Fantasy Football Data

library(fflr)
packageVersion("fflr")
#> [1] '2.1.0'
ffl_id(leagueId = "42654852")
#> Temporarily set `fflr.leagueId` option to 42654852
#> [1] "42654852"

This vignette will demonstrate the fflr functions used to reach equivalency with the ESPN fantasy football website. The website has eight section headers with various subsections:

  1. My Team
  2. League
  3. Players
  4. FantasyCast
  5. Scoreboard
  6. Standings
  7. Opposing Teams
  8. LM Tools

My Team

The My Team page presents an overview of, well, your fantasy team. From this page, a team manager can set their lineup and see statistics and news on the players on their roster.

There are six subsections on the My Team page.

Overview

The team_roster() function returns all rosters in a league. The output of this function is organized to replicate the layout of the table found on the website. Players are listed in order of their “slot” with name and team information followed by projected and actual scores and ownership statistics.

my_team <- team_roster(scoringPeriodId = 1)[[1]] # select first roster
my_team[, -(1:3)]
#> # A tibble: 16 × 13
#>    abbrev lineup…¹ playe…² first…³ lastN…⁴ proTeam posit…⁵ injur…⁶ proje…⁷ actua…⁸ perce…⁹
#>    <fct>  <fct>      <int> <chr>   <chr>   <fct>   <fct>   <chr>     <dbl>   <dbl>   <dbl>
#>  1 AUS    QB       3916387 Lamar   Jackson Bal     QB      A         21.2     20.2    91.8
#>  2 AUS    RB       3117251 Christ… McCaff… Car     RB      A         21.0     15.7    99.7
#>  3 AUS    RB       3054850 Alvin   Kamara  NO      RB      Q         18.7      7.6    99.3
#>  4 AUS    WR       4362628 Ja'Marr Chase   Cin     WR      A         17.0     28.9    99.8
#>  5 AUS    WR         15818 Keenan  Allen   LAC     WR      Q         14.0     10.6    95.3
#>  6 AUS    TE       3116365 Mark    Andrews Bal     TE      A         14.4     10.2    99.6
#>  7 AUS    FLEX     4259545 D'Andre Swift   Det     RB      A         16.0     26.5    97.0
#>  8 AUS    D/ST      -16009 Packers D/ST    GB      D/ST    A          5.14     0      77.3
#>  9 AUS    K        4249087 Matt    Gay     LAR     K       A          8.87     6      94.7
#> 10 AUS    BE         16737 Mike    Evans   TB      WR      A         14.8     18.1    95.2
#> 11 AUS    BE       4047646 A.J.    Brown   Phi     WR      A         14.4     25.5    92.3
#> 12 AUS    BE       3128720 Nick    Chubb   Cle     RB      A         13.9     15.3    92.9
#> 13 AUS    BE         16731 Brandin Cooks   Hou     WR      A         13.7     15.2    67.6
#> 14 AUS    BE       4239996 Travis  Etienn… Jax     RB      A         13.6      8.5    71.4
#> 15 AUS    BE       4241463 Jerry   Jeudy   Den     WR      A         13.5      0      72.5
#> 16 AUS    BE       4241985 J.K.    Dobbins Bal     RB      O          0        0      22.0
#> # … with 2 more variables: percentOwned <dbl>, percentChange <dbl>, and abbreviated
#> #   variable names ¹​lineupSlot, ²​playerId, ³​firstName, ⁴​lastName, ⁵​position,
#> #   ⁶​injuryStatus, ⁷​projectedScore, ⁸​actualScore, ⁹​percentStarted

News

The player_outlook() and player_news() functions return news on your roster. The first returns all outlooks by player and week and cannot be refined beyond setting a limit of players to return (in order of rank).

player_outlook(limit = 1)
#> # A tibble: 2 × 6
#>   seasonId scoringPeriodId      id firstName lastName outlook                             
#>      <int>           <int>   <int> <chr>     <chr>    <chr>                               
#> 1     2022               0 2977187 Cooper    Kupp     "Here is an incomplete list of cate…
#> 2     2022               1 2977187 Cooper    Kupp     "Kupp was \"other-wordly good\" in …

The second fiction takes a single playerId value and returns all the recent news on that player, including premium stories in HTML format.

player_news(playerId = "3139477", parseHTML = FALSE)
#> # A tibble: 7 × 6
#>        id published           type     premium headline                              body 
#>     <int> <dttm>              <chr>    <lgl>   <chr>                                 <chr>
#> 1 3139477 2022-09-12 23:51:43 Story    FALSE   Reunions and revenge games highlight… "<p>…
#> 2 3139477 2022-09-12 00:00:40 Rotowire FALSE   Mahomes completed 30 of 39 passes fo… "The…
#> 3 3139477 2022-08-20 23:10:54 Rotowire FALSE   Mahomes completed 12 of 19 passes fo… "Mah…
#> 4 3139477 2022-08-18 15:54:34 Rotowire FALSE   Mahomes is in line to play in Saturd… "Whi…
#> 5 3139477 2022-08-13 20:23:31 Rotowire FALSE   Mahomes went 6-for-7 for 60 yards an… "Mah…
#> 6 3139477 2022-08-11 22:59:48 Rotowire FALSE   Mahomes is expected to see action in… "Bas…
#> 7 3139477 2022-08-01 16:24:40 Rotowire FALSE   Though Mahomes tweaked his ankle dur… "Wit…

League

ESPN fantasy leagues have their own unique settings and structure. This package has been tested for a very narrow subset of those possible settings.

league_info(leagueId = "42654852")
#> # A tibble: 1 × 6
#>         id seasonId name             isPublic  size finalScoringPeriod
#>      <int>    <int> <chr>            <lgl>    <int>              <int>
#> 1 42654852     2022 FFLR Test League TRUE         4                 17
league_name()
#> [1] "FFLR Test League"
league_size()
#> # A tibble: 1 × 2
#>   seasonId  size
#>      <int> <int>
#> 1     2022     4
str(league_status())
#> tibble [1 × 12] (S3: tbl_df/tbl/data.frame)
#>  $ year                   : int 2022
#>  $ isActive               : logi TRUE
#>  $ activatedDate          : POSIXct[1:1], format: "2022-09-09 18:45:51"
#>  $ scoringPeriodId        : int 1
#>  $ firstScoringPeriod     : int 1
#>  $ finalScoringPeriod     : int 17
#>  $ previousSeasons        :List of 1
#>   ..$ : int 2021
#>  $ standingsUpdateDate    : POSIXct[1:1], format: "2022-09-12 03:17:05"
#>  $ teamsJoined            : int 4
#>  $ waiverLastExecutionDate: POSIXct[1:1], format: "2022-09-12 03:17:05"
#>  $ waiverNextExecutionDate: POSIXct[1:1], format: NA
#>  $ waiverProcessStatus    :List of 1
#>   ..$ :'data.frame': 0 obs. of  1 variable:
#>   .. ..$ date: 'POSIXct' num(0) 
#>  - attr(*, "tzone")= chr ""

Settings

Draft

draft_settings()
#> # A tibble: 1 × 13
#>   seasonId aucti…¹ availableDate       date                isTra…² keepe…³ keepe…⁴ keepe…⁵
#>      <int> <chr>   <dttm>              <dttm>              <lgl>     <int>   <int> <chr>  
#> 1     2022 200     2022-09-10 19:00:00 2022-09-10 19:00:00 FALSE         2       2 TRADIT…
#> # … with 5 more variables: leagueSubType <chr>, orderType <chr>, pickOrder <list>,
#> #   timePerSelection <int>, type <chr>, and abbreviated variable names ¹​auctionBudget,
#> #   ²​isTradingEnabled, ³​keeperCount, ⁴​keeperCountFuture, ⁵​keeperOrderType

Rosters

roster_settings()
#> # A tibble: 1 × 8
#>   seasonId isBenchUnlimited isUsingUndroppableList lineu…¹ lineu…² moveL…³ posit…⁴ roste…⁵
#>      <int> <lgl>            <lgl>                  <chr>   <list>    <int> <list>  <chr>  
#> 1     2022 TRUE             TRUE                   INDIVI… <df>         -1 <df>    INDIVI…
#> # … with abbreviated variable names ¹​lineupLocktimeType, ²​lineupSlotCounts, ³​moveLimit,
#> #   ⁴​positionLimits, ⁵​rosterLocktimeType

Scoring

scoring_settings()
#> # A tibble: 1 × 7
#>   seasonId scoringType playerRankType homeTeamBonus playoffHomeTeamBonus playoff…¹ scori…²
#>      <int> <chr>       <chr>                  <int>                <int> <chr>     <list> 
#> 1     2022 H2H_POINTS  PPR                        1                    0 NONE      <df>   
#> # … with abbreviated variable names ¹​playoffMatchupTieRule, ²​scoringItems

Transactions and Keepers

acquisition_settings()
#> # A tibble: 1 × 10
#>    year acquisitionBudget acquis…¹ acqui…² isUsi…³ minim…⁴ waive…⁵ waive…⁶ waive…⁷ waive…⁸
#>   <int>             <int>    <int> <chr>   <lgl>     <int>   <int> <lgl>   <list>    <int>
#> 1  2022               100       -1 WAIVER… FALSE         1      24 TRUE    <chr>        11
#> # … with abbreviated variable names ¹​acquisitionLimit, ²​acquisitionType,
#> #   ³​isUsingAcquisitionBudget, ⁴​minimumBid, ⁵​waiverHours, ⁶​waiverOrderReset,
#> #   ⁷​waiverProcessDays, ⁸​waiverProcessHour

Schedule

schedule_settings()
#> # A tibble: 1 × 10
#>   seasonId divisions    matchupP…¹ match…² match…³ perio…⁴ playo…⁵ playo…⁶ playo…⁷ playo…⁸
#>      <int> <list>            <int>   <int> <list>    <int>   <int> <chr>     <int>   <int>
#> 1     2022 <df [2 × 3]>         17       1 <df>          1       0 TOTAL_…       0       0
#> # … with abbreviated variable names ¹​matchupPeriodCount, ²​matchupPeriodLength,
#> #   ³​matchupPeriods, ⁴​periodTypeId, ⁵​playoffMatchupPeriodLength, ⁶​playoffSeedingRule,
#> #   ⁷​playoffSeedingRuleBy, ⁸​playoffTeamCount

Members

league_members()
#> # A tibble: 1 × 3
#>   displayName memberId                               isLeagueManager
#>   <chr>       <chr>                                  <lgl>          
#> 1 K5cents     {22DFE7FF-9DF2-4F3B-9FE7-FF9DF2AF3BD2} FALSE

Rosters

team_roster(scoringPeriodId = 1)
#> $AUS
#> # A tibble: 16 × 16
#>    seasonId scorin…¹ teamId abbrev lineu…² playe…³ first…⁴ lastN…⁵ proTeam posit…⁶ injur…⁷
#>       <int>    <int>  <int> <fct>  <fct>     <int> <chr>   <chr>   <fct>   <fct>   <chr>  
#>  1     2022        1      1 AUS    QB      3916387 Lamar   Jackson Bal     QB      A      
#>  2     2022        1      1 AUS    RB      3117251 Christ… McCaff… Car     RB      A      
#>  3     2022        1      1 AUS    RB      3054850 Alvin   Kamara  NO      RB      Q      
#>  4     2022        1      1 AUS    WR      4362628 Ja'Marr Chase   Cin     WR      A      
#>  5     2022        1      1 AUS    WR        15818 Keenan  Allen   LAC     WR      Q      
#>  6     2022        1      1 AUS    TE      3116365 Mark    Andrews Bal     TE      A      
#>  7     2022        1      1 AUS    FLEX    4259545 D'Andre Swift   Det     RB      A      
#>  8     2022        1      1 AUS    D/ST     -16009 Packers D/ST    GB      D/ST    A      
#>  9     2022        1      1 AUS    K       4249087 Matt    Gay     LAR     K       A      
#> 10     2022        1      1 AUS    BE        16737 Mike    Evans   TB      WR      A      
#> 11     2022        1      1 AUS    BE      4047646 A.J.    Brown   Phi     WR      A      
#> 12     2022        1      1 AUS    BE      3128720 Nick    Chubb   Cle     RB      A      
#> 13     2022        1      1 AUS    BE        16731 Brandin Cooks   Hou     WR      A      
#> 14     2022        1      1 AUS    BE      4239996 Travis  Etienn… Jax     RB      A      
#> 15     2022        1      1 AUS    BE      4241463 Jerry   Jeudy   Den     WR      A      
#> 16     2022        1      1 AUS    BE      4241985 J.K.    Dobbins Bal     RB      O      
#> # … with 5 more variables: projectedScore <dbl>, actualScore <dbl>, percentStarted <dbl>,
#> #   percentOwned <dbl>, percentChange <dbl>, and abbreviated variable names
#> #   ¹​scoringPeriodId, ²​lineupSlot, ³​playerId, ⁴​firstName, ⁵​lastName, ⁶​position,
#> #   ⁷​injuryStatus
#> 
#> $BOS
#> # A tibble: 16 × 16
#>    seasonId scorin…¹ teamId abbrev lineu…² playe…³ first…⁴ lastN…⁵ proTeam posit…⁶ injur…⁷
#>       <int>    <int>  <int> <fct>  <fct>     <int> <chr>   <chr>   <fct>   <fct>   <chr>  
#>  1     2022        1      2 BOS    QB      3918298 Josh    Allen   Buf     QB      A      
#>  2     2022        1      2 BOS    RB      3068267 Austin  Ekeler  LAC     RB      A      
#>  3     2022        1      2 BOS    RB      4241457 Najee   Harris  Pit     RB      Q      
#>  4     2022        1      2 BOS    WR      3126486 Deebo   Samuel  SF      WR      A      
#>  5     2022        1      2 BOS    WR      2976212 Stefon  Diggs   Buf     WR      A      
#>  6     2022        1      2 BOS    TE        15847 Travis  Kelce   KC      TE      A      
#>  7     2022        1      2 BOS    FLEX    4361579 Javonte Willia… Den     RB      A      
#>  8     2022        1      2 BOS    D/ST     -16027 Buccan… D/ST    TB      D/ST    A      
#>  9     2022        1      2 BOS    K         15683 Justin  Tucker  Bal     K       A      
#> 10     2022        1      2 BOS    BE      3929630 Saquon  Barkley NYG     RB      A      
#> 11     2022        1      2 BOS    BE      4240021 Cam     Akers   LAR     RB      A      
#> 12     2022        1      2 BOS    BE      4372016 Jaylen  Waddle  Mia     WR      A      
#> 13     2022        1      2 BOS    BE      4241372 Marqui… Brown   Ari     WR      A      
#> 14     2022        1      2 BOS    BE      4047650 DK      Metcalf Sea     WR      A      
#> 15     2022        1      2 BOS    BE      4374302 Amon-Ra St. Br… Det     WR      A      
#> 16     2022        1      2 BOS    BE      4040655 Darnell Mooney  Chi     WR      A      
#> # … with 5 more variables: projectedScore <dbl>, actualScore <dbl>, percentStarted <dbl>,
#> #   percentOwned <dbl>, percentChange <dbl>, and abbreviated variable names
#> #   ¹​scoringPeriodId, ²​lineupSlot, ³​playerId, ⁴​firstName, ⁵​lastName, ⁶​position,
#> #   ⁷​injuryStatus
#> 
#> $CHI
#> # A tibble: 16 × 16
#>    seasonId scorin…¹ teamId abbrev lineu…² playe…³ first…⁴ lastN…⁵ proTeam posit…⁶ injur…⁷
#>       <int>    <int>  <int> <fct>  <fct>     <int> <chr>   <chr>   <fct>   <fct>   <chr>  
#>  1     2022        1      3 CHI    QB      4038941 Justin  Herbert LAC     QB      A      
#>  2     2022        1      3 CHI    RB      4242335 Jonath… Taylor  Ind     RB      A      
#>  3     2022        1      3 CHI    RB      3116593 Dalvin  Cook    Min     RB      A      
#>  4     2022        1      3 CHI    WR      4262921 Justin  Jeffer… Min     WR      A      
#>  5     2022        1      3 CHI    WR      4241389 CeeDee  Lamb    Dal     WR      A      
#>  6     2022        1      3 CHI    TE      4360248 Kyle    Pitts   Atl     TE      A      
#>  7     2022        1      3 CHI    FLEX    3116406 Tyreek  Hill    Mia     WR      A      
#>  8     2022        1      3 CHI    D/ST     -16002 Bills   D/ST    Buf     D/ST    A      
#>  9     2022        1      3 CHI    K       3055899 Harris… Butker  KC      K       Q      
#> 10     2022        1      3 CHI    BE      3042519 Aaron   Jones   GB      RB      A      
#> 11     2022        1      3 CHI    BE      4239993 Tee     Higgins Cin     WR      Q      
#> 12     2022        1      3 CHI    BE      3121422 Terry   McLaur… Wsh     WR      A      
#> 13     2022        1      3 CHI    BE      4035538 David   Montgo… Chi     RB      A      
#> 14     2022        1      3 CHI    BE      3051392 Ezekiel Elliott Dal     RB      A      
#> 15     2022        1      3 CHI    BE      3128429 Courtl… Sutton  Den     WR      A      
#> 16     2022        1      3 CHI    BE      4243537 Gabe    Davis   Buf     WR      A      
#> # … with 5 more variables: projectedScore <dbl>, actualScore <dbl>, percentStarted <dbl>,
#> #   percentOwned <dbl>, percentChange <dbl>, and abbreviated variable names
#> #   ¹​scoringPeriodId, ²​lineupSlot, ³​playerId, ⁴​firstName, ⁵​lastName, ⁶​position,
#> #   ⁷​injuryStatus
#> 
#> $DEN
#> # A tibble: 16 × 16
#>    seasonId scorin…¹ teamId abbrev lineu…² playe…³ first…⁴ lastN…⁵ proTeam posit…⁶ injur…⁷
#>       <int>    <int>  <int> <fct>  <fct>     <int> <chr>   <chr>   <fct>   <fct>   <chr>  
#>  1     2022        1      4 DEN    QB      3139477 Patrick Mahomes KC      QB      A      
#>  2     2022        1      4 DEN    RB      3043078 Derrick Henry   Ten     RB      A      
#>  3     2022        1      4 DEN    RB      3116385 Joe     Mixon   Cin     RB      A      
#>  4     2022        1      4 DEN    WR      2977187 Cooper  Kupp    LAR     WR      A      
#>  5     2022        1      4 DEN    WR        16800 Davante Adams   LV      WR      A      
#>  6     2022        1      4 DEN    TE      2576925 Darren  Waller  LV      TE      A      
#>  7     2022        1      4 DEN    FLEX    3115364 Leonard Fourne… TB      RB      A      
#>  8     2022        1      4 DEN    D/ST     -16018 Saints  D/ST    NO      D/ST    A      
#>  9     2022        1      4 DEN    K       4360234 Evan    McPher… Cin     K       A      
#> 10     2022        1      4 DEN    BE      3045147 James   Conner  Ari     RB      A      
#> 11     2022        1      4 DEN    BE      3915416 DJ      Moore   Car     WR      A      
#> 12     2022        1      4 DEN    BE      4035687 Michael Pittma… Ind     WR      A      
#> 13     2022        1      4 DEN    BE      3932905 Diontae Johnson Pit     WR      A      
#> 14     2022        1      4 DEN    BE      3045138 Mike    Willia… LAC     WR      A      
#> 15     2022        1      4 DEN    BE      4427366 Breece  Hall    NYJ     RB      A      
#> 16     2022        1      4 DEN    BE      3116165 Chris   Godwin  TB      WR      Q      
#> # … with 5 more variables: projectedScore <dbl>, actualScore <dbl>, percentStarted <dbl>,
#> #   percentOwned <dbl>, percentChange <dbl>, and abbreviated variable names
#> #   ¹​scoringPeriodId, ²​lineupSlot, ³​playerId, ⁴​firstName, ⁵​lastName, ⁶​position,
#> #   ⁷​injuryStatus

Schedule

tidy_schedule(scoringPeriodId = 1)
#> # A tibble: 68 × 7
#>    seasonId matchupPeriodId matchupId teamId abbrev opponent isHome
#>       <int>           <int>     <int>  <int> <fct>  <fct>    <lgl> 
#>  1     2022               1         1      1 AUS    CHI      TRUE  
#>  2     2022               1         1      3 CHI    AUS      FALSE 
#>  3     2022               1         2      2 BOS    DEN      TRUE  
#>  4     2022               1         2      4 DEN    BOS      FALSE 
#>  5     2022               2         3      3 CHI    DEN      TRUE  
#>  6     2022               2         3      4 DEN    CHI      FALSE 
#>  7     2022               2         4      1 AUS    BOS      TRUE  
#>  8     2022               2         4      2 BOS    AUS      FALSE 
#>  9     2022               3         5      4 DEN    AUS      TRUE  
#> 10     2022               3         5      1 AUS    DEN      FALSE 
#> # … with 58 more rows

Message Board

league_messages(scoringPeriodId = 1)
#> # A tibble: 1 × 7
#>   id       type  author                        date                content messa…¹ viewa…²
#>   <chr>    <chr> <chr>                         <dttm>              <chr>   <list>  <list> 
#> 1 5af42ec9 NOTE  {22DFE7FF-9DF2-4F3B-9FE7-FF9… 2021-09-13 19:46:07 This [… <NULL>  <NULL> 
#> # … with abbreviated variable names ¹​messages, ²​viewableBy

Transaction Counter

transaction_counter()
#> # A tibble: 4 × 14
#>   seasonId scori…¹ teamId abbrev waive…² acqui…³ acqui…⁴ drops  misc moveT…⁵ moveT…⁶  paid
#>      <int>   <int>  <int> <fct>    <int>   <int>   <int> <int> <int>   <int>   <int> <dbl>
#> 1     2022       1      1 AUS          3       0       0     0     0       1       0     0
#> 2     2022       1      2 BOS          1       0       0     0     0       3       0     0
#> 3     2022       1      3 CHI          4       0       0     0     0       0       0     0
#> 4     2022       1      4 DEN          2       0       0     0     0       0       0     0
#> # … with 2 more variables: teamCharges <dbl>, trades <int>, and abbreviated variable
#> #   names ¹​scoringPeriodId, ²​waiverRank, ³​acquisitionBudgetSpent, ⁴​acquisitions,
#> #   ⁵​moveToActive, ⁶​moveToIR

Draft Recap

draft_recap()
#> # A tibble: 64 × 15
#>    seasonId autoDr…¹ bidAm…² pickId keeper lineu…³ nomin…⁴ overa…⁵ playe…⁶ reser…⁷ roundId
#>       <int>    <int>   <int>  <int> <lgl>  <fct>   <fct>     <int>   <int> <lgl>     <int>
#>  1     2022        7      NA      1 FALSE  RB      <NA>          1 4242335 TRUE          1
#>  2     2022        7      NA      2 FALSE  RB      <NA>          2 3117251 TRUE          1
#>  3     2022        7      NA      3 FALSE  WR      <NA>          3 2977187 TRUE          1
#>  4     2022        7      NA      4 FALSE  RB      <NA>          4 3068267 TRUE          1
#>  5     2022        7      NA      5 FALSE  WR      <NA>          5 4262921 TRUE          2
#>  6     2022        7      NA      6 FALSE  WR      <NA>          6 4362628 TRUE          2
#>  7     2022        7      NA      7 FALSE  RB      <NA>          7 3043078 TRUE          2
#>  8     2022        7      NA      8 FALSE  RB      <NA>          8 4241457 TRUE          2
#>  9     2022        7      NA      9 FALSE  RB      <NA>          9 3116593 FALSE         3
#> 10     2022        7      NA     10 FALSE  RB      <NA>         10 3054850 FALSE         3
#> # … with 54 more rows, 4 more variables: roundPickNumber <int>, teamId <int>,
#> #   abbrev <fct>, tradeLocked <lgl>, and abbreviated variable names ¹​autoDraftTypeId,
#> #   ²​bidAmount, ³​lineupSlot, ⁴​nominatingTeamId, ⁵​overallPickNumber, ⁶​playerId,
#> #   ⁷​reservedForKeeper

Recent Activity

recent_activity(scoringPeriodId = 1)
#> # A tibble: 64 × 14
#>    bidAm…¹ execu…² id    isAct…³ isLea…⁴ isPen…⁵ items proposedDate        scori…⁶ skipT…⁷
#>      <int> <chr>   <chr> <lgl>   <lgl>   <lgl>   <lis> <dttm>                <int> <lgl>  
#>  1       0 EXECUTE 7428… FALSE   FALSE   FALSE   <df>  2022-09-10 19:03:18       1 FALSE  
#>  2       0 EXECUTE 924e… FALSE   FALSE   FALSE   <df>  2022-09-10 19:03:18       1 FALSE  
#>  3       0 EXECUTE 1527… FALSE   FALSE   FALSE   <df>  2022-09-10 19:03:18       1 FALSE  
#>  4       0 EXECUTE 12f8… FALSE   FALSE   FALSE   <df>  2022-09-10 19:03:18       1 FALSE  
#>  5       0 EXECUTE 8c9c… FALSE   FALSE   FALSE   <df>  2022-09-10 19:03:18       1 FALSE  
#>  6       0 EXECUTE cd06… FALSE   FALSE   FALSE   <df>  2022-09-10 19:03:18       1 FALSE  
#>  7       0 EXECUTE e521… FALSE   FALSE   FALSE   <df>  2022-09-10 19:03:18       1 FALSE  
#>  8       0 EXECUTE 66aa… FALSE   FALSE   FALSE   <df>  2022-09-10 19:03:18       1 FALSE  
#>  9       0 EXECUTE 81ef… FALSE   FALSE   FALSE   <df>  2022-09-10 19:03:18       1 FALSE  
#> 10       0 EXECUTE deba… FALSE   FALSE   FALSE   <df>  2022-09-10 19:03:18       1 FALSE  
#> # … with 54 more rows, 4 more variables: status <chr>, teamId <int>, type <chr>,
#> #   processDate <dttm>, and abbreviated variable names ¹​bidAmount, ²​executionType,
#> #   ³​isActingAsTeamOwner, ⁴​isLeagueManager, ⁵​isPending, ⁶​scoringPeriodId,
#> #   ⁷​skipTransactionCounters

Players

list_players(limit = 10, proTeam = "Mia", status = "ALL")
#> # A tibble: 10 × 19
#>    seaso…¹ scori…²      id first…³ lastN…⁴ proTeam defau…⁵ injur…⁶ perce…⁷ perce…⁸ perce…⁹
#>      <int>   <dbl>   <int> <chr>   <chr>   <fct>   <fct>   <chr>     <dbl>   <dbl>   <dbl>
#>  1    2022       1 3116406 Tyreek  Hill    Mia     WR      A       9.90e-1  0.999   0.0194
#>  2    2022       1 4372016 Jaylen  Waddle  Mia     WR      A       7.36e-1  0.983  -0.0977
#>  3    2022       1 3119195 Chase   Edmonds Mia     RB      A       1.26e-1  0.876   0.954 
#>  4    2022       1 3116164 Mike    Gesicki Mia     TE      A       2.60e-1  0.764  -4.23  
#>  5    2022       1 4241479 Tua     Tagova… Mia     QB      A       9.55e-2  0.671   1.78  
#>  6    2022       1 2576414 Raheem  Mostert Mia     RB      A       2.96e-2  0.626   6.40  
#>  7    2022       1  -16015 Dolphi… D/ST    Mia     D/ST    <NA>    3.39e-1  0.424  10.4   
#>  8    2022       1 4036335 Cedrick Wilson… Mia     WR      A       1.54e-3  0.0413 -0.313 
#>  9    2022       1 3124679 Jason   Sanders Mia     K       A       1.48e-2  0.0191 -0.0680
#> 10    2022       1 3886818 Myles   Gaskin  Mia     RB      A       4.19e-4  0.0112  0.0755
#> # … with 8 more variables: positionalRanking <int>, totalRating <dbl>,
#> #   auctionValueAverage <dbl>, averageDraftPosition <dbl>, projectedScore <dbl>,
#> #   lastScore <dbl>, lastSeason <dbl>, currentSeason <dbl>, and abbreviated variable
#> #   names ¹​seasonId, ²​scoringPeriodId, ³​firstName, ⁴​lastName, ⁵​defaultPosition,
#> #   ⁶​injuryStatus, ⁷​percentStarted, ⁸​percentOwned, ⁹​percentChange

Scoreboard

live_scoring()
#> # A tibble: 4 × 6
#>   currentMatchupPeriod matchupId teamId abbrev totalPointsLive totalProjectedPointsLive
#>                  <int>     <int>  <int> <fct>            <dbl>                    <dbl>
#> 1                    1         1      1 AUS               127.                     127.
#> 2                    1         1      3 CHI               158.                     158.
#> 3                    1         2      2 BOS               139.                     152.
#> 4                    1         2      4 DEN               164.                     164.

Standings

league_standings()
#> # A tibble: 4 × 17
#>   seasonId scoringP…¹ teamId abbrev draft…² curre…³ playo…⁴ rankC…⁵ games…⁶ losses perce…⁷
#>      <int>      <int>  <int> <fct>    <int>   <int>   <int>   <int>   <dbl>  <int>   <dbl>
#> 1     2022          1      1 AUS          3       3       4       0       0      0       0
#> 2     2022          1      2 BOS          2       1       3       0       0      0       0
#> 3     2022          1      3 CHI          1       2       2       0       0      0       0
#> 4     2022          1      4 DEN          4       4       1       0       0      0       0
#> # … with 6 more variables: pointsAgainst <dbl>, pointsFor <dbl>, streakLength <int>,
#> #   streakType <chr>, ties <int>, wins <int>, and abbreviated variable names
#> #   ¹​scoringPeriodId, ²​draftDayProjectedRank, ³​currentProjectedRank, ⁴​playoffSeed,
#> #   ⁵​rankCalculatedFinal, ⁶​gamesBack, ⁷​percentage