### Weng-Lin Quickstart Example

Source: https://docs.rs/skillratings/0.28.2/skillratings/weng_lin/index.html

A basic example demonstrating how to initialize player ratings, define match outcomes, configure the Weng-Lin algorithm, and calculate updated ratings.

```APIDOC
## Rust Quickstart Example

### Description
This example shows the fundamental usage of the Weng-Lin module for updating player ratings after a match.

### Method
Illustrative code, not a direct API call.

### Endpoint
N/A (Local computation)

### Parameters
N/A (Illustrative code)

### Request Example
```rust
use skillratings::{
    weng_lin::{weng_lin, WengLinConfig, WengLinRating},
    Outcomes,
};

// Initialise a new player rating with default values.
let player_one = WengLinRating::new();

// Initialise another player rating with custom values.
let (some_rating, some_uncertainty) = (41.2, 2.12);
let player_two = WengLinRating { 
    rating: some_rating,
    uncertainty: some_uncertainty,
};

// Define the outcome from player one's perspective.
let outcome = Outcomes::WIN;

// Configure Weng-Lin parameters, customizing beta.
let config = WengLinConfig {
    beta: 25.0 / 12.0,
    ..Default::default()
};

// Calculate the new ratings for both players.
let (new_player_one, new_player_two) = weng_lin(&player_one, &player_two, &outcome, &config);
```

### Response
#### Success Response (200)
Returns updated `WengLinRating` for both players.

#### Response Example
```rust
// The result of the weng_lin function is a tuple of the updated ratings:
// let (new_player_one, new_player_two): (WengLinRating, WengLinRating)
```
```

--------------------------------

### TrueSkill Module Quickstart

Source: https://docs.rs/skillratings/0.28.2/skillratings/trueskill/index.html

A basic example demonstrating how to initialize player ratings, define match outcomes, configure TrueSkill parameters, and calculate new ratings.

```APIDOC
## Module trueskill

### Description
The TrueSkill rating algorithm, developed by Microsoft for Halo 3. Used in various Xbox Live games, it's designed for online games with multiple teams and players. TrueSkill uses a normal distribution (skill rating μ and uncertainty σ) to represent player skill, similar to Glicko and Glicko-2, and is efficient at assessing skill levels quickly.

**Caution:** TrueSkill is patented. For commercial projects, consider alternative algorithms like the Weng-Lin algorithm.

### Quickstart Example

This example shows the basic usage of the TrueSkill module.

```rust
use skillratings::{
    trueskill::{trueskill, TrueSkillConfig, TrueSkillRating},
    Outcomes,
};

// Initialise a new player rating with default values (rating: 25, uncertainty: 8.33).
let player_one = TrueSkillRating::new();

// Initialize with custom values (e.g., from a database).
let (some_rating, some_uncertainty) = (34.2, 2.3);
let player_two = TrueSkillRating {
    rating: some_rating,
    uncertainty: some_uncertainty,
};

// Define the outcome of the match from player one's perspective.
let outcome = Outcomes::WIN;

// Configure TrueSkill parameters. Here, draw probability is set to 0.05 (5%).
// Adjust this value based on the game's draw frequency.
let config = TrueSkillConfig {
    draw_probability: 0.05,
    ..Default::default()
};

// Calculate the new ratings for both players.
let (new_player_one, new_player_two) = trueskill(&player_one, &player_two, &outcome, &config);
```

### Key Components

*   **TrueSkillRating**: Represents a player's skill level with a rating (μ) and uncertainty (σ).
*   **TrueSkillConfig**: Allows customization of TrueSkill calculation parameters, such as `draw_probability`.
*   **trueskill function**: Computes the updated ratings based on match results and configuration.
*   **Outcomes enum**: Represents the possible results of a match (e.g., WIN, LOSS, DRAW).
```

--------------------------------

### DWZ Module - Quickstart Example

Source: https://docs.rs/skillratings/0.28.2/skillratings/dwz/index.html

A basic example demonstrating how to initialize DWZ ratings for two players and calculate the outcome of a match using the `dwz` function.

```APIDOC
## DWZ Module - Quickstart Example

This is the most basic example on how to use the DWZ Module. Please take a look at the functions below to see more advanced use cases.

```rust
use skillratings::{
    dwz::{dwz, DWZRating},
    Outcomes,
};

// Initialise a new player rating.
// We need to set the actual age for the player,
// if you are unsure what to set here, choose something that is greater than 25.
let player_one = DWZRating::new(19);

// Or you can initialise it with your own values of course.
// Imagine these numbers being pulled from a database.
// The default rating is 1000, and the index denotes the amount of tournaments played.
let (some_rating, some_index, some_age) = (1325.0, 51, 27);
let player_two = DWZRating {
    rating: some_rating,
    index: some_index,
    age: some_age,
};

// The outcome of the match is from the perspective of player one.
let outcome = Outcomes::WIN;

// The dwz function will calculate the new ratings for both players and return them.
let (new_player_one, new_player_two) = dwz(&player_one, &player_two, &outcome);
```
```

--------------------------------

### Sticko Algorithm Quickstart

Source: https://docs.rs/skillratings/0.28.2/skillratings/sticko/index.html

A basic example demonstrating how to initialize player ratings, define match outcomes, configure Sticko parameters, and calculate new ratings.

```APIDOC
## Sticko Algorithm Quickstart

This is the most basic example on how to use the Sticko Module. Please take a look at the functions below to see more advanced use cases.

```rust
use skillratings::{
    sticko::{sticko, StickoConfig, StickoRating},
    Outcomes,
};

// Initialise a new player rating with a rating of 1500 and a deviation of 350.
let player_one = StickoRating::new();

// Or you can initialise it with your own values of course.
// Imagine these numbers being pulled from a database.
let (some_rating, some_deviation) = (1325.0, 230.0);
let player_two = StickoRating {
    rating: some_rating,
    deviation: some_deviation,
};

// The outcome of the match is from the perspective of player one.
let outcome = Outcomes::WIN;

// The config allows you to specify certain values in the Sticko calculation.
// For more information on how to customise the config, please check out the StickoConfig struct.
let config = StickoConfig {
    // The gamma value describes the advantage of player_one.
    // 30.0 is roughly accurate for playing White in Chess.
    // If player_two was to play White, change this to -30.0.
    // By default it is set to 0.0.
    gamma: 30.0,
    // We leave the other settings at their default values.
    ..Default::default()
};

// The sticko function will calculate the new ratings for both players and return them.
let (new_player_one, new_player_two) = sticko(&player_one, &player_two, &outcome, &config);
```
```

--------------------------------

### Install skillratings via Cargo

Source: https://docs.rs/skillratings

Commands to add the crate to a Rust project.

```bash
cargo add skillratings
```

```toml
[dependencies]
skillratings = "0.28"
```

--------------------------------

### WengLin Rating System Implementation

Source: https://docs.rs/skillratings/0.28.2/skillratings/trait.RatingPeriodSystem.html

Example implementation of RatingPeriodSystem for the WengLin rating system. It uses WengLinRating for ratings and WengLinConfig for configuration.

```rust
type RATING = WengLinRating;
    type CONFIG = WengLinConfig;
```

--------------------------------

### TrueSkill Rating System Implementation

Source: https://docs.rs/skillratings/0.28.2/skillratings/trait.RatingPeriodSystem.html

Example implementation of RatingPeriodSystem for the TrueSkill rating system. It uses TrueSkillRating for ratings and TrueSkillConfig for configuration.

```rust
type RATING = TrueSkillRating;
    type CONFIG = TrueSkillConfig;
```

--------------------------------

### Initialize and Use TrueSkill Rating

Source: https://docs.rs/skillratings/0.28.2/skillratings/trueskill/index.html

Demonstrates basic initialization of player ratings, custom configuration, and calculating new ratings after a match outcome. Use this for a quick start with the TrueSkill algorithm.

```rust
use skillratings::{
    trueskill::{trueskill, TrueSkillConfig, TrueSkillRating},
    Outcomes,
};

// Initialise a new player rating with a rating of 25, and an uncertainty of 25/3 ≈ 8.33.
let player_one = TrueSkillRating::new();

// Or you can initialise it with your own values of course.
// Imagine these numbers being pulled from a database.
let (some_rating, some_uncertainty) = (34.2, 2.3);
let player_two = TrueSkillRating {
    rating: some_rating,
    uncertainty: some_uncertainty,
};

// The outcome of the match is from the perspective of player one.
let outcome = Outcomes::WIN;

// The config allows you to specify certain values in the TrueSkill calculation.
// We set the draw probability to 0.05 (5%) instead of the default 0.1 (10%).
// This means that in our game, draws will be very rare to occur.
// Change this value to reflect the outcomes of your game.
// For example in chess, it might be a good idea to increase this value.
// For more information on how to customise the config,
// please check out the TrueSkillConfig struct.
let config = TrueSkillConfig {
    draw_probability: 0.05,
    ..Default::default()
};

// The trueskill function will calculate the new ratings for both players and return them.
let (new_player_one, new_player_two) = trueskill(&player_one, &player_two, &outcome, &config);
```

--------------------------------

### Sticko Rating System Implementation

Source: https://docs.rs/skillratings/0.28.2/skillratings/trait.RatingPeriodSystem.html

Example implementation of RatingPeriodSystem for the Sticko rating system. It uses StickoRating for ratings and StickoConfig for configuration.

```rust
type RATING = StickoRating;
    type CONFIG = StickoConfig;
```

--------------------------------

### DWZ Rating System Implementation

Source: https://docs.rs/skillratings/0.28.2/skillratings/trait.RatingPeriodSystem.html

Example implementation of RatingPeriodSystem for the DWZ rating system. It uses DWZRating for ratings and requires no specific configuration.

```rust
type RATING = DWZRating;
    type CONFIG = ();
```

--------------------------------

### Ingo Rating System Implementation

Source: https://docs.rs/skillratings/0.28.2/skillratings/trait.RatingPeriodSystem.html

Example implementation of RatingPeriodSystem for the Ingo rating system. It uses IngoRating for ratings and requires no specific configuration.

```rust
type RATING = IngoRating;
    type CONFIG = ();
```

--------------------------------

### Elo Rating System Implementation

Source: https://docs.rs/skillratings/0.28.2/skillratings/trait.RatingPeriodSystem.html

Example implementation of RatingPeriodSystem for the Elo rating system. It uses EloRating for ratings and EloConfig for configuration.

```rust
type RATING = EloRating;
    type CONFIG = EloConfig;
```

--------------------------------

### skillratings::dwz::get_first_dwz

Source: https://docs.rs/skillratings/0.28.2/skillratings/dwz/fn.get_first_dwz.html

Gets a proper first DWZRating. In the case that you do not have enough opponents to rate a player against, consider using DWZRating::from() if you have an EloRating or DWZRating::new() if not. Takes in the player’s age and their results as a Slice of tuples containing the opponent and the outcome. If the actual player’s age is unavailable or unknown, choose something >25.

```APIDOC
## GET skillratings::dwz::get_first_dwz

### Description
Gets a proper first `DWZRating`.
In the case that you do not have enough opponents to rate a player against, consider using `DWZRating::from()` if you have an `EloRating` or `DWZRating::new()` if not.
Takes in the player’s age and their results as a Slice of tuples containing the opponent and the outcome. If the actual player’s age is unavailable or unknown, choose something `>25`.

### Method
GET

### Endpoint
/skillratings/dwz/get_first_dwz

### Parameters
#### Query Parameters
- **player_age** (usize) - Required - The player's age.
- **results** (array of tuples) - Required - A slice of tuples containing the opponent's `DWZRating` and the `Outcomes` of the game.

### Response
#### Success Response (200)
- **DWZRating** - The calculated `DWZRating` for the player.

#### Error Response
- **GetFirstDWZError::NotEnoughGames** - Returned if the player has played less than 5 games.
- **GetFirstDWZError::InvalidWinRate** - Returned if the player has a winrate of either 0% or 100%.

### Request Example
```json
{
  "player_age": 26,
  "results": [
    {"opponent": {"rating": 1300.0, "index": 23, "age": 17}, "outcome": "WIN"},
    {"opponent": {"rating": 1540.0, "index": 2, "age": 29}, "outcome": "DRAW"},
    {"opponent": {"rating": 1200.0, "index": 10, "age": 7}, "outcome": "LOSS"},
    {"opponent": {"rating": 1290.0, "index": 76, "age": 55}, "outcome": "WIN"},
    {"opponent": {"rating": 1400.0, "index": 103, "age": 11}, "outcome": "WIN"}
  ]
}
```

### Response Example
```json
{
  "rating": 1491.0,
  "index": 1,
  "age": 26
}
```
```

--------------------------------

### Glicko2 Rating System Implementation

Source: https://docs.rs/skillratings/0.28.2/skillratings/trait.RatingPeriodSystem.html

Example implementation of RatingPeriodSystem for the Glicko2 rating system. It uses Glicko2Rating for ratings and Glicko2Config for configuration.

```rust
type RATING = Glicko2Rating;
    type CONFIG = Glicko2Config;
```

--------------------------------

### Calculate Multi-Team TrueSkill Ratings

Source: https://docs.rs/skillratings/0.28.2/skillratings/trueskill/fn.trueskill_multi_team.html

Example demonstrating how to define teams, assign ranks, apply player weights, and calculate new ratings using trueskill_multi_team.

```rust
use skillratings::{
    trueskill::{trueskill_multi_team, TrueSkillConfig, TrueSkillRating},
    MultiTeamOutcome,
};

let team_one = vec![
    TrueSkillRating::new(),
    TrueSkillRating {
        rating: 30.0,
        uncertainty: 1.2,
    },
    TrueSkillRating {
        rating: 21.0,
        uncertainty: 6.5,
    },
];

let team_two = vec![
    TrueSkillRating::default(),
    TrueSkillRating {
        rating: 41.0,
        uncertainty: 1.4,
    },
    TrueSkillRating {
        rating: 19.2,
        uncertainty: 4.3,
    },
];

let team_three = vec![
    TrueSkillRating::default(),
    TrueSkillRating {
        rating: 29.4,
        uncertainty: 1.6,
    },
    TrueSkillRating {
        rating: 17.2,
        uncertainty: 2.1,
    },
];

let teams_and_ranks = vec![
    (&team_one[..], MultiTeamOutcome::new(2)), // Team 1 takes the second place.
    (&team_two[..], MultiTeamOutcome::new(1)), // Team 2 takes the first place.
    (&team_three[..], MultiTeamOutcome::new(3)), // Team 3 takes the third place.
];

let weights: &[&[f64]] = &[
    &[1.0, 1.0, 0.5], // Player 3 left halfway through the match
    &[1.0, 0.9, 1.0], // Player 2 left close to the end
    &[1.0, 1.0, 1.0],
];

let new_teams = trueskill_multi_team(&teams_and_ranks, &TrueSkillConfig::new(), Some(&weights)).unwrap();

assert_eq!(new_teams.len(), 3);

let new_one = &new_teams[0];
let new_two = &new_teams[1];
let new_three = &new_teams[2];

assert!((new_one[0].rating - 28.180_576_928_436_55).abs() < f64::EPSILON);
assert!((new_one[1].rating - 30.066_263_874_493_455).abs() < f64::EPSILON);
assert!((new_one[2].rating - 21.967_593_771_099_708).abs() < f64::EPSILON);

assert!((new_two[0].rating - 27.657_276_377_119_9).abs() < f64::EPSILON);
assert!((new_two[1].rating - 41.067_731_453_349_65).abs() < f64::EPSILON);
assert!((new_two[2].rating - 19.907_710_735_630_584).abs() < f64::EPSILON);

assert!((new_three[0].rating - 19.162_146_694_443_58).abs() < f64::EPSILON);
assert!((new_three[1].rating - 29.184_231_167_296_68).abs() < f64::EPSILON);
assert!((new_three[2].rating - 16.828_726_305_722_817).abs() < f64::EPSILON);
```

--------------------------------

### Calculate TrueSkill ratings for 3v3

Source: https://docs.rs/skillratings

Example of calculating new ratings for two teams in a team-based match using the TrueSkill algorithm.

```rust
use skillratings::{
    trueskill::{trueskill_two_teams, TrueSkillConfig, TrueSkillRating},
    Outcomes,
};

// We initialise Team One as a Vec of multiple TrueSkillRatings.
// The default values for the rating are: 25, 25/3 ≈ 8.33.
let team_one = vec![
    TrueSkillRating {
        rating: 33.3,
        uncertainty: 3.3,
    },
    TrueSkillRating {
        rating: 25.1,
        uncertainty: 1.2,
    },
    TrueSkillRating {
        rating: 43.2,
        uncertainty: 2.0,
    },
];

// Team Two will be made up of 3 new players, for simplicity.
// Note that teams do not necessarily have to be the same size.
let team_two = vec![
    TrueSkillRating::new(),
    TrueSkillRating::new(),
    TrueSkillRating::new(),
];

// The outcome of the match is from the perspective of team one.
let outcome = Outcomes::LOSS;

// The config allows you to specify certain values in the TrueSkill calculation.
let config = TrueSkillConfig::new();

// The trueskill_two_teams function will calculate the new ratings for both teams and return them.
let (new_team_one, new_team_two) = trueskill_two_teams(&team_one, &team_two, &outcome, &config);

// The rating of the first player on team one decreased by around ~1.2 points.
assert_eq!(new_team_one[0].rating.round(), 32.0);
```

--------------------------------

### Glicko Rating System Implementation

Source: https://docs.rs/skillratings/0.28.2/skillratings/trait.RatingPeriodSystem.html

Example implementation of RatingPeriodSystem for the Glicko rating system. It uses GlickoRating for ratings and GlickoConfig for configuration.

```rust
type RATING = GlickoRating;
    type CONFIG = GlickoConfig;
```

--------------------------------

### USCF Rating System Implementation

Source: https://docs.rs/skillratings/0.28.2/skillratings/trait.RatingPeriodSystem.html

Example implementation of RatingPeriodSystem for the USCF rating system. It uses USCFRating for ratings and USCFConfig for configuration.

```rust
type RATING = USCFRating;
    type CONFIG = USCFConfig;
```

--------------------------------

### Calculate Glicko-2 ratings for 1v1

Source: https://docs.rs/skillratings

Example of calculating new ratings for two players in a 1v1 match using the Glicko-2 algorithm.

```rust
use skillratings::{
    glicko2::{glicko2, Glicko2Config, Glicko2Rating},
    Outcomes,
};

// Initialise a new player rating.
// The default values are: 1500, 350, and 0.06.
let player_one = Glicko2Rating::new();

// Or you can initialise it with your own values of course.
// Imagine these numbers being pulled from a database.
let (some_rating, some_deviation, some_volatility) = (1325.0, 230.0, 0.05932);
let player_two = Glicko2Rating {
    rating: some_rating,
    deviation: some_deviation,
    volatility: some_volatility,
};

// The outcome of the match is from the perspective of player one.
let outcome = Outcomes::WIN;

// The config allows you to specify certain values in the Glicko-2 calculation.
let config = Glicko2Config::new();

// The glicko2 function will calculate the new ratings for both players and return them.
let (new_player_one, new_player_two) = glicko2(&player_one, &player_two, &outcome, &config);

// The first players rating increased by ~112 points.
assert_eq!(new_player_one.rating.round(), 1612.0);
```

--------------------------------

### Fifa Rating System Implementation

Source: https://docs.rs/skillratings/0.28.2/skillratings/trait.RatingPeriodSystem.html

Example implementation of RatingPeriodSystem for the Fifa rating system. It uses FifaRating for ratings and FifaConfig for configuration.

```rust
type RATING = FifaRating;
    type CONFIG = FifaConfig;
```

--------------------------------

### EGF Rating System Implementation

Source: https://docs.rs/skillratings/0.28.2/skillratings/trait.RatingPeriodSystem.html

Example implementation of RatingPeriodSystem for the EGF rating system. It uses EGFRating for ratings and EGFConfig for configuration.

```rust
type RATING = EGFRating;
    type CONFIG = EGFConfig;
```

--------------------------------

### GlickoBoost Rating System Implementation

Source: https://docs.rs/skillratings/0.28.2/skillratings/trait.RatingPeriodSystem.html

Example implementation of RatingPeriodSystem for the GlickoBoost rating system. It uses GlickoBoostRating for ratings and GlickoBoostConfig for configuration.

```rust
type RATING = GlickoBoostRating;
    type CONFIG = GlickoBoostConfig;
```

--------------------------------

### StickoConfig::new()

Source: https://docs.rs/skillratings/0.28.2/skillratings/sticko/struct.StickoConfig.html

Initializes a new StickoConfig with default values.

```APIDOC
## impl StickoConfig

### pub const fn new() -> Self

Initialise a new `StickoConfig` with a h value of `10.0`, a beta value of `0.0`, a lambda value of `2.0` and a gamma value of `0.0`.
```

--------------------------------

### Get Rank Function

Source: https://docs.rs/skillratings/0.28.2/skillratings/trueskill/fn.get_rank.html

Calculates the conservatively estimated rank of a player using their rating and deviation. The recommended scale used for Xbox Live is 0 (lowest, starting value) to 50 (highest).

```APIDOC
## GET /get_rank

### Description
Gets the conservatively estimated rank of a player using their rating and deviation. This is a conservative estimate of player skill, the system is 99% sure the player’s skill is higher than displayed. Takes in a player as a `TrueSkillRating` and returns the rank as an `f64`. The recommended scale used for Xbox Live is 0 (lowest, starting value) to 50 (highest).

### Method
GET

### Endpoint
/get_rank

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
- **player** (TrueSkillRating) - Required - The player's TrueSkillRating object.

### Request Example
```json
{
  "player": {
    "rating": 43.1,
    "uncertainty": 1.92
  }
}
```

### Response
#### Success Response (200)
- **rank** (f64) - The conservatively estimated rank of the player.

#### Response Example
```json
{
  "rank": 37.0
}
```
```

--------------------------------

### Get Player Rank with TrueSkillRating

Source: https://docs.rs/skillratings/0.28.2/skillratings/trueskill/fn.get_rank.html

Use this function to get a conservative estimate of a player's skill rank. The system is 99% sure the player’s skill is higher than the displayed rank. Takes a `TrueSkillRating` and returns the rank as an `f64`. The recommended scale is 0 (lowest) to 50 (highest).

```rust
use skillratings::trueskill::{get_rank, TrueSkillRating};

let new_player = TrueSkillRating::new();
let older_player = TrueSkillRating {
    rating: 43.1,
    uncertainty: 1.92,
};

let new_rank = get_rank(&new_player);
let older_rank = get_rank(&older_player);

assert!((new_rank.round() - 0.0).abs() < f64::EPSILON);
assert!((older_rank.round() - 37.0).abs() < f64::EPSILON);
```

--------------------------------

### Initialize and Use Glicko2 Rating System

Source: https://docs.rs/skillratings/0.28.2/skillratings/glicko2/index.html

Demonstrates basic initialization of Glicko2 ratings for two players and calculating the outcome of a match using a custom configuration. The `tau` value in `Glicko2Config` can be adjusted to influence volatility changes.

```rust
use skillratings::{
    glicko2::{glicko2, Glicko2Config, Glicko2Rating},
    Outcomes,
};

// Initialise a new player rating with a rating of 1500, a deviation of 350 and a volatility of 0.06.
let player_one = Glicko2Rating::new();

// Or you can initialise it with your own values of course.
// Imagine these numbers being pulled from a database.
let (some_rating, some_deviation, some_volatility) = (1325.0, 230.0, 0.05932);
let player_two = Glicko2Rating {
    rating: some_rating,
    deviation: some_deviation,
    volatility: some_volatility,
};

// The outcome of the match is from the perspective of player one.
let outcome = Outcomes::WIN;

// The config allows you to specify certain values in the Glicko-2 calculation.
// Here we set the Tau value to 0.9, instead of the default 0.5.
// This will increase the change in volatility over time.
// According to Mark Glickman, values between 0.3 and 1.2 are reasonable.
// For more information on how to customise the config,
// please check out the Glicko2Config struct.
let config = Glicko2Config {
    tau: 0.9,
    ..Default::default()
};

// The glicko2 function will calculate the new ratings for both players and return them.
let (new_player_one, new_player_two) = glicko2(&player_one, &player_two, &outcome, &config);
```

--------------------------------

### Initialize and Calculate Glicko Ratings

Source: https://docs.rs/skillratings/0.28.2/skillratings/glicko/index.html

Demonstrates basic usage of the Glicko module, including initializing player ratings, defining match outcomes, configuring Glicko parameters, and calculating new ratings. Use this for a quick integration of the Glicko algorithm.

```rust
use skillratings::{
    glicko::{glicko, GlickoConfig, GlickoRating},
    Outcomes,
};

// Initialise a new player rating with a rating of 1500 and a deviation of 350.
let player_one = GlickoRating::new();

// Or you can initialise it with your own values of course.
// Imagine these numbers being pulled from a database.
let (some_rating, some_deviation) = (1325.0, 230.0);
let player_two = GlickoRating {
    rating: some_rating,
    deviation: some_deviation,
};

// The outcome of the match is from the perspective of player one.
let outcome = Outcomes::WIN;

// The config allows you to specify certain values in the Glicko calculation.
// Here we set the c value to 23.75, instead of the default 63.2.
// This will decrease the amount by which rating deviation increases per rating period.
let config = GlickoConfig { c: 23.75 };

// The glicko function will calculate the new ratings for both players and return them.
let (new_player_one, new_player_two) = glicko(&player_one, &player_two, &outcome, &config);

```

--------------------------------

### Get Type ID

Source: https://docs.rs/skillratings/0.28.2/skillratings/dwz/struct.DWZ.html

Retrieves the `TypeId` of the current instance. This is a standard trait implementation.

```rust
fn type_id(&self) -> TypeId
```

--------------------------------

### Get Glicko2Rating Value

Source: https://docs.rs/skillratings/0.28.2/skillratings/glicko2/struct.Glicko2Rating.html

Returns the numerical rating value of the Glicko2Rating. This is the primary skill score.

```rust
fn rating(&self) -> f64
```

--------------------------------

### Get Glicko2Rating Uncertainty

Source: https://docs.rs/skillratings/0.28.2/skillratings/glicko2/struct.Glicko2Rating.html

Returns the uncertainty associated with the Glicko2Rating. If the algorithm does not provide an uncertainty value, this returns None.

```rust
fn uncertainty(&self) -> Option<f64>
```

--------------------------------

### Initialize and Use Weng-Lin Rating

Source: https://docs.rs/skillratings/0.28.2/skillratings/weng_lin/index.html

Demonstrates initializing player ratings, defining match outcomes, configuring Weng-Lin parameters like beta, and calculating new ratings after a game. The beta value influences the impact of rating differences on win probability.

```rust
use skillratings::{
    weng_lin::{weng_lin, WengLinConfig, WengLinRating},
    Outcomes,
};

// Initialise a new player rating with a rating of 25, and an uncertainty of 25/3 ≈ 8.33.
let player_one = WengLinRating::new();

// Or you can initialise it with your own values of course.
// Imagine these numbers being pulled from a database.
let (some_rating, some_uncertainty) = (41.2, 2.12);
let player_two = WengLinRating {
    rating: some_rating,
    uncertainty: some_uncertainty,
};

// The outcome of the match is from the perspective of player one.
let outcome = Outcomes::WIN;

// The config allows you to specify certain values in the Weng-Lin calculation.
// Here we change the beta value from the default of 25 / 6 ≈ 4.167.
// The beta value measures the difference you need in rating points
// to achieve a ~67% win-rate over another player.
// Lower this value if your game is heavily reliant on pure skill,
// or increase it if randomness plays a big factor in the outcome of the game.
// For more information on how to customise the config,
// please check out the WengLinConfig struct.
let config = WengLinConfig {
    beta: 25.0 / 12.0,
    ..Default::default()
};

// The weng_lin function will calculate the new ratings for both players and return them.
let (new_player_one, new_player_two) = weng_lin(&player_one, &player_two, &outcome, &config);
```

--------------------------------

### Get MultiTeamOutcome Rank

Source: https://docs.rs/skillratings/0.28.2/skillratings/struct.MultiTeamOutcome.html

Retrieves the rank associated with this `MultiTeamOutcome` instance. The rank indicates the team's placement in the match.

```rust
pub const fn rank(self) -> usize
```

--------------------------------

### Initialize and Calculate Ingo Ratings

Source: https://docs.rs/skillratings/0.28.2/skillratings/ingo/index.html

Demonstrates how to initialize IngoRating structures and calculate new ratings after a match outcome.

```rust
use skillratings::{
    ingo::{ingo, IngoRating},
    Outcomes,
};

// Initialise a new player rating.
// We need to set the actual age for the player,
// if you are unsure what to set here, choose something that is greater than 25.
let player_one = IngoRating::new(19);

// Or you can initialise it with your own values of course.
// Imagine these numbers being pulled from a database.
// The default rating is 230. Unlike with other algorithms, with Ingo a lower rating is more desirable.
let (some_rating, some_age) = (150.4, 23);
let player_two = IngoRating {
    rating: some_rating,
    age: some_age,
};

// The outcome of the match is from the perspective of player one.
let outcome = Outcomes::WIN;

// The ingo function will calculate the new ratings for both players and return them.
let (new_player_one, new_player_two) = ingo(&player_one, &player_two, &outcome);
```

--------------------------------

### GlickoBoostConfig::new()

Source: https://docs.rs/skillratings/0.28.2/skillratings/glicko_boost/struct.GlickoBoostConfig.html

Initializes a new GlickoBoostConfig with default values.

```APIDOC
## Constructor: GlickoBoostConfig::new()

### Description
Initialise a new `GlickoBoostConfig` with a eta value of 30.0, a k value of 1.96, b values of 0.20139 and 17.5, and alpha values of 5.83733, -1.75374e-04, -7.080124e-05, 0.001733792, 0.00026706.

### Method
`pub const fn new() -> Self`

### Returns
A new `GlickoBoostConfig` instance with default values.

### Example Usage (Conceptual)
```rust
let config = GlickoBoostConfig::new();
```
```

--------------------------------

### IngoRating::new

Source: https://docs.rs/skillratings/0.28.2/skillratings/ingo/struct.IngoRating.html

Initializes a new IngoRating with a default rating of 230.0 and a specified age.

```APIDOC
### impl IngoRating

#### pub const fn new(age: usize) -> Self

Initialise a new `IngoRating` with a rating of 230.0 and the given age. The age is the actual age of the player, if unsure or unavailable set this to `>25`.
```

--------------------------------

### Enable Serde support

Source: https://docs.rs/skillratings

Configuration to enable Serde feature for serialization and deserialization.

```bash
cargo add skillratings --features serde
```

```toml
[dependencies]
skillratings = {version = "0.28", features = ["serde"]}
```

--------------------------------

### Initialize TrueSkillConfig

Source: https://docs.rs/skillratings/0.28.2/skillratings/trueskill/struct.TrueSkillConfig.html

Creates a new TrueSkillConfig with default values for draw probability (0.1), beta (approx. 4.167), and dynamics factor (approx. 0.0833).

```rust
pub fn new() -> Self
```

--------------------------------

### Initialize Rating System

Source: https://docs.rs/skillratings/0.28.2/skillratings/trait.RatingPeriodSystem.html

Implement this method to initialize a rating system with its specific configuration. If no configuration is needed, an empty tuple `()` can be used.

```rust
fn new(config: Self::CONFIG) -> Self;
```

--------------------------------

### Sticko Rating System Methods

Source: https://docs.rs/skillratings/0.28.2/skillratings/sticko/struct.Sticko.html

Methods for initializing the Sticko system, calculating ratings, and determining expected scores.

```APIDOC
## Sticko Rating System

### Description
The Sticko struct allows for the calculation of ratings and expected scores using the StickoRating system.

### Methods
- **new(config: StickoConfig)**: Initializes the rating system with the provided configuration.
- **rate(player: &StickoRating, results: &[(StickoRating, Outcomes)])**: Calculates ratings for a player based on a list of opponents and outcomes.
- **expected_score(player: &StickoRating, opponents: &[StickoRating])**: Calculates the expected win probability (0.0 to 1.0) for a player against a list of opponents.
- **rate(player_one: &StickoRating, player_two: &StickoRating, outcome: &Outcomes)**: Calculates new ratings for two players based on a head-to-head outcome.
- **expected_score(player_one: &StickoRating, player_two: &StickoRating)**: Calculates the expected win probability for two players in a head-to-head match.
```

--------------------------------

### Calculate Weng-Lin ratings for multiple teams

Source: https://docs.rs/skillratings/0.28.2/skillratings/weng_lin/fn.weng_lin_multi_team.html

Demonstrates how to initialize team ratings and calculate new ratings based on their relative ranks.

```rust
use skillratings::{
    weng_lin::{weng_lin_multi_team, WengLinConfig, WengLinRating},
    MultiTeamOutcome,
};

let team_one = vec![
    WengLinRating::new(),
    WengLinRating {
        rating: 30.0,
        uncertainty: 1.2,
    },
    WengLinRating {
        rating: 21.0,
        uncertainty: 6.5,
    },
];

let team_two = vec![
    WengLinRating::default(),
    WengLinRating {
        rating: 41.0,
        uncertainty: 1.4,
    },
    WengLinRating {
        rating: 19.2,
        uncertainty: 4.3,
    },
];

let team_three = vec![
    WengLinRating::default(),
    WengLinRating {
        rating: 29.4,
        uncertainty: 1.6,
    },
    WengLinRating {
        rating: 17.2,
        uncertainty: 2.1,
    },
];

let teams_and_ranks = vec![
    (&team_one[..], MultiTeamOutcome::new(2)), // Team 1 takes the second place.
    (&team_two[..], MultiTeamOutcome::new(1)), // Team 2 takes the first place.
    (&team_three[..], MultiTeamOutcome::new(3)), // Team 3 takes the third place.
];

let new_teams = weng_lin_multi_team(&teams_and_ranks, &WengLinConfig::new());

assert_eq!(new_teams.len(), 3);

let new_one = &new_teams[0];
let new_two = &new_teams[1];
let new_three = &new_teams[2];

assert!(((new_one[0].rating * 100.0).round() - 2538.0).abs() < f64::EPSILON);
assert!(((new_one[1].rating * 100.0).round() - 3001.0).abs() < f64::EPSILON);
assert!(((new_one[2].rating * 100.0).round() - 2123.0).abs() < f64::EPSILON);

assert!(((new_two[0].rating * 100.0).round() - 2796.0).abs() < f64::EPSILON);
assert!(((new_two[1].rating * 100.0).round() - 4108.0).abs() < f64::EPSILON);
assert!(((new_two[2].rating * 100.0).round() - 1999.0).abs() < f64::EPSILON);

assert!(((new_three[0].rating * 100.0).round() - 2166.0).abs() < f64::EPSILON);
assert!(((new_three[1].rating * 100.0).round() - 2928.0).abs() < f64::EPSILON);
assert!(((new_three[2].rating * 100.0).round() - 1699.0).abs() < f64::EPSILON);
```

--------------------------------

### CloneToUninit Implementation (Nightly)

Source: https://docs.rs/skillratings/0.28.2/skillratings/enum.Outcomes.html

An experimental nightly-only API for performing copy-assignment to uninitialized memory.

```rust
unsafe fn clone_to_uninit(&self, dest: *mut u8)
```

--------------------------------

### Get Minimum of Two MultiTeamOutcome

Source: https://docs.rs/skillratings/0.28.2/skillratings/struct.MultiTeamOutcome.html

Compares two `MultiTeamOutcome` instances and returns the minimum of the two. This is useful when determining the worst outcome among several.

```rust
fn min(self, other: Self) -> Self
```

--------------------------------

### Switching Rating Systems with Glicko-2

Source: https://docs.rs/skillratings

Demonstrates how to use the RatingSystem trait with Glicko-2 for 1v1 matches. Ensure the correct Config is provided when switching systems. For more accurate calculations, consider using rating system modules directly.

```rust
use skillratings::{
    glicko2::{Glicko2, Glicko2Config},
    Outcomes,
    Rating,
    RatingSystem,
};

// Initialise a new player rating with a rating value and uncertainty value.
// Not every rating system has an uncertainty value, so it may be discarded.
// Some rating systems might consider other values too (volatility, age, matches played etc.).
// If that is the case, we will use the default values for those.
let player_one = Rating::new(Some(1200.0), Some(120.0));
// Some rating systems might use widely different scales for measuring a player's skill.
// So if you always want the default values for every rating system, use None instead.
let player_two = Rating::new(None, None);

// The config needs to be specific to the rating system.
// When you swap rating systems, make sure to update the config.
let config = Glicko2Config::new();

// For 1v1 matches we are using the `RatingSystem` trait with the provided config.
// If no config is available for the rating system, pass in empty brackets.
// You may also need to use a type annotation here for the compiler.
let rating_system: Glicko2 = RatingSystem::new(config);

// The outcome of the match is from the perspective of player one.
let outcome = Outcomes::WIN;

// Calculate the expected score of the match.
let expected_score = rating_system.expected_score(&player_one, &player_two);
// Calculate the new ratings.
let (new_one, new_two) = rating_system.rate(&player_one, &player_two, &outcome);

// After that, access new ratings and uncertainties with the functions below.
assert_eq!(new_one.rating().round(), 1241.0);
// Note that because not every rating system has an uncertainty value,
// the uncertainty function returns an Option<f64>.
assert_eq!(new_one.uncertainty().unwrap().round(), 118.0);
```

--------------------------------

### Get Maximum of Two MultiTeamOutcome

Source: https://docs.rs/skillratings/0.28.2/skillratings/struct.MultiTeamOutcome.html

Compares two `MultiTeamOutcome` instances and returns the maximum of the two. This is useful when determining the best outcome among several.

```rust
fn max(self, other: Self) -> Self
```

--------------------------------

### Function: get_first_dwz

Source: https://docs.rs/skillratings/0.28.2/skillratings/dwz/index.html

Determines and returns a proper initial DWZ rating for a new player.

```APIDOC
## Function: get_first_dwz

Gets a proper first `DWZRating`.
```

--------------------------------

### Rating Trait

Source: https://docs.rs/skillratings/0.28.2/skillratings/trait.Rating.html

Defines the core interface for skill rating systems, including methods to get the rating value, its uncertainty, and to create a new rating.

```APIDOC
## Trait Rating

### Description
Measure of player’s skill.

📌 _**Important note:**_ Please keep in mind that some rating systems use widely different scales for measuring ratings. Please check out the documentation for each rating system for more information, or use `None` to always use default values. Some rating systems might consider other values too (volatility, age, matches played etc.). If that is the case, we will use the default values for those.

### Required Methods

#### fn rating(&self) -> f64

A single value for player’s skill

#### fn uncertainty(&self) -> Option<f64>

A value for the uncertainty of a players rating. If the algorithm does not include an uncertainty value, this will return `None`.

#### fn new(rating: Option<f64>, uncertainty: Option<f64>) -> Self

Initialise a `Rating` with provided score and uncertainty, if `None` use default. If the algorithm does not include an uncertainty value it will get dismissed.

### Dyn Compatibility

This trait is **not** dyn compatible. _In older versions of Rust, dyn compatibility was called "object safety", so this trait is not object safe._
```

--------------------------------

### TrueSkillConfig Struct

Source: https://docs.rs/skillratings/0.28.2/skillratings/trueskill/struct.TrueSkillConfig.html

Configuration parameters for the TrueSkill algorithm.

```APIDOC
## TrueSkillConfig

### Description
Constants used in the TrueSkill calculations to adjust rating updates based on game-specific characteristics.

### Fields
- **draw_probability** (f64) - The probability of draws occurring in a match. Default: 0.1.
- **beta** (f64) - The skill-class width, representing the rating difference needed for an 80% win probability. Default: ~4.167.
- **dynamics_factor** (f64) - The additive dynamics factor determining volatility of player positions. Default: ~0.0833.

### Methods
#### new()
Initializes a new `TrueSkillConfig` with default values (draw_probability: 0.1, beta: ~4.167, dynamics_factor: ~0.0833).
```

--------------------------------

### Initialize DWZ Rating System

Source: https://docs.rs/skillratings/0.28.2/skillratings/dwz/struct.DWZ.html

Initializes the DWZ rating system. This function does not require any configuration.

```rust
fn new(_config: Self::CONFIG) -> Self
```

--------------------------------

### Initialize New Glicko2Config

Source: https://docs.rs/skillratings/0.28.2/skillratings/glicko2/struct.Glicko2Config.html

Creates a new Glicko2Config with default values for tau (0.5) and convergence tolerance (0.000001).

```rust
pub const fn new() -> Self
```