rate anything but 1 vs 1 matches.
ELO is only really capable of rating of even team games, such as 2v2, it cannot properly weight a Free For All or a team game with more than two sides. Each team will be considered as a single player, so that the leader board will show a result for each pair of player, for every pair that ever exists.
TrueSkill however, can handle any match up. Teams are the weighted sum of the players inside, and results are correctly calculated from the team result to the players in the teams. It can easily handle FFA, 2vs2vs2 and so on.
The ELO system handles draws differently from Trueskill. For Elo, a draw is simply a half-win half-lost game.
TrueSkill measures a drawn outcome very differently Each map has a draw percentage based of all of the outcomes of games played on that map. TrueSkill considers draws as a meaningful outcome : You were matched with a equally skilled opponent.
But Let's considers two players with the same skill.
On a map where draws are more unlikely, a draw game will lead to no difference in skill, but the system is learning the player better (actual skills are accurate - see below). That result will also increase the overall draw probability for that map.
However, on a map like "Winter Duel" for example, where draws are a more likely outcome a draw is expected as result, so the skill won't move, but the system doesn't know the players better, so that game is meaningless compared the "normal" map case. That result will also increase the draw probability on Winter Duel.
Now let's say that player 1 wins.
On the "normal" map, the player will gain points, for example's sake say a gain +4 points, and the loser receives a penalty of -4. That result will decrease the draw probability on that map.
Now, on the Winter Duel map as draw was a more likely outcome, the fact that player 1 wow means that's he is actually significantly better than his opponent. As a result his rating will be revised upwards, so instead of +4, he will gain +6, and the loser -6 for example. That result will then decrease the draw probability on Winter Duel.
Elo systems can have a tendency to inflate over time. Because it's only comparing 2 players' ratings to determine an new rating, a better player who plays often will gain more and more points over time. For example, at the beginning of the GPGnet ranked ladder the top 10 players were rated around 1900. Presently the highest ranked player is around 2700. Does that means that their skill is increasing ? Maybe. But not that much. The rating increase because, as all good top tier players, they plays often. And as they are goods, they win games, and gain points, increase the rating over time.
To combat inflation, ELO system has a "K-Factor", limiting the maximum points a player win or loss per game. GPGNet used a K-Factor of 30. In the Chess leaderboard the K factor depends of the rating of the player (A 2400+ players got a K-Factor of 16 where a newer player got 32). That's arbitrary, not accurate and only artificially decrease the inflation problem. 
Trueskill is less susceptible to inflation. When you start a game, TrueSkill calculates the possible -and probable- outcome of the game : it estimates what are your chances of winning.
Let's say it predicts that you will win that game.
If you win the game, as it was the expected outcome, you will gain points depending of the "chances of ranking" factor (itself depending of the difference in skill between players, and the outcome probability). If you lose the game, as an unexpected result, you will lose more points. On paper, it sounds a lot like Elo, but the algorithms behind are more evolved, and once you reach your real rating, unless you play really badly or improve a lot, you will stay at that rank.
This graph represents a trueSkill rating for a selection of football teams. As you can see, team 1 is the best, and their rank stays stable. Team 5 had a bad start (you lost your first games), and were badly rated. Over time, TrueSkill manage to correct that and find a stable skill. Team 2 is the most interesting case : It's a new team, really good. At start, it was rated way under their real skill. You can see how fast the system was able to determine their correct rating. One of the advantages of Trueskill is that it can determine your correct rating very quickly.
TrueSkill can rate ANY game. That's why ANY custom game or ranked will contribute to your skill rating. TrueSKill can lower the impact of your result : A FFA is less meaningful than a 1v1, so the outcome of a FFA will contribute less.
The number you see in the leaderboards is an approximation of your real rating.
What this means is that two players with the same rating can in reality perform at different skill levels. At this time we are displaying the approximation - you can see the actual distribution by right clicking on your name in the player list and selecting View Player Statistics.
In reality, your rating is a Gaussian bell curve.
It's comprised of two values : Your mean and your deviation.
It sounds complicated (which is why we haven't shown them to you yet) but it's easy to understand.
Don't be intimidated by the graphs, the concept is actually very simple.
The mean represent your maximum skill/rating. The system thinks that it cannot be higher than that. Trueskill believes at your current skill level, you can't perform at an higher level, but possibly also at a lower one. Technically speaking, for a real-valued random variable X, the mean is the expectation of X. For more information on the maths behind this, visit Wikipedia.
The standard deviation is the "uncertainty" factor. The bigger it is, the higher your possible real rating is. Standard deviation is a widely used measure of variability or diversity used in statistics and probability theory. It shows how much variation or "dispersion" exists from the average (mean, or expected value)
The mean is often quoted along with the standard deviation: the mean describes the central location of the data, and the standard deviation describes the spread.
Let's take the value of a new player. By default, you have 1500 in mean, and 500 in deviation. 1500 is the average level.
When you join, the system predicts you will perform as average (1500). However, as you can see on the curve, the probability that you will perform at either 1000 or 2000 is still very high.
Quite simply, the system doesn't have enough data to accurately predict your level of performance & thus you have a high level of deviation or, uncertainty.
Let's use the values of a higher rated player as an example.
The mean is 2189 and the deviation is 56.8 (after 500 games).
As you can see, the system predicts they will perform between 2150 and 2250. A performance higher or lower than that is considered statistically unlikely.
Now let's examine a random player after 30 games.
Mean = 1188 deviation = 91
That player is below the statistical average. Trueskill thinks that his rating is between 1100 and 1300. As before, Truskill thinks it's statistically unlikely that they will perform higher or lower than that.
It's a simple mathematic formula : Rating = Mean - 3 * deviation. (meaning 0 at start).
That's a very simple representation, and should be pondered by the number of games of the players : Under 30, it's not meaningful.
Why we are using that ? It's a conservative estimate value. With a rating of 1200, it means that you probably perform higher than 1200, but unlikely under 1200.
So by checking that number, you can be sure that the player has all the chances to perform at least to a certain level, and probably best.
"Before" the game, Trueskill is "betting" on a particular outcome. If you have 90% chances of winning, and win, it means that your current rating is correct, and therefore doesn't require adjusting. But your deviation will decrease as the system is now more statistically certain of your actual rating.
But if it "bet" a 40% probability of losing and you win, that means that your rating need to be adjusted as it's probably wrong. Your deviation will still decrease (as any additional data is valuable), but not a lot.
In conclusion, you won't gain points for winning games that you should win, or lose points for games that you are unlikely to win. This is why the TrueSkill system doesn't suffer from inflation.
Before each game, the server is adding more deviation to your score. It's not supposed to happen, but it's there to reflect the fact that you are not a robot, and add more dynamism to the ladder. What can happen in very balance games or very unbalanced ones, is this :
As your rating is Mean - 3 * deviation, and your mean doesn't move a lot while your deviation slightly increase, the result is a lower rating.
It doesn't mean that you lose points. Your mean will still be increased correctly. When this happen, it can be a 1 or 2 points decrease maximum. It's not meaningful.
Remember that trueskill is supposed to put you at your right place, once determined, you won't move a lot. So you can't always gain points for a victory ! Once you reach your rank, your rating won't move a lot. This is perfectly normal.
Each team is the sum of each player rating. You can think that it's not true, because some members of the team probably work harder than others.
Additionally, sometimes special dynamics occur that make the sum greater than the parts.
But it will be impossible to take these in considerations. Instead, Trueskill follow one rule :
“Statistically sophisticated or complex methods do not necessarily provide more accurate forecasts than simpler ones”
At the end of the game, the result of the team is propagated to your personal rating. Meaning that a teammate can gain a lot from a game while you don't gain anything.
At first, your deviation is so high that your rating is meaningless.
That also mean that in your first games, your rating can be very "jumpy" or very low/high for no good reason. This is totally normal, as your deviation will have more importance than your mean (Mean - 3 * deviation, higher the deviation, higher the "jumpiness").
Your deviation is decreasing after each game, no matter what (maybe a lot, maybe not, that depend of the relevance of that game).
After 30-40 games, the system "learn" you, and your rating starts to make sense.
Computing Your Skill]“ – Moserware
40% doesn't mean that the game will be awful. 5% means it.
You maybe want to read the conclusion too.
The game balance index is a representation of how well the teams in your match are balanced, according to the current team composition.
In a x Vs x situation :
An index, of 1 (100%) means that both teams have an equal chance of winning the game.
An index of 0 ( 0% ) means that one team have statistically no chance of winning. This is a non-zero probability but extremely unlikely.
First, because of what is explained here : How Trueskill works.
Two players with the same visual rating can have very different mean and deviations values.
But even two players with the exact same mean and deviation won't get you a 100% balance rating !
If the deviation is high, the chances that your "mean" is correct is low. (your deviation is reflected by the color of your rating in the lobby. Whiter = closer to your real rating)
As a new player :
In a 1v1, two players with that graph can perform between/around 1000 or 2000. Meaning that possibly, we are matching a 1100 rated players against a 1700 rated player !
As we don't know, the game balance is pondered. That kind of match-up will result in a game quality factor of 44%.
With two players with these values (Mean = 1188, deviation = 91, after 30 games), the game quality would be 94%.
As the values are pondered by the deviation of each players, the game quality index can be used in a reliable way to determine if the game is balanced or not.
But it's only a simple representation of it, it doesn't mean that a game rated 20% will be horrible to play, there are many others factors, unknown by the system :
So don't judge if a game should be play or not by that index. It's only there to help you determine the overall balance in a totally random situation!
It's recommended that you follow Widely Accepted Guidelines when balancing team games.
You must first understand what that index really is.
It's the probability of getting a draw for all participants.
It uses a skill chain to do it.
You can think of beta as the number of points to guarantee about an 80% chance of winning.
The skill chain is composed of the worst player/team on the far left and the best player/team on the far right.
Each subsequent person on the skill chain is “beta” points better and has an 80% win probability against the weaker player.
So, to have a high Game quality in that case, each player/team should have a low beta difference in each link. (meaning that every player has high chances to get a draw from another player).
FAF uses a real rating system for each and every game. This system gives a real-time rating of all players who have participated in custom and/or ladder FAF games. A players' score depends on his in- game performance; good performance leads to increased rating, while poor performance causes a drop in rating. You can find your exact rating here, but keep in mind, a high rating does not mean you're good, but you may have a high rating because you're good.
Only Custom Games affect global rating. TMM matches affected 1v1 and global rating for a while, but now 1v1 games affect a different rating only, your "Ladder rating"
Generally, all standard games are rated, but a few exceptions exist:
You can access TMM (1v1) ranking from the Leaderboards tab, but only players who played a TMM game in the last two months are shown there. You can also see the approximate Global Ranking in the chat, when hovering over the icon of a user in the list.
You can see the global rating of any player next to his nickname in the FA lobby.