mlbstatsR

library(mlbstatsR)

mlbstatsR es un package que tiene como objetivo facilitar las estadisticas, fotos de los jugadores, los logos y los colores de los equipos de la liga profesional de Baseball MLB, para visualizaciones y graficas

Que contiene el package

El package contiene las siguientes funciones:

Algunos Ejemplos

get_reference_players_mlb()

Descarga de la página baseball-reference desde el año 1876 las estadsiticas de los jugadores en Batting Pitching y Fielding.

En Batting podemos seleccionar standard, advanced, value, probability, ratio, baserunning, pitchesbatting, neutralizedbatting, situational, baserunning, cumulative . Como por ejemplo :

get_reference_players_mlb(1945, “batting”, “value”)

#> LOADING 1945 batting value from the index:
#> 'advanced', 'value', 'probability', 'ratio', 'baserunning', 'standard'
#> 'pitchesbatting', 'neutralizedbatting','situational', 'baserunning' o 'cumulative'
#> # A tibble: 865 × 27
#>     year stats stats_type rk    name  age   tm    g     pa    rbat  rbaser rdp  
#>    <dbl> <chr> <chr>      <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>  <chr>
#>  1  1945 batt… value      1     Jame… 26    KCM   2     6     1     0      0    
#>  2  1945 batt… value      2     Ace … 35    NYG   65    20    -2    0      0    
#>  3  1945 batt… value      3     Bust… 30    2TM   154   707   15    0      1    
#>  4  1945 batt… value      4     Emer… 34    NBY   19    56    0     0      0    
#>  5  1945 batt… value      5     Morr… 29    2TM   70    174   -1    -1     1    
#>  6  1945 batt… value      6     Bill… 32    NYC   8     10    -2    0      0    
#>  7  1945 batt… value      7     Nate… 31    BSN   22    53    -5    0      0    
#>  8  1945 batt… value      8     Stan… 28    2TM   34    89    -4    1      0    
#>  9  1945 batt… value      9     John… 29    2TM   127   540   -16   -2     -1   
#> 10  1945 batt… value      10    Pete… 41    2TM   8     5     0     0      0    
#> # … with 855 more rows, and 15 more variables: rfield <chr>, rpos <chr>,
#> #   raa <chr>, waa <chr>, rrep <chr>, rar <chr>, war <chr>,
#> #   waa_wl_percent <chr>, x162wl_percent <chr>, o_war <chr>, d_war <chr>,
#> #   o_rar <chr>, salary <chr>, acquired <chr>, pos_summary <chr>

En Pitching podemos seleccionar advanced, value, probability, ratio, battingagainst, startingpitching, standard, reliefpitching, neutralizedpitching, baserunning o cumulative. Como por ejemplo :

get_reference_players_mlb(1965, “pitching”, “ratio”)

#> LOADING 1965 pitching ratio from the index:
#> 'advanced', 'value', 'probability', 'ratio', 'battingagainst', 'startingpitching',
#> 'standard', 'reliefpitching', 'neutralizedpitching', 'baserunning' o 'cumulative'
#> # A tibble: 341 × 25
#>     year stats    stats_type rk    name  age   tm    ip    ptn_percent hr_percent
#>    <dbl> <chr>    <chr>      <chr> <chr> <chr> <chr> <chr> <chr>       <chr>     
#>  1  1965 pitching ratio      1     Ted … 32    CHC   136.1 57%         1.2%      
#>  2  1965 pitching ratio      2     Hank… 34    DET   208.1 19%         2.7%      
#>  3  1965 pitching ratio      3     Jack… 24    KCA   51.1  59%         1.4%      
#>  4  1965 pitching ratio      4     Matt… 26    SFG   2.0   30%         0.0%      
#>  5  1965 pitching ratio      5     Don … 22    HOU   6.0   35%         0.0%      
#>  6  1965 pitching ratio      6     Gerr… 24    CIN   54.0  27%         1.5%      
#>  7  1965 pitching ratio      7     Denn… 24    STL   7.1   58%         0.0%      
#>  8  1965 pitching ratio      8     Jack… 28    PHI   99.0  61%         0.9%      
#>  9  1965 pitching ratio      9     Stev… 27    BAL   220.2 20%         1.8%      
#> 10  1965 pitching ratio      10    Ed B… 21    BAL   4.1   82%         0.0%      
#> # … with 331 more rows, and 15 more variables: so_percent <chr>,
#> #   bb_percent <chr>, so_bb_percent <chr>, xbh_percent <chr>,
#> #   x_h_percent <chr>, gb_fb <chr>, go_ao <chr>, ip_percent <chr>,
#> #   ld_percent <chr>, hr_fb <chr>, if_fb <chr>, opp <chr>, dp <chr>,
#> #   percent <chr>, p_au <chr>

En Fielding podemos seleccionar appearances, pitcher, catcher, firstbase, secondbase, thirdbase, shortstop, leftfield, centerfield, rightfield, outfield. Como por ejemplo :

get_reference_players_mlb(2002, “fielding”, “appearances”)

#> LOADING 2002 fielding appearances from the index:
#> 'appearances', 'pitcher', 'catcher', 'firstbase', 'secondbase', 'thirdbase',
#> 'shortstop', 'leftfield', 'centerfield', 'rightfield', 'outfield'
#> # A tibble: 1,218 × 25
#>     year stats    stats_type  rk    name   age   tm    yrs   g     gs    batting
#>    <dbl> <chr>    <chr>       <chr> <chr>  <chr> <chr> <chr> <chr> <chr> <chr>  
#>  1  2002 fielding appearances 1     Paul … 34    SEA   9     7     5     0      
#>  2  2002 fielding appearances 2     Brent… 24    TBD   2     117   115   117    
#>  3  2002 fielding appearances 3     Bobby… 28    PHI   7     157   153   157    
#>  4  2002 fielding appearances 4     Jose … 24    CIN   2     6     5     6      
#>  5  2002 fielding appearances 5     Juan … 32    DET   7     65    0     4      
#>  6  2002 fielding appearances 6     Terry… 29    PHI   8     46    19    45     
#>  7  2002 fielding appearances 7     Jerem… 23    KCR   1st   34    7     0      
#>  8  2002 fielding appearances 8     Benny… 30    2TM   5     61    41    61     
#>  9  2002 fielding appearances 9     Kurt … 23    SFG   2     6     4     6      
#> 10  2002 fielding appearances 10    Israe… 29    MIL   3     16    6     16     
#> # … with 1,208 more rows, and 14 more variables: defense <chr>, p <chr>,
#> #   c <chr>, x1b <chr>, x2b <chr>, x3b <chr>, ss <chr>, lf <chr>, cf <chr>,
#> #   rf <chr>, of <chr>, dh <chr>, ph <chr>, pr <chr>

get_reference_team_mlb()

Descarga de la página baseball-reference desde el año 1876 las estadisticas de los equipos en Batting Pitching y Fielding.

En Batting podemos seleccionar standard, advanced, value, probability, ratio, baserunning, pitchesbatting, neutralizedbatting, situational. Como por ejemplo :

get_reference_team_mlb(2021,“batting”, “advanced”)

#> LOADING 2021 batting advanced from the index:
#> 'advanced', 'value', 'probability', 'ratio', 'baserunning',
#> 'standard', 'pitchesbatting', 'situational' o 'baserunning'
#> # A tibble: 34 × 26
#>     year stats   stats_type x              batting batting_2 batting_3 batting_4
#>    <dbl> <chr>   <chr>      <chr>          <chr>   <chr>     <chr>     <chr>    
#>  1  2021 batting advanced   Tm             rOBA    Rbat+     BAbip     ISO      
#>  2  2021 batting advanced   Arizona Diamo… .309    86        .294      .146     
#>  3  2021 batting advanced   Atlanta Braves .331    94        .283      .192     
#>  4  2021 batting advanced   Baltimore Ori… .311    89        .288      .167     
#>  5  2021 batting advanced   Boston Red Sox .334    102       .309      .185     
#>  6  2021 batting advanced   Chicago Cubs   .315    89        .289      .170     
#>  7  2021 batting advanced   Chicago White… .334    109       .307      .166     
#>  8  2021 batting advanced   Cincinnati Re… .332    90        .296      .180     
#>  9  2021 batting advanced   Cleveland Ind… .313    91        .278      .169     
#> 10  2021 batting advanced   Colorado Rock… .323    82        .295      .167     
#> # … with 24 more rows, and 18 more variables: batting_ratios <chr>,
#> #   batting_ratios_2 <chr>, batting_ratios_3 <chr>, batted_ball <chr>,
#> #   batted_ball_2 <chr>, batted_ball_3 <chr>, batted_ball_4 <chr>,
#> #   batted_ball_5 <chr>, batted_ball_6 <chr>, batted_ball_7 <chr>,
#> #   batted_ball_8 <chr>, batted_ball_9 <chr>, win_probability <chr>,
#> #   win_probability_2 <chr>, win_probability_3 <chr>, baserunning <chr>,
#> #   baserunning_2 <chr>, baserunning_3 <chr>

En Pitching podemos seleccionar standard, batting, value, probability, ratio, battingagainst, startingpitching, reliefpitching, basesituation. Como por ejemplo:

get_reference_team_mlb(1980, “pitching”, “battingagainst”)

#> LOADING 1980 pitching battingagainst from the index:
#> 'batting', 'value', 'probability', 'ratio', 'battingagainst', 'startingpitching',
#> 'reliefpitching',  'basesituation', 'standard'
#> # A tibble: 29 × 30
#>     year stats  stats_type tm    ra_g  p_au  g     pa    ab    r     h     x2b  
#>    <dbl> <chr>  <chr>      <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#>  1  1980 pitch… batting    Atla… 4.10  ""    161   6028  5423  660   1397  232  
#>  2  1980 pitch… batting    Balt… 3.95  ""    162   6131  5510  640   1438  241  
#>  3  1980 pitch… batting    Bost… 4.79  ""    160   6192  5571  767   1557  287  
#>  4  1980 pitch… batting    Cali… 4.98  ""    160   6256  5563  797   1548  271  
#>  5  1980 pitch… batting    Chic… 4.49  ""    162   6402  5613  728   1525  263  
#>  6  1980 pitch… batting    Chic… 4.46  ""    162   6199  5448  722   1434  217  
#>  7  1980 pitch… batting    Cinc… 4.11  ""    163   6143  5511  670   1404  246  
#>  8  1980 pitch… batting    Clev… 5.04  ""    160   6221  5531  807   1519  230  
#>  9  1980 pitch… batting    Detr… 4.64  ""    163   6335  5630  757   1505  252  
#> 10  1980 pitch… batting    Hous… 3.61  ""    163   6160  5562  589   1367  203  
#> # … with 19 more rows, and 18 more variables: x3b <chr>, hr <chr>, sb <chr>,
#> #   cs <chr>, bb <chr>, so <chr>, ba <chr>, obp <chr>, slg <chr>, ops <chr>,
#> #   b_abip <chr>, tb <chr>, gdp <chr>, hbp <chr>, sh <chr>, sf <chr>,
#> #   ibb <chr>, roe <chr>

En Fielding podemos seleccionar standard, appearances, pitcher, catcher, firstbase, secondbase, thirdbase, shortstop, leftfield, centerfield, rightfield, outfield. Ejemplo:

get_reference_team_mlb(1980, “fielding”, “centerfield”)

#> LOADING 1980 fielding centerfield from the index:
#> 'appearances', 'pitcher', 'catcher', 'firstbase', 'secondbase', 'thirdbase',
#>          'shortstop', 'leftfield', 'centerfield', 'rightfield', 'outfield'
#> # A tibble: 29 × 20
#>     year stats  stats_type tm     number_fld ra_g  g     gs    cg    inn   ch   
#>    <dbl> <chr>  <chr>      <chr>  <chr>      <chr> <chr> <chr> <chr> <chr> <chr>
#>  1  1980 field… specialpo… Atlan… 5          4.10  161   161   150   1428… 412  
#>  2  1980 field… specialpo… Balti… 2          3.95  162   162   154   1460… 524  
#>  3  1980 field… specialpo… Bosto… 7          4.79  160   160   146   1441… 457  
#>  4  1980 field… specialpo… Calif… 4          4.98  160   160   134   1428… 504  
#>  5  1980 field… specialpo… Chica… 6          4.49  162   162   129   1479… 424  
#>  6  1980 field… specialpo… Chica… 5          4.46  162   162   149   1435… 450  
#>  7  1980 field… specialpo… Cinci… 6          4.11  163   163   74    1459… 474  
#>  8  1980 field… specialpo… Cleve… 6          5.04  160   160   143   1428… 466  
#>  9  1980 field… specialpo… Detro… 5          4.64  163   163   139   1467… 483  
#> 10  1980 field… specialpo… Houst… 5          3.61  163   163   148   1482… 446  
#> # … with 19 more rows, and 9 more variables: po <chr>, a <chr>, e <chr>,
#> #   dp <chr>, fld_percent <chr>, rtot <chr>, rtot_yr <chr>, rtz <chr>,
#> #   rof <chr>

get_reference_team_standings()

Nos devuelve la clasificación de todas las maneras posibles y proyecciones de victorias

#> # A tibble: 31 × 25
#>     year    rk tm              w     l w_l_percent     r    ra rdiff   sos   srs
#>    <dbl> <int> <chr>       <int> <int>       <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#>  1  1999     1 Atlanta Br…   103    59       0.636   5.2   4.1   1.1   0.1   1.2
#>  2  1999     2 Arizona Di…   100    62       0.617   5.6   4.2   1.4   0.1   1.5
#>  3  1999     3 New York Y…    98    64       0.605   5.6   4.5   1    -0.3   0.8
#>  4  1999     4 Houston As…    97    65       0.599   5.1   4.2   0.9   0.1   1  
#>  5  1999     5 Cleveland …    97    65       0.599   6.2   5.3   0.9  -0.3   0.6
#>  6  1999     6 New York M…    97    66       0.595   5.2   4.4   0.9   0.2   1  
#>  7  1999     7 Cincinnati…    96    67       0.589   5.3   4.4   0.9   0.1   1.1
#>  8  1999     8 Texas Rang…    95    67       0.586   5.8   5.3   0.5  -0.2   0.3
#>  9  1999     9 Boston Red…    94    68       0.58    5.2   4.4   0.7  -0.2   0.5
#> 10  1999    10 Oakland At…    87    75       0.537   5.5   5.2   0.3  -0.2   0.1
#> # … with 21 more rows, and 14 more variables: pyth_wl <chr>, luck <int>,
#> #   v_east <chr>, v_cent <chr>, v_west <chr>, inter <chr>, home <chr>,
#> #   road <chr>, ex_inn <chr>, x1run <chr>, v_rhp <chr>, v_lhp <chr>,
#> #   x500 <chr>, x500_2 <chr>

espn_player_stats()

Descarga de la pagina de ESPN las estadisticas de los jugadores de la MLB desde el año 2002. Podemos seleccionar Regular o Playoffs y las estadisticas de batting, pitching y fielding.

Regular

espn_player_stats(2015, “pitching”, “regular”)

#> Getting pitching stats de la regular season del 2015!
#> # A tibble: 78 × 23
#>     year season_type  rank name            team  pos   games_played games_started
#>    <dbl> <chr>       <int> <chr>           <chr> <chr>        <int>         <int>
#>  1  2015 regular         1 Zack Greinke    LAD   SP              32            32
#>  2  2015 regular         2 Jake Arrieta    CHC   SP              33            33
#>  3  2015 regular         3 Clayton Kershaw LAD   SP              33            33
#>  4  2015 regular         4 David Price     DET   SP              32            32
#>  5  2015 regular         5 Dallas Keuchel  HOU   SP              33            33
#>  6  2015 regular         6 Jacob deGrom    NYM   SP              30            30
#>  7  2015 regular         7 Gerrit Cole     PIT   SP              32            32
#>  8  2015 regular         8 Matt Harvey     NYM   SP              29            29
#>  9  2015 regular         9 Sonny Gray      OAK   SP              31            31
#> 10  2015 regular        10 John Lackey     STL   SP              33            33
#> # … with 68 more rows, and 15 more variables: quality_starts <int>,
#> #   earned_run_avg <dbl>, wins <int>, losses <int>, saves <int>, holds <int>,
#> #   innings_pitched <dbl>, hits <int>, earned_runs <int>, home_runs <int>,
#> #   walks <int>, strikeouts <int>, strikes_x_9_i <dbl>, war <dbl>, whip <dbl>

Playoffs

espn_player_stats(2004, “batting”, “playoffs”)

#> Getting batting stats de los playoffs del 2004!
#> # A tibble: 61 × 23
#>     year season_type  rank name     team  pos   games_played at_bats  runs  hits
#>    <dbl> <chr>       <int> <chr>    <chr> <chr>        <int>   <int> <int> <int>
#>  1  2004 playoffs        1 Andruw … ATL   LF               5      19     4    10
#>  2  2004 playoffs        2 Darin E… ANA   LF               3      10     2     5
#>  3  2004 playoffs        3 Michael… MIN   LF               4      15     1     7
#>  4  2004 playoffs        4 Carlos … HOU   OF              12      46    21    20
#>  5  2004 playoffs        5 Albert … STL   1B              15      58    15    24
#>  6  2004 playoffs        6 Hideki … NYY   LF              11      51    12    21
#>  7  2004 playoffs        7 David O… BOS   DH              14      55    13    22
#>  8  2004 playoffs        8 Rafael … ATL   2B               5      21     5     8
#>  9  2004 playoffs        9 Troy Gl… ANA   1B               3      11     3     4
#> 10  2004 playoffs       10 Torii H… MIN   RF               4      17     5     6
#> # … with 51 more rows, and 13 more variables: batting_avg <dbl>, doubles <int>,
#> #   triples <int>, home_runs <int>, runs_batted_in <int>, total_bases <int>,
#> #   walks <int>, strikeouts <int>, stolen_bases <int>, on_base_pct <dbl>,
#> #   slugging_pct <dbl>, opb_slg_pct <dbl>, war <dbl>

espn_team_stats()

Descarga de la pagina de ESPN las estadisticas de los equipos de la MLB desde el año 2002. Podemos seleccionar Regular o Playoffs y las estadisticas de batting, pitching y fielding.

Regular

espn_team_stats(2021, “fielding”, “regular”)

#> Getting fielding stats de la regular season del 2021!
#> # A tibble: 30 × 10
#>     year season_type  rank team   g_played errors fielding_percen… total_chances
#>    <dbl> <chr>       <int> <chr>     <int>  <int>            <dbl> <chr>        
#>  1  2021 regular         1 Houst…      142     59            0.988 5,084        
#>  2  2021 regular         2 Oakla…      143     58            0.988 4,794        
#>  3  2021 regular         3 Color…      144     65            0.987 5,094        
#>  4  2021 regular         4 Balti…      143     55            0.987 4,296        
#>  5  2021 regular         5 Pitts…      143     55            0.987 4,126        
#>  6  2021 regular         6 Atlan…      142     62            0.986 4,573        
#>  7  2021 regular         7 San F…      143     70            0.986 5,121        
#>  8  2021 regular         8 Chica…      144     69            0.986 4,956        
#>  9  2021 regular         9 Seatt…      143     71            0.986 5,060        
#> 10  2021 regular        10 San D…      142     72            0.986 5,095        
#> # … with 20 more rows, and 2 more variables: putouts <chr>, assists <chr>

Playoffs

espn_team_stats(2011, “fielding”, “playoffs”)

#> Getting fielding stats de los playoffs del 2011!
#> # A tibble: 8 × 10
#>    year season_type  rank team    g_played errors fielding_percen… total_chances
#>   <dbl> <chr>       <int> <chr>      <int>  <int>            <dbl>         <int>
#> 1  2011 playoffs        1 Tampa …        4      0            1               143
#> 2  2011 playoffs        2 New Yo…        5      1            0.995           194
#> 3  2011 playoffs        3 Arizon…        5      1            0.994           164
#> 4  2011 playoffs        4 Detroi…       11      5            0.988           401
#> 5  2011 playoffs        5 St. Lo…       18     10            0.985           685
#> 6  2011 playoffs        6 Philad…        5      3            0.984           190
#> 7  2011 playoffs        7 Texas …       17     12            0.981           646
#> 8  2011 playoffs        8 Milwau…       11     12            0.971           408
#> # … with 2 more variables: putouts <int>, assists <int>

Espero que sea util