Fangraphs Batting Leaderboards

Out:

       #            Name   Team  Season  Age  ...  Cent%+  Oppo%+  Soft%+  Med%+  Hard%+
0      1      Will Smith    SFG    2019   29  ...       0     400       0      0     257
1      2    Oliver Drake    TBR    2019   32  ...     295       0       0      0     264
2      3    Ruben Alaniz  - - -    2019   28  ...     290       0     594      0       0
3      4       Seth Lugo    NYM    2019   29  ...     290       0     594      0       0
4      5    John Brebbia    STL    2019   29  ...       0     400     594      0       0
..   ...             ...    ...     ...  ...  ...     ...     ...     ...    ...     ...
985  986     Rico Garcia    COL    2019   25  ...
986  987  Adrian Morejon    SDP    2019   20  ...
987  988  Ronald Bolanos    SDP    2019   22  ...       0     400       0      0     257
988  989   Elvis Luciano    TOR    2019   19  ...
989  990   Yusei Kikuchi    SEA    2019   28  ...       0     404       0    220       0

[990 rows x 306 columns]
464
[('fg_guts_constants', 'fg_guts_constants.csv'), ('fg_batting_1871', 'fg_bat_1871.csv'), ('fg_batting_1872', 'fg_bat_1872.csv'), ('fg_batting_1873', 'fg_bat_1873.csv'), ('fg_batting_1874', 'fg_bat_1874.csv'), ('fg_batting_1875', 'fg_bat_1875.csv'), ('fg_batting_1876', 'fg_bat_1876.csv'), ('fg_batting_1877', 'fg_bat_1877.csv'), ('fg_batting_1878', 'fg_bat_1878.csv'), ('fg_batting_1879', 'fg_bat_1879.csv')]
     Season   wOBA  wOBAScale    wBB   wHBP  ...  runSB  runCS   R/PA     R/W   cFIP
0      2021  0.307      1.257  0.689  0.720  ...    0.2 -0.402  0.116   9.621  3.093
1      2020  0.320      1.185  0.699  0.728  ...    0.2 -0.435  0.126  10.282  3.191
2      2019  0.320      1.157  0.690  0.719  ...    0.2 -0.435  0.126  10.296  3.214
3      2018  0.315      1.226  0.690  0.720  ...    0.2 -0.407  0.117   9.714  3.161
4      2017  0.321      1.185  0.693  0.723  ...    0.2 -0.423  0.122  10.048  3.158
..      ...    ...        ...    ...    ...  ...    ...    ...    ...     ...    ...
146    1875  0.261      1.274  0.730  0.761  ...    0.2 -0.531  0.156  12.231  2.370
147    1874  0.282      1.145  0.760  0.789  ...    0.2 -0.629  0.179  14.227  2.808
148    1873  0.303      1.025  0.788  0.814  ...    0.2 -0.741  0.207  16.482  2.932
149    1872  0.297      1.020  0.791  0.816  ...    0.2 -0.763  0.213  16.926  3.508
150    1871  0.312      0.909  0.797  0.820  ...    0.2 -0.863  0.237  18.954  3.580

[151 rows x 14 columns]

from pybbda.data import FangraphsData

fg_data = FangraphsData()

print(fg_data.fg_batting_2019)

print(len(fg_data.tables))
print(list(fg_data.tables.items())[0:10])

print(fg_data.fg_guts_constants)