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五 MLB 全明星团队数据集

五 MLB 全明星团队数据集

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Business,Baseball Classification

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    Data Structure ?

    * 以上分析是由系统提取分析形成的结果,具体实际数据为准。

    README.md

    Content # MLB All-Star Teams This folder contains data behind the story [The Best MLB All-Star Teams Ever](http://fivethirtyeight.com/features/the-best-mlb-all-star-teams-ever/). Estimates of most talented MLB All-Star teams, 1933-2015 `allstar_team_talent.csv` contains team talent estimates with the following headers: Header | Definition ---|--------- `yearID` | The season in question `gameNum` | Order of All-Star Game for the season (in years w/ multiple ASGs; set to 0 when only 1 per year) `gameID` | Game ID at Baseball-Reference.com `lgID` | League of All-Star team `tm_OFF_talent` | Total runs of offensive talent above average per game (36 plate appearances) `tm_DEF_talent` | Total runs of fielding talent above average per game (36 plate appearances) `tm_PIT_talent` | Total runs of pitching talent above average per game (9 innings) `MLB_avg_RPG` | MLB average runs scored/game that season `talent_RSPG` | Expected runs scored per game based on talent (MLB R/G + team OFF talent) `talent_RAPG` | Expected runs allowed per game based on talent (MLB R/G - team DEF talent- team PIT talent) `unadj_PYTH` | Unadjusted pythagorean talent rating; PYTH =(RSPG^1.83)/(RSPG^1.83+RAPG^1.83) `timeline_adj` | Estimate of relative league quality where 2015 MLB = 1.00 `SOS` | Strength of schedule faced; adjusts an assumed .500 SOS downward based on timeline adjustment `adj_PYTH` | Adjusted pythagorean record; =(SOS*unadj_Pyth)/((2*unadj_Pyth*SOS)-SOS-unadj_Pyth+1) `no_1_player` | Best player according to combo of actual PA/IP and talent `no_2_player` | 2nd-best player according to combo of actual PA/IP and talent `allstar_player_talent.csv` contains team player estimates with the following headers: Header | Definition ---|--------- `bbref_ID` | Player's ID at Baseball-Reference.com `yearID` | The season in question `gameNum` | Order of All-Star Game for the season (in years w/ multiple ASGs; set to 0 when only 1 per year) `gameID` | Game ID at Baseball-Reference.com `lgID` | League of All-Star team `startingPos` | Postion (according to baseball convention; 1=pitcher, 2=catcher, etc.) if starter `OFF600` | Estimate of offensive talent, in runs above league average per 600 plate appearances `DEF600` | Estimate of fielding talent, in runs above league average per 600 plate appearances `PITCH200` | Estimate of pitching talent, in runs above league average per 200 innings pitched `asg_PA` | Number of plate appearances in the All-Star Game itself `asg_IP` | Number of innings pitched in the All-Star Game itself `OFFper9innASG` | Expected offensive runs added above average (from talent) based on PA in ASG, scaled to a 9-inning game `DEFper9innASG` | Expected defensive runs added above average (from talent) based on PA in ASG, scaled to a 9-inning game `PITper9innASG` | Expected pitching runs added above average (from talent) based on IP in ASG, scaled to a 9-inning game `TOTper9innASG` | Expected runs added above average (from talent) based on PA/IP in ASG, scaled to a 9-inning game Context This is a dataset from [FiveThirtyEight](https://fivethirtyeight.com/) hosted on their [GitHub](https://github.com/fivethirtyeight/data). Explore FiveThirtyEight data using Kaggle and all of the data sources available through the FiveThirtyEight [organization page](https://www.kaggle.com/fivethirtyeight)! * Update Frequency: This dataset is updated daily. Acknowledgements This dataset is maintained using GitHub's [API](https://developer.github.com/v3/?) and Kaggle's [API](https://github.com/Kaggle/kaggle-api). This dataset is distributed under the [Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/) license.
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