ffsimulator

https://ffsimulator.ffverse.com
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The ffsimulator package uses bootstrap resampling to run fantasy football season simulations...
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### Install Development Dependencies

Source: https://ffsimulator.ffverse.com/contributing

Installs all necessary development dependencies for the package. Ensure this is run after cloning the repository.

```r
devtools::install_dev_deps()
```

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

### R Example: Copying a Template

Source: https://ffsimulator.ffverse.com/reference/ffs_copy_template

Demonstrates how to use ffs_copy_template to copy a simulation template to a temporary file. This is useful for testing or creating new simulation setups.

```R
# \donttest {

tmp <- tempfile()
ffs_copy_template(tmp)
#> ✔ Successfully copied template to /tmp/Rtmpwf16Qh/file1a447f6a29e3!
# }

```

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

### Example: Fetching and Displaying Starter Positions

Source: https://ffsimulator.ffverse.com/reference/ffs_starter_positions

Demonstrates how to establish a connection and then fetch and display the starter positions for a league. This example uses a cached connection for efficiency and includes error handling.

```r
# cached examples
try({
conn <- .ffs_cache("mfl_conn.rds")
ffs_starter_positions(conn)
})
```

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

### R Example: Optimising Lineups with Cached Data

Source: https://ffsimulator.ffverse.com/reference/ffs_optimise_lineups

This example demonstrates how to use the `ffs_optimise_lineups` function with pre-cached roster scores and lineup constraints. It shows the typical output structure.

```R
# \donttest{
# cached examples
roster_scores <- .ffs_cache("roster_scores.rds")
lineup_constraints <- .ffs_cache("mfl_lineup_constraints.rds")

ffs_optimise_lineups(roster_scores, lineup_constraints)
```

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

### Example Usage of ff_simulate_week

Source: https://ffsimulator.ffverse.com/reference/ff_simulate_week

This example demonstrates how to connect to a fantasy league using mfl_connect and then simulate an upcoming week using ff_simulate_week. It includes a try block to handle potential errors during execution, such as no unplayed weeks being available.

```R
# \donttest{
try({
conn <- mfl_connect(2021, 22627)
ff_simulate_week(conn, n = 1000, actual_schedule = TRUE)
})
# }
```

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

### Import Lineup Constraints

Source: https://ffsimulator.ffverse.com/articles/custom

Retrieve lineup constraints, such as starting positions and minimum requirements, from your fantasy platform. These can be edited to test hypothetical starting lineup settings.

```r
lineup_constraints <- ffs_starter_positions(conn)
```

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

### R Example: Fetching Latest Rankings

Source: https://ffsimulator.ffverse.com/reference/ffs_latest_rankings

Demonstrates how to call the ffs_latest_rankings function to retrieve the latest FantasyPros expert rankings. The example is wrapped in a try block to prevent potential CRAN-related issues.

```R
# \donttest{ 
try({ # try block to prevent CRAN-related issues
ffs_latest_rankings()
})
#> ── nflverse FP expert rankings ─────────────────────────────────────────────────
#> ℹ Data updated: 2024-10-03 14:21:37 UTC
#> # A tibble: 1,324 × 8
#>    player           fantasypros_id pos   team    bye   ecr    sd scrape_date
#>    <chr>            <chr>          <chr> <chr> <dbl> <dbl> <dbl> <date>     
#>  1 Brian Branch     25235          DB    DET       5   1     0   2024-09-27 
#>  2 Jessie Bates III 17544          DB    ATL      12   3     1   2024-09-27 
#>  3 Julian Love      18243          DB    SEA      10   3     0   2024-09-27 
#>  4 Derwin James Jr. 17310          DB    LAC       5   3.5   1.5 2024-09-27 
#>  5 Budda Baker      16733          DB    ARI      11   4.5   0.5 2024-09-27 
#>  6 Jaquan Brisker   23719          DB    CHI       7   8     2   2024-09-27 
#>  7 Kyle Dugger      19337          DB    NEP      14   8.5   2.5 2024-09-27 
#>  8 Kyle Hamilton    23494          DB    BAL      14   8.5   1.5 2024-09-27 
#>  9 Joshua Metellus  19580          DB    MIN       6  10.5   2.5 2024-09-27 
#> 10 Xavier McKinney  19216          DB    GBP      10  11     2   2024-09-27 
#> # ℹ 1,314 more rows
# }
```

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

### Install ffsimulator from CRAN

Source: https://ffsimulator.ffverse.com/dev

Install the stable version of the ffsimulator package from CRAN.

```r
install.packages("ffsimulator") # CRAN
```

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

### Install ffsimulator Development Version (remotes)

Source: https://ffsimulator.ffverse.com/dev

Install the development version of the ffsimulator package using the remotes package.

```r
remotes::install_github("ffverse/ffsimulator")
```

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

### Run ff_simulate with Example Data

Source: https://ffsimulator.ffverse.com/reference/ff_simulate

Example of how to connect to a league and run the ff_simulate function with a specified number of seasons. This code block is wrapped in a try-catch to prevent CRAN-related issues and includes output messages indicating the simulation progress.

```R
# \donttest{
try({
conn <- mfl_connect(2021, 22627)
ff_simulate(conn, n_seasons = 25)
})
# }
```

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

### Install ffsimulator Development Version (pak)

Source: https://ffsimulator.ffverse.com/dev

Install the development version of the ffsimulator package using the pak package manager.

```r
pak::pak("ffverse/ffsimulator")
```

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

### Get Franchises Data

Source: https://ffsimulator.ffverse.com/reference/ffs_franchises

Fetches franchise data including the league_id, which is necessary for ffsimulator. This example demonstrates how to connect to a league and retrieve its franchises.

```r
# \donttest{
# cached examples
conn <- .ffs_cache("mfl_conn.rds")

try({
ffs_franchises(conn)
})
# }
```

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

### Install ffsimulator Development Version (r-universe)

Source: https://ffsimulator.ffverse.com/dev

Install the development version of the ffsimulator package from the ffverse r-universe repository.

```r
install.packages("ffsimulator", repos = "https://ffverse.r-universe.dev")
```

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

### Get League Starter Positions

Source: https://ffsimulator.ffverse.com/reference/ffs_starter_positions

This function retrieves positional lineup rules for a fantasy football league. It requires an active connection object.

```r
ffs_starter_positions(conn)
```

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

### Example Usage of ffs_generate_projections_week

Source: https://ffsimulator.ffverse.com/reference/ffs_generate_projections_week

Demonstrates how to use the `ffs_generate_projections_week` function with cached ADP outcomes and latest rankings. The function simulates weekly scores for players.

```r
# \donttest{
# cached examples
adp_outcomes_week <- .ffs_cache("adp_outcomes_week.rds")
latest_rankings_week <- .ffs_cache("latest_rankings_week.rds")

ffs_generate_projections_week(adp_outcomes_week, latest_rankings_week)
#>
#>          week fantasypros_id         player    pos   team    ecr    sd  rank
#>          <int>         <char>         <char> <char> <char>  <num> <num> <num>
#>      1:     1          17233  Lamar Jackson     QB    BAL   1.79  0.67     1
#>      2:     9          17233  Lamar Jackson     QB    BAL   1.79  0.67     1
#>      3:    18          17233  Lamar Jackson     QB    BAL   1.79  0.67     1
#>      4:    22          17233  Lamar Jackson     QB    BAL   1.79  0.67     1
#>      5:    30          17233  Lamar Jackson     QB    BAL   1.79  0.67     1
#>     ---
#> 276996:   374          19270 Devin Duvernay     WR    BAL 121.00 15.00   145
#> 276997:   460          19270 Devin Duvernay     WR    BAL 121.00 15.00   145
#> 276998:   208          19270 Devin Duvernay     WR    BAL 121.00 15.00   148
#> 276999:   781          19270 Devin Duvernay     WR    BAL 121.00 15.00   148
#> 277000:   863          18318     Jalen Hurd     WR     SF 117.67 15.92   150
#>         scrape_date projected_score projection gp_model season
#>              <Date>           <num>      <num>    <num>  <num>
#>      1:  2021-09-06              NA         NA        1      1
#>      2:  2021-09-06              NA         NA        1      1
#>      3:  2021-09-06              NA         NA        1      1
#>      4:  2021-09-06              NA         NA        1      1
#>      5:  2021-09-06              NA         NA        1      1
#>     ---
#> 276996:  2021-09-06              NA         NA        1      1
#> 276997:  2021-09-06              NA         NA        1      1
#> 276998:  2021-09-06              NA         NA        1      1
#> 276999:  2021-09-06              NA         NA        1      1
#> 277000:  2021-09-06             0.9        0.9        1      1
# }

```

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

### Example Usage of ffs_schedule

Source: https://ffsimulator.ffverse.com/reference/ffs_schedule

Demonstrates how to use the ffs_schedule function with a pre-established connection object. It caches the connection and then calls ffs_schedule, showing the resulting empty tibble.

```r
# \donttest{
# cached examples
try({ # try block to prevent CRAN-related issues
conn <- .ffs_cache("mfl_conn.rds")
ffs_schedule(conn)
})
#> # A tibble: 0 × 4
#> # ℹ 4 variables: week <dbl>, franchise_id <chr>, opponent_id <chr>,
#> #   league_id <chr>
# }

```

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

### Example Usage of ffs_generate_projections

Source: https://ffsimulator.ffverse.com/reference/ffs_generate_projections

Demonstrates how to use the ffs_generate_projections function with cached adp_outcomes and latest_rankings data. The optional 'rosters' argument can be used to reduce computation.

```R
# \donttest{
# cached examples
adp_outcomes <- .ffs_cache("adp_outcomes.rds")
latest_rankings <- .ffs_cache("latest_rankings.rds")

ffs_generate_projections(adp_outcomes, latest_rankings)
#>         season fantasypros_id             player    pos   team   bye    ecr
#>          <int>         <char>             <char> <char> <char> <num>  <num>
#>      1:      2          16413 Patrick Mahomes II     QB    KCC    12   1.32
#>      2:      2          16413 Patrick Mahomes II     QB    KCC    12   1.32
#>      3:      2          16413 Patrick Mahomes II     QB    KCC    12   1.32
#>      4:      2          16413 Patrick Mahomes II     QB    KCC    12   1.32
#>      5:      2          16413 Patrick Mahomes II     QB    KCC    12   1.32
#>     ---                                                                    
#> 994696:     88          19534        Tarik Black     WR    IND    14 239.50
#> 994697:     88          19534        Tarik Black     WR    IND    14 239.50
#> 994698:     88          19534        Tarik Black     WR    IND    14 239.50
#> 994699:     88          19534        Tarik Black     WR    IND    14 239.50
#> 994700:     88          19534        Tarik Black     WR    IND    14 239.50
#>            sd  rank scrape_date  week projection gp_model projected_score
#>         <num> <num>      <Date> <int>      <num>    <int>           <num>
#>      1:  0.69     1  2021-09-03     1      18.82        1           18.82
#>      2:  0.69     1  2021-09-03     2      20.44        0            0.00
#>      3:  0.69     1  2021-09-03     3      18.92        1           18.92
#>      4:  0.69     1  2021-09-03     4      20.44        1           20.44
#>      5:  0.69     1  2021-09-03     5      25.19        1           25.19
#>     ---                                                                  
#> 994696: 20.50   243  2021-09-03    10       2.10        0            0.00
#> 994697: 20.50   243  2021-09-03    11       0.00        0            0.00
#> 994698: 20.50   243  2021-09-03    12       0.00        0            0.00
#> 994699: 20.50   243  2021-09-03    13       4.40        0            0.00
#> 994700: 20.50   243  2021-09-03    14       0.00        0            0.00
# }

```

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

### Connect to a Fantasy League and Simulate Seasons

Source: https://ffsimulator.ffverse.com/articles/basic

Connect to a MyFantasyLeague (MFL) league and run a specified number of seasons and weeks for simulation. This is the primary function to start a simulation.

```r
foureight_conn <- mfl_connect(2021, 22627)

foureight_sim <- ff_simulate(conn = foureight_conn, n_seasons = 10, n_weeks = 14)
foureight_sim
```

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

### Run Basic Fantasy Football Season Simulation

Source: https://ffsimulator.ffverse.com/dev

Run a fantasy football season simulation using ffsimulator. This example connects to MFL, runs 100 seasons, and plots the results. Other platform connections can be used.

```r
library(ffsimulator)
library(ggplot2)
library(ggridges)

mfl_conn <- mfl_connect(season = 2021, league_id = 22627)

## OTHER PLATFORM CONNECTIONS MAY BE USED, FOR EXAMPLE:
# sleeper_conn <- sleeper_connect(season = 2021,  league_id = "652582284720971776") 
# flea_conn <- fleaflicker_connect(season = 2021, league_id = 312861) 
# espn_conn <- espn_connect(season = 2021, league_id = 899513) 

mfl_sim <- ff_simulate(conn = mfl_conn, n_seasons = 100)

plot(mfl_sim)
```

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

### Import Rosters

Source: https://ffsimulator.ffverse.com/articles/custom

Get roster data and attach a 'fantasypros_id'. This dataframe can be manually edited to simulate hypothetical scenarios like trades before running the simulation.

```r
rosters <- ffs_rosters(conn)
```

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

### Generate ADP Outcomes with Simple Games Played Model

Source: https://ffsimulator.ffverse.com/reference/ffs_adp_outcomes

This example demonstrates how to use `ffs_adp_outcomes` with the default `gp_model = "simple"`. It requires cached scoring history data.

```R
# cached data
scoring_history <- .ffs_cache("mfl_scoring_history.rds")

ffs_adp_outcomes(scoring_history, gp_model = "simple")
#>         pos  rank   prob_gp                           week_outcomes
#>      <char> <num>     <num>                                  <list>
#>   1:     QB     1 0.9265173 12.92,14.36,13.30,28.48, 9.42,18.32,...
#>   2:     QB     2 0.9250973  9.40,17.00, 9.70,17.78,-2.00,18.79,...
#>   3:     QB     3 0.9235976 20.56,21.10,24.46,17.68,33.23,32.94,...
#>   4:     QB     4 0.9219388 20.56,21.10,24.46,17.68,33.23,32.94,...
#>   5:     QB     5 0.9200411 20.56,21.10,24.46,17.68,33.23,32.94,...
#>  ---                                                               
#> 643:     WR   240 0.1362678                 1.8,0.9,2.8,1.3,0.3,1.6
#> 644:     WR   241 0.1343298                 1.0,2.1,1.8,0.9,0.3,1.6
#> 645:     WR   242 0.1323911        1.0, 2.1,14.5, 5.7, 6.7, 5.9,...
#> 646:     WR   243 0.1304520        1.0, 2.1,14.5, 5.7, 6.7, 5.9,...
#> 647:     WR   244 0.1285126        1.0, 2.1, 5.7, 6.3, 5.2,11.4,...
#>                                                                                          player_name
#>                                                                                               <list>
#>   1: Aaron Rodgers,Deshaun Watson,Deshaun Watson,Patrick Mahomes,Patrick Mahomes,Patrick Mahomes,...
#>   2:      Baker Mayfield,Aaron Rodgers,Deshaun Watson,Patrick Mahomes,Lamar Jackson,Dak Prescott,...
#>   3:         Matt Ryan,Baker Mayfield,Aaron Rodgers,Deshaun Watson,Patrick Mahomes,Lamar Jackson,...
#>   4:             Matt Ryan,Baker Mayfield,Aaron Rodgers,Deshaun Watson,Carson Wentz,Kyler Murray,...
#>   5:                 Matt Ryan,Cam Newton,Baker Mayfield,Aaron Rodgers,Carson Wentz,Kyler Murray,...
#>  ---                                                                                                
#> 643:                                                   Ashton Dulin,CJ Board,JoJo Natson,Marcus Kemp
#> 644:                                                 Fred Brown,Ashton Dulin,JoJo Natson,Marcus Kemp
#> 645:                                                             Fred Brown,Allen Lazard,Marcus Kemp
#> 646:                                                             Fred Brown,Allen Lazard,Marcus Kemp
#> 647:                                            Fred Brown,Marvin Hall,Allen Lazard,Darrius Shepherd
#>                              fantasypros_id
#>                                      <list>
#>   1: 9001,16398,16398,16413,16413,16413,...
#>   2: 17237,9001,16398,16413,17233,15600,...
#>   3:  9444,17237,9001,16398,16413,17233,...
#>   4:  9444,17237,9001,16398,15520,18600,...
#>   5:   9444,9869,17237,9001,15520,18600,...
#>  ---                                       
#> 643:                18656,16834,16854,16918
#> 644:                17160,18656,16854,16918
#> 645:                      17160,17301,16918
#> 646:                      17160,17301,16918
#> 647:                17160,16115,17301,19030
```

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

### Example Usage of ffs_adp_outcomes_week

Source: https://ffsimulator.ffverse.com/reference/ffs_adp_outcomes_week

Demonstrates how to use the `ffs_adp_outcomes_week` function with cached scoring history data. It shows the resulting dataframe structure including position, rank, weekly outcomes, player names, and FantasyPros IDs.

```R
# \donttest{ 
# cached data
scoring_history <- .ffs_cache("mfl_scoring_history.rds")
ffs_adp_outcomes_week(scoring_history, pos_filter = c("QB","RB","WR","TE"))
#>         pos  rank                           week_outcomes
#>      <char> <num>                                  <list>
#>   1:     QB     1  7.64, 7.64,32.88,24.48,11.44,24.30,...
#>   2:     QB     2 32.94, 7.64,32.88,24.48,11.44,24.30,...
#>   3:     QB     3 32.94, 2.56, 7.64,32.88,24.48,11.44,...
#>   4:     QB     4 30.80, 6.96,28.76,13.32,32.94, 2.56,...
#>   5:     QB     5 30.80, 6.96,28.76,13.32,21.10,24.46,...
#>  ---                                                     
#> 476:     WR   170       -0.2, 1.2, 0.0, 2.1,  NA,  NA,...
#> 477:     WR   171       -0.2, 0.0,  NA,  NA,  NA,  NA,...
#> 478:     WR   172       -0.2, 0.0,  NA,  NA,  NA,  NA,...
#> 479:     WR   173                    0,NA,NA,NA,NA,NA,...
#> 480:     WR   174                    0,NA,NA,NA,NA,NA,...
#>                                                                          player_name
#>                                                                               <list>
#>   1: Matt Ryan,Matt Ryan,Lamar Jackson,Lamar Jackson,Lamar Jackson,Lamar Jackson,...
#>   2:  Matt Ryan,Matt Ryan,Lamar Jackson,Lamar Jackson,Lamar Jackson,Dak Prescott,...
#>   3:     Matt Ryan,Matt Ryan,Matt Ryan,Lamar Jackson,Lamar Jackson,Lamar Jackson,...
#>   4:      Kyler Murray,Matt Ryan,Matt Ryan,Matt Ryan,Lamar Jackson,Lamar Jackson,...
#>   5:      Kyler Murray,Matt Ryan,Matt Ryan,Matt Ryan,Lamar Jackson,Lamar Jackson,...
#>  ---                                                                                
#> 476:               Deonte Harty,Dwayne Harris,Johnny Holton,Jaleel Scott
#> 477:                                                      Deonte Harty,Johnny Holton
#> 478:                                                      Deonte Harty,Johnny Holton
#> 479:                                                                   Johnny Holton
#> 480:                                                                   Johnny Holton
#>                             fantasypros_id
#>                                     <list>
#>   1: 9444,9444,17233,17233,17233,17233,...
#>   2: 9444,9444,17233,17233,17233,15600,...
#>   3:  9444,9444,9444,17233,17233,17233,...
#>   4:  18600,9444,9444,9444,17233,17233,...
#>   5:  18600,9444,9444,9444,17233,17233,...
#>  ---                                      
#> 476:               18876,10004,15803,17260
#> 477:                           18876,15803
#> 478:                           18876,15803
#> 479:                                 15803
#> 480:                                 15803
#> 
# }
```

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

### Initialize ffscrapr and ffsimulator

Source: https://ffsimulator.ffverse.com/articles/custom

Sets up the environment by configuring ffscrapr caching and loading necessary libraries. A seed is set for reproducible results.

```r
options(ffscrapr.cache = "filesystem")
library(ffsimulator)
library(ffscrapr)
library(tidyverse)
library(tictoc) # for timing!

set.seed(613)
```

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

### Initialize Git Branch for PR

Source: https://ffsimulator.ffverse.com/contributing

Creates a new Git branch for your pull request. Replace 'brief-description-of-change' with a concise summary of your modifications.

```r
usethis::pr_init("brief-description-of-change")
```

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

### Create GitHub Fork and Clone

Source: https://ffsimulator.ffverse.com/contributing

Use this function to fork the package repository on GitHub and clone it to your local machine. This is the recommended first step for new contributors.

```r
usethis::create_from_github("ffverse/ffsimulator", fork = TRUE)
```

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

### ffs_starter_positions

Source: https://ffsimulator.ffverse.com/reference/ffs_starter_positions

This function lightly wraps `ffscrapr::ff_starter_positions()` and cleans up some abbreviations (PK -> K). It returns a tidy dataframe of positional lineup rules.

```APIDOC
## ffs_starter_positions

### Description
Retrieves a tidy dataframe of positional lineup rules, one row per position with minimum and maximum starters as well as total starter calculations.

### Usage
```
ffs_starter_positions(conn)
```

### Arguments

* **conn** (object) - Required - A connection object as created by `ffscrapr::ff_connect()` and friends.

### Value
A tidy dataframe of positional lineup rules, one row per position with minimum and maximum starters as well as total starter calculations.

### Examples

```R
# \donttest{
# cached examples
try({
conn <- .ffs_cache("mfl_conn.rds")
ffs_starter_positions(conn)
})
#}
```
```

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

### Build Schedules and Summarize Results

Source: https://ffsimulator.ffverse.com/articles/custom

Constructs game schedules for the simulated seasons and then summarizes the weekly and seasonal performance, culminating in a final simulation summary. These steps are computationally fast.

```r
schedules <- ffs_build_schedules(franchises = franchises,
                                 n_seasons = n_seasons,
                                 n_weeks = n_weeks)

summary_week <- ffs_summarise_week(optimal_scores, schedules)
summary_season <- ffs_summarise_season(summary_week)
summary_simulation <- ffs_summarise_simulation(summary_season)
```

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

### Aggregate Simulation Results

Source: https://ffsimulator.ffverse.com/articles/custom

Aggregates simulation results sequentially, starting from weekly scores, then summarizing by season, and finally by simulation. Each summary function feeds into the next.

```r
summary_week <- ffs_summarise_week(optimal_scores, schedules)
summary_season <- ffs_summarise_season(summary_week)
summary_simulation <- ffs_summarise_simulation(summary_season)
```

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

### Get Rosters with Connection

Source: https://ffsimulator.ffverse.com/reference/ffs_rosters

Retrieves player rosters using an established connection object. This function is designed to work with various fantasy football platform connection types.

```r
conn <- .ffs_cache("mfl_conn.rds")

try({
  ffs_rosters(conn)
})
```

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

### ff_simulate

Source: https://ffsimulator.ffverse.com/reference/ff_simulate

Runs fantasy football season simulations using bootstrap resampling. It calculates optimal lineups and returns aggregated results based on historical rankings and nflfastR data.

```APIDOC
## ff_simulate

### Description
Runs fantasy football season simulations using bootstrap resampling. It calculates optimal lineups and returns aggregated results based on historical rankings and nflfastR data.

### Arguments

* **conn** (connection) - Required - An connection to a league made with `ff_connect()` and friends.
* **n_seasons** (integer) - Optional - Number of seasons to simulate, default = 100.
* **n_weeks** (integer) - Optional - Number of weeks per season, default = 14.
* **best_ball** (logical) - Optional - A logical: are weekly wins based on optimal lineups?
* **seed** (integer) - Optional - An integer to control reproducibility.
* **gp_model** (character) - Optional - Select between "simple", "none" to apply a model for whether a player played in a given game, defaults to "simple".
* **base_seasons** (numeric vector) - Optional - A numeric vector that selects seasons as base data, earliest available is 2012.
* **actual_schedule** (logical) - Optional - A logical: use actual ff_schedule? default is FALSE.
* **replacement_level** (logical) - Optional - A logical: use best available on waiver as replacement level? defaults to TRUE.
* **pos_filter** (character vector) - Optional - A character vector of positions to filter/run, default is c("QB","RB","WR","TE","K").
* **verbose** (logical) - Optional - A logical: print status messages? default is TRUE, configure with options(ffsimulator.verbose).
* **return** (character) - Optional - One of c("default", "all") - what objects to return in the output list.

### Value
An `ff_simulation` object which can be passed to `plot()` and contains the output data from the simulation.

### Examples
```R
# \donttest{
try({
conn <- mfl_connect(2021, 22627)
ff_simulate(conn, n_seasons = 25)
})
}
```
```

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

### Generate ADP Outcomes with None Games Played Model

Source: https://ffsimulator.ffverse.com/reference/ffs_adp_outcomes

This example shows how to use `ffs_adp_outcomes` with `gp_model = "none"`, which assumes every game is played. It also requires cached scoring history data.

```R
ffs_adp_outcomes(scoring_history, gp_model = "none")
#>         pos  rank prob_gp                           week_outcomes
#>      <char> <num>   <num>                                  <list>
#>   1:     QB     1       1 12.92,14.36,13.30,28.48, 9.42,18.32,...
#>   2:     QB     2       1  9.40,17.00, 9.70,17.78,-2.00,18.79,...
#>   3:     QB     3       1 20.56,21.10,24.46,17.68,33.23,32.94,...
#>   4:     QB     4       1 20.56,21.10,24.46,17.68,33.23,32.94,...
#>   5:     QB     5       1 20.56,21.10,24.46,17.68,33.23,32.94,...
#>  ---                                                             
#> 674:     WR   255       1                                     0,0
```

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

### Load Required Libraries

Source: https://ffsimulator.ffverse.com/articles/basic

Load the ffsimulator and ggplot2 libraries before running simulations.

```r
library(ffsimulator)
library(ggplot2)
```

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

### Connect to League and Simulate a Week

Source: https://ffsimulator.ffverse.com/articles/basic

Connects to a specified fantasy league and simulates a single week of gameplay. The simulation can be run multiple times (n) for more robust analysis.

```r
foureight_conn <- mfl_connect(2021, 22627)

foureight_sim_week <- ff_simulate_week(conn = foureight_conn, n = 10)

foureight_sim_week
```

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

### ff_connect()

Source: https://ffsimulator.ffverse.com/reference/ff_connect

Establishes a connection object that can be used with ff_* functions to interact with fantasy football leagues. Refer to the ffscrapr::ff_connect() documentation for detailed usage.

```APIDOC
## ff_connect()

### Description
Establishes a connection object to be used with `ff_*` functions.

### Details
See `ffscrapr::ff_connect()` for details.

### Value
A connection object to be used with `ff_*` functions.

### See Also
Other ffscrapr-imports: `espn_connect()`, `ff_scoringhistory()`, `ff_starter_positions()`, `fleaflicker_connect()`, `mfl_connect()`, `sleeper_connect()`
```

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

### Build Fantasy Schedules Function

Source: https://ffsimulator.ffverse.com/reference/ffs_build_schedules

Generates random head-to-head schedules for a specified number of teams, seasons, and weeks. Use this function to create the foundational schedule for a fantasy simulation.

```R
ffs_build_schedules(
  n_teams = NULL,
  n_seasons = 100,
  n_weeks = 14,
  franchises = NULL,
  seed = NULL
)
```

```R
# \donttest{
ffs_build_schedules(n_teams = 12, n_seasons = 1, n_weeks = 14)
#>      season  week franchise_id opponent_id
#> #>       <int> <int>        <int>       <int>
#> #>   1:      1     5            6          10
#> #>   2:      1     5           11           9
#> #>   3:      1     5            2           3
#> #>   4:      1     5            8           7
#> #>   5:      1     5            5           4
#> #>  ---                                      
#> 164:      1     9            4          10
#> 165:      1     9            7           9
#> 166:      1     9            3           6
#> 167:      1     9            9           7
#> 168:      1     9           10           4
# >
# }
```

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

### Run a Fantasy Football Season Simulation

Source: https://ffsimulator.ffverse.com/

Loads necessary libraries, connects to the MyFantasyLeague (MFL) platform for a specific season and league, runs 100 season simulations, and plots the results. Other platform connections (Sleeper, Fleaflicker, ESPN) can also be used.

```r
library(ffsimulator)
library(ggplot2)
library(ggridges)

mfl_conn <- mfl_connect(season = 2021, league_id = 22627)

## OTHER PLATFORM CONNECTIONS MAY BE USED, FOR EXAMPLE:
# sleeper_conn <- sleeper_connect(season = 2021,  league_id = "652582284720971776") 
# flea_conn <- fleaflicker_connect(season = 2021, league_id = 312861) 
# espn_conn <- espn_connect(season = 2021, league_id = 899513)

mfl_sim <- ff_simulate(conn = mfl_conn, n_seasons = 100)

plot(mfl_sim)
```

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

### Display League Info Table

Source: https://ffsimulator.ffverse.com/articles/basic

Shows the structure and sample data for the league_info table, which includes metadata generated by ffscrapr::ff_league(). This table provides details about the fantasy league's settings and characteristics.

```text
foureight_sim$league_info
#> # A tibble: 1 × 17
#>   league_id league_name         season league_type franchise_count qb_type idp  
#>   <chr>     <chr>                <int> <chr>                 <dbl> <chr>   <lgl>
#> 1 22627     Four-Eight Dynasty…   2021 dynasty                  12 2QB/SF  TRUE 
#> # ℹ 10 more variables: scoring_flags <chr>, best_ball <lgl>, salary_cap <lgl>,
#> #   player_copies <dbl>, years_active <chr>, qb_count <chr>, roster_size <dbl>,
#> #   league_depth <dbl>, draft_type <chr>, draft_player_pool <chr>
```

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

### Push Changes and Create Pull Request

Source: https://ffsimulator.ffverse.com/contributing

Pushes your committed changes to your fork and initiates the pull request process. Follow the prompts in your browser to complete the PR creation.

```r
usethis::pr_push()
```

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

### Load Required Libraries

Source: https://ffsimulator.ffverse.com/articles/custom

Load the necessary libraries for ffsimulator, ffscrapr, dplyr, and ggplot2. These are essential for running simulations and data manipulation.

```r
library(ffsimulator)
library(ffscrapr)
library(dplyr)
library(ggplot2)
```

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

### Check Package with R CMD check

Source: https://ffsimulator.ffverse.com/contributing

Runs R CMD check to ensure the package passes all checks. It's recommended to resolve any issues before proceeding with further development.

```r
devtools::check()
```

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

### Display summary_week Table

Source: https://ffsimulator.ffverse.com/articles/basic

Shows the structure and sample data for the summary_week table. This table contains weekly performance summaries for each team.

```text
foureight_sim$summary_week
#>       season season_week                 franchise_name optimal_score
#>        <num>       <num>                         <char>         <num>
#>    1:      1           1        Mexico City Space Force        166.65
#>    2:      1           1                    Dirty Dgens        145.65
#>    3:      1           1             Alberta Armadillos        108.13
#>    4:      1           1               Electric Woodies        166.51
#>    5:      1           1               Motor City Mutts        148.63
#>   ---                                                                
#> 1676:     10          14             Domination Station        182.70
#> 1677:     10          14 Kill Devil Hills Carpetbaggers        175.64
#> 1678:     10          14                     [Redacted]        134.50
#> 1679:     10          14                           TB12         64.17
#> 1680:     10          14           Indigo Plateau Elite        205.99
#>       lineup_efficiency team_score opponent_score result
#>                   <num>      <num>          <num> <char>
#>    1:             0.691    115.169         76.084      W
#>    2:             0.737    107.286        132.011      L
#>    3:             0.776     83.912        179.982      L
#>    4:             0.793    132.011        107.286      W
#>    5:             0.682    101.357        143.900      L
#>   ---                                                   
#> 1676:             0.740    135.286        113.904      W
#> 1677:             0.795    139.638        100.899      W
#> 1678:             0.847    113.904        135.286      L
#> 1679:             0.778     49.902        131.653      L
#> 1680:             0.760    156.605         79.371      W
#>                        opponent_name allplay_wins allplay_games allplay_pct
#>                               <char>        <num>         <num>       <num>
#>    1:            Hoth City Tauntauns            5            11       0.455
#>    2:               Electric Woodies            3            11       0.273
#>    3:           Indigo Plateau Elite            1            11       0.091
#>    4:                    Dirty Dgens            7            11       0.636
#>    5: Kill Devil Hills Carpetbaggers            2            11       0.182
#>   ---                                                                      
#> 1676:                     [Redacted]            8            11       0.727
#> 1677:        Mexico City Space Force            9            11       0.818
#> 1678:             Domination Station            5            11       0.455
#> 1679:               Electric Woodies            0            11       0.000
#> 1680:            Hoth City Tauntauns           11            11       1.000
#>       league_id franchise_id                       optimal_player_id
#>          <char>       <char>                                  <list>
#>    1:     22627         0001 13592,14777,14081,15265,14805,13672,...
#>    2:     22627         0002 12610,11747,13138,14803,15268,12212,...
#>    3:     22627         0003 10700,11644,14075,14087,14806,15261,...
#>    4:     22627         0004 10703,13589,13139,13319,13236,13880,...
#>    5:     22627         0005  13593,9431,12171,13404,14072,12677,...
#>   ---                                                               
#> 1676:     22627         0008 11760,15240,12164,13604,13607,14798,...
#> 1677:     22627         0009  14059,7836,11657,13108,13133,15505,...
#> 1678:     22627         0010 12140,13116,14223,15254,13680,11671,...
#> 1679:     22627         0011 15239,13131,13850,14828,13192,11232,...
#> 1680:     22627         0012  14056,8062,11193,12626,13130,14852,...
#>                          optimal_player_score
#>                                        <list>
#>    1: 17.76,18.54, 8.70,23.70,12.10,17.10,...
#>    2:        8.8, 9.7,17.6, 7.7, 8.8,26.2,...
#>    3: 10.42, 7.96,10.10, 8.60,17.50,22.30,...
#>    4: 24.24,25.12, 0.00,21.40,15.25,13.40,...
#>    5: 16.92,14.76,12.10,15.30,11.90,11.85,...
#>   ---                                        
#> 1676: 13.78,12.92, 9.40,22.30,20.30, 9.80,...
#> 1677: 29.60,23.64,20.70,11.30,11.70,16.20,...
#> 1678: 20.65,38.60, 4.00, 4.40, 7.85, 8.20,...
#> 1679:  6.12, 8.20,14.70, 2.40, 2.75, 2.40,...
#> 1680: 27.82,25.52, 7.20,18.30,20.70,33.00,...
```

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

### Build Schedules

Source: https://ffsimulator.ffverse.com/articles/custom

Generates randomized head-to-head schedules for a specified number of seasons, teams, and weeks. It uses the circle method for round robin scheduling and shuffles assignments.

```r
schedules <- ffs_build_schedules(
    n_seasons = n_seasons,
    n_weeks = n_weeks,
    seed = NULL,
    franchises = ffs_franchises(conn)
  )
```
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