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@sahirb/nba-stats
Advanced tools
NBA data and Javascript APIs to access stats. Also the util APIs that were used to build the stats files.
🏀 Making NBA data more accessible for fellow fanatics! 🥹
npm install @sahirb/nba-stats
The package includes .txt files of all scores/etc and simple javascript functions for accessing the data! 🤯
No more querying nba.com, basketball-reference, espn, etc! 🤗
💰 Evaluate mid-game scenarios based on "similar" teams in past games/seasons as defined by you
🎶 Easily combine stats across seasons to find true historical outliers (both 🏆 && 🤮)
🚦 No more getting rate limited by web apis
Local copy of data with functions to access - with these building blocks the possibilities are endless! 😬
| Stat | Season | Notes |
|---|---|---|
| Points per quarter | 2003-2023 (20 seasons) | basketball-reference.com/boxscores |
| Possessions per game | ^ | basketball-reference.com/teams |
| Offensive/defensive efficiency | ^ | basketball-reference.com/boxscores |
| Points per game | ^ | derived from points per quarter |
| Points per possession | ^ | derived |
... and some others you'd reasonably expect 🥳
Possible Future Data:
If you have a request, check the previous README version for instructions on how to get priority 😆
If we want the top 3 offenses from the last 5 years:
// offensiveEfficiencyRank: 3, pointsRank: 11
// guess which eastern conference team isn't good, just slow!?
// hint: 'the mecca of basketball' but not for the home team lol
[2022, 2021, 2020, 2019, 2018].forEach(year => {
const sortedTop5 = bref.getSeasonSummaries(year)
.filter(summary => {
return summary.offensiveEfficiencyRank <= 5;
}).map(summary => {
return {
teamName: summary.teamName,
offensiveEfficiencyRank: summary.offensiveEfficiencyRank,
pointsRank: summary.pointsScoredPerGameRank,
offensiveEfficiency: summary.offensiveEfficiency,
points: summary.pointsScoredPerGame,
pace: summary.pace
}
}).sort((a, b) => {
return a.offRank - b.offRank;
});
console.log(year);
console.log(sortedTop3);
});
// -- result --
2022
[
{
teamName: 'Sacramento',
offensiveEfficiencyRank: 1,
pointsRank: 1,
offensiveEfficiency: 119.4,
points: 120.70731707317073,
pace: 100.3
},
{
teamName: 'Boston',
offensiveEfficiencyRank: 2,
pointsRank: 4,
offensiveEfficiency: 118,
points: 117.9390243902439,
pace: 98.5
},
{
teamName: 'New York',
offensiveEfficiencyRank: 3,
pointsRank: 11,
offensiveEfficiency: 117.8,
points: 116.02439024390245,
pace: 97.1
}
]
2021
[
{
teamName: 'Atlanta',
offensiveEfficiencyRank: 2,
...
}
]
...
If we want the game total & q2 difference for 2022 Lakers road losses (sorted by game total):
const sortedLakers = bref.getSeasonScores(2022)
.filter(boxScore => {
return
boxScore.roadTeam === 'LA Lakers' &&
boxScore.winningTeam !== 'LA Lakers';
}).sort((boxScoreA, boxScoreB) => {
return
boxScoreA.roadTeamTotal - boxScoreB.roadTeamTotal;
}).map(boxScore => {
return {
gameDate: boxScore.gameDate,
roadTeamTotal: boxScore.roadTeamTotal,
roatTeamSecondQuarter: boxScore.periodBreakdown[1].roadTotal
}
});
console.log(sortedLakers);
// -- result --
[
{ date: '2022-12-28', total: 98, diff: -14, q2Diff: -1 },
{ date: '2022-10-26', total: 99, diff: -11, q2Diff: 4 },
{ date: '2022-11-9', total: 101, diff: -13, q2Diff: 15 },
{ date: '2022-10-28', total: 102, diff: -9, q2Diff: 3 },
{ date: '2022-12-6', total: 102, diff: -14, q2Diff: -7 },
{ date: '2022-12-19', total: 104, diff: -26, q2Diff: -10 },
{ date: '2023-1-30', total: 104, diff: -17, q2Diff: 1 },
{ date: '2022-11-22', total: 105, diff: -10, q2Diff: 6 },
{ date: '2022-10-18', total: 109, diff: -14, q2Diff: -4 },
{ date: '2023-1-9', total: 109, diff: -13, q2Diff: -8 },
{ date: '2023-2-28', total: 109, diff: -12, q2Diff: 7 },
{ date: '2023-3-15', total: 110, diff: -4, q2Diff: -2 },
{ date: '2022-12-7', total: 113, diff: -13, q2Diff: -15 },
{ date: '2022-12-25', total: 115, diff: -9, q2Diff: 4 },
{ date: '2023-2-13', total: 115, diff: -12, q2Diff: -4 },
{ date: '2022-11-7', total: 116, diff: -23, q2Diff: 3 },
{ date: '2023-4-5', total: 118, diff: -7, q2Diff: -13 },
{ date: '2022-12-21', total: 120, diff: -14, q2Diff: -9 },
{ date: '2023-1-28', total: 121, diff: -4, q2Diff: 7 },
{ date: '2022-12-9', total: 122, diff: -11, q2Diff: 9 },
{ date: '2023-2-4', total: 126, diff: -5, q2Diff: 9 }
]
To get all scores for one/more teams:
const lakersThunder = bref.getSeasonScoresSimple(2022, ['LA Lakers', 'Oklahoma City']);
console.log(lakersThunder.length);
console.log(lakersThunder[0]);
// -- result --
160
{
gameDate: '2021-10-19',
roadTeam: 'Golden State',
homeTeam: 'LA Lakers',
...
winningTeamScore: 121,
losingTeamScore: 114
}
Data Model
BoxScore: {
gameDate: string,
numExtraPeriods: number,
roadTeam: string,
homeTeam: string,
gameTotal: number,
roadTeamTotal: number,
homeTeamTotal: number,
winningTeam: string,
losingTeam: string,
winningTeamScore: number,
losingTeamScore: number,
periodBreakdown: []PeriodBreakdown
}
PeriodBreakdown: {
period: number,
roadTotal: number,
homeTotal: number
}
Functions
getSeasonScores(season_start_year) => BoxScore[]
getSeasonScoresSimple(season_start_year, teams_to_include) => BoxScore[]
season_start_year: number
teams_to_include?: string[] // exclude to get all teams
Parse basketball-reference.com for NBA data! 🏀 🧬
This was used to create the NBA Data! 🙏🏽
Currently supports getting game totals. For example, if we're interested in 2023-11-16 https://www.basketball-reference.com/boxscores/?month=11&day=16&year=2023

const bref = require('@sahirb/basketball-reference')
bref.getBoxScores({
year: 2023,
month: 11,
day: 16
});
// -- result --
{
gameDate: '2023-11-16',
numExtraPeriods: 0,
periodBreakdown: [
{ period: 1, roadTotal: 39, homeTotal: 24 },
{ period: 2, roadTotal: 28, homeTotal: 36 },
{ period: 3, roadTotal: 27, homeTotal: 25 },
{ period: 4, roadTotal: 34, homeTotal: 24 }
],
roadTeam: 'Oklahoma City',
homeTeam: 'Golden State',
gameTotal: 237,
roadTeamTotal: 128,
homeTeamTotal: 109,
winningTeam: 'Oklahoma City',
losingTeam: 'Golden State',
winningTeamScore: 128,
losingTeamScore: 109
},
{
... // NJ Nets at Miami
}
Data Model
BoxScore: {
gameDate: string,
numExtraPeriods: number,
roadTeam: string,
homeTeam: string,
gameTotal: number,
roadTeamTotal: number,
homeTeamTotal: number,
winningTeam: string,
losingTeam: string,
winningTeamScore: number,
losingTeamScore: number,
periodBreakdown: []PeriodBreakdown
}
PeriodBreakdown: {
period: number,
roadTotal: number,
homeTotal: number
}
Functions
getBoxScores(date) => Promise<BoxScore[]>
date: {
year: number,
month: number,
day: number
}
getBoxScoresForDates(last_game_date, num_additional_days, file_path, box_score_transformation) => Promise<BoxScore[]>
last_game_date: {
year: number,
month: number,
day: number
}
num_additional_days: number // additional days going back from last_game_date
file_path?: string // (optional) local file to save result to
box_score_transformation?: (BoxScore) => void // (optional) callback applied to each BoxScore in the response (and in the local file if file_path specified)
How to use - simple
const bref = require('@sahirb/basketball-reference')
const date = {
year: 2023,
month: 11,
day: 16
};
bref.getBoxScores(date).then(boxScores => {
boxScores.forEach(boxScore => console.log(boxScore));
});
How to use - advanced (save multiple days to file with new 'feeling' column)
const bref = require('@sahirb/basketball-reference')
const last_game_date = {
year: 2023,
month: 11,
day: 16
};
const num_additional_days = 2;
const local_file_path = "/Users/boghani/basketball-reference-js-box-score/output_json.txt";
const box_score_transformation = (boxScore) => {
let feeling = 'snooze fest';
if (boxScore.gameTotal > 220) {
feeling = 'wow points and stuff';
if (boxScore.winningTeamScore - boxScore.losingTeamScore < 10) {
feeling = 'be still my heart <4';
}
}
boxScore.feeling = feeling;
};
bref.getBoxScoresForDates(last_game_date, num_additional_days, local_file_path, box_score_transformation).then(boxScores => {
boxScores.forEach(boxScore => console.log(boxScore));
});
FAQs
NBA data and Javascript APIs to access stats. Also the util APIs that were used to build the stats files.
The npm package @sahirb/nba-stats receives a total of 19 weekly downloads. As such, @sahirb/nba-stats popularity was classified as not popular.
We found that @sahirb/nba-stats demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 1 open source maintainer collaborating on the project.
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