Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-13 00:04 UTC

swar / nba_api

An API Client package to access the APIs for NBA.com

PythonMIT★ 3,740 stars⑂ 723 forkssince Sep 2018View on GitHub ↗

swar/nba_api holds a health index of 75 out of 100, placing it in the Good band. It scores highest on Community & Adoption (82/100) and lowest on Security (46/100). It was last updated 128 days ago. 2 contributors account for most of its recent work.

75
overall / 100
Good

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean, calibrated against the distribution of the public record so bands carry percentile meaning; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At Risk ceiling of 34.

75
Exceptional93-100The record's top tier (≈ top 5%); essentially all checked criteria met
Excellent80-92Strong across the board; minor gaps
Good65-79Healthy; gaps are limited and manageable
Moderate50-64Acceptable with notable gaps; review recommended
Weak35-49Material weaknesses across several areas
At Risk20-34Significant weaknesses; adoption warrants caution
Critical1-19Severe problems (abandoned, single-maintainer, no hygiene)
VitalityCommunity &AdoptionSustainability &GovernanceEngineeringQualitySecurityAI Readiness

Score profile

Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.

The weighted overall 65 is calibrated to 75 on the published index scale (record calibration 2026-08-02).

Ownership

Swar PatelPersonal account
200 followers8 public repossince Sep 2015https://www.linkedin.com/in/swar/

This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPInba_api1.11.4-43173 days agoapibasketballdatanbasportsstats

Metrics by category

Vitality

Is the project alive — is code being written and are releases shipping?

54Moderate · 21% of overall
How it's scored
9.9/36Push recencylast push 128 days ago
9.7/36Commit cadence14/52 weeks with commits
16.6/18Commit volume70 commits in the last year
0/10OpenSSF Scorecard: Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year70
human_commit_share0.98
days_since_last_push128
active_weeks_last_year14
How it's scored
27/27Ships releases38 releases published
27/36Release recencylatest release 173 days ago
27/27Release cadencea release every ~38.6 days
0/10OpenSSF Scorecard: Signed-ReleasesProject has not signed or included provenance with any releases.
Inputs used
releases_count38
latest_release_tagv1.11.4
releases_from_tagsno
days_since_latest_release173
mean_days_between_releases38.6

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

82Excellent · 17% of overall
How it's scored
58/60Stars3,740 stars
23.8/25Forks723 forks
11.3/15Watchers110 watchers
Inputs used
forks723
stars3,740
watchers110
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (MIT)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges5
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesshields.io
has_pull_request_templateno

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

68Good · 23% of overall
How it's scored
25.2/54Bus factor2 contributor(s) cover half of all commits
13.3/22.5Commit distributiontop contributor authored 41% of commits
13.5/13.5Contributor breadth36 contributors
10/10OpenSSF Scorecard: Contributorsproject has 4 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled36
top_contributor_share0.411
How it's scored
33.6/42Issue resolution80% of issues closed
23.9/30PR acceptance192/241 decided PRs merged
0/13Newcomer PR acceptance0/1 first-time contributors' PRs merged in 30d
3/15OpenSSF Scorecard: Code-ReviewFound 2/9 approved changesets -- score normalized to 2
Inputs used
merged_prs192
open_issues84
closed_issues335
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d1
issue_closed_ratio0.8
closed_unmerged_prs49
first_time_authors_30d1
first_time_prs_merged_30d0
first_time_prs_decided_30d1
How it's scored
10/30Ownership backingpersonal (user) account
0/20Verified domainnot applicable to user accounts
16.6/25Owner reach200 followers of swar
18.9/25Track record8 public repos, account ~10 yr old
Inputs used
followers200
owner_typeUser
is_verified
owner_loginswar
public_repos8
account_age_days3,972
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 173 days ago
20/20Version history43 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesnba_api
ecosystemspypi
any_deprecatedno
min_days_since_publish173

Engineering Quality

Are baseline engineering and documentation practices in place?

76Good · 19% of overall
How it's scored
0/24CI workflows
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests8 out of 8 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_cino
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

85Excellent
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics14 topics
10/10Wiki
Inputs used
topicsnba, stats, nba-stats, nba-api, nba-stats-api, basketball-stats, sports-stats, api-client, endpoint-analysis, jupyter-notebooks, analysis, http-client, python, python3
has_wikiyes
homepage
docs_site
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?

46Weak · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionno data
2.5/2.5CI-Tests8 out of 8 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
1.5/7.5Code-ReviewFound 2/9 approved changesets -- score normalized to 2
2.5/2.5Contributorsproject has 4 contributing companies or organizations
0/10Dangerous-Workflowno data
7.5/7.5Dependency-Update-Toolupdate tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
0/7.5Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
0/5Packagingno data
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0/5SASTSAST tool is not run on all commits -- score normalized to 0
0/5Security-Policysecurity policy file not detected
0/7.5Signed-ReleasesProject has not signed or included provenance with any releases.
0/7.5Token-Permissionsno data
0/7.5Vulnerabilities31 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated14
scorecard_versionv5.5.0
checks_inconclusive4
scorecard_aggregate3.2
Excluded from scoring (no data or not applicable): Branch-Protection, Dangerous-Workflow, Packaging, Token-Permissions. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
25/25Indirect dependencies free of known advisoriesno indirect dependency carries a known advisory
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages9
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:nba_api@1.11.4 runtime dependency closure — what installing the published package pulls in — 9 packages. Reachability is not analyzed.

AI Readiness

How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight (4%): agent tooling is a real maintenance signal, but a repository with none can still reach 100/100.

59Moderate · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
28.3/40Legible commit history52 of 98 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.531
agent_instruction_files
agent_instruction_max_bytes
How it's scored
18/18One-command bootstrapMakefile
22/22Automated tests
11/11Lint / format config
0/11Static type checking
10/10Reproducible environmentdevcontainer, Dockerfile, lockfile
0/10Demonstrated agent practiceno agent-authored commits among the last 100
8/8Automated maintenance2 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilespoetry.lock
has_dockerfileyes
typed_languageno
bootstrap_filesMakefile
has_devcontaineryes
has_linter_configyes
typecheck_configs
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0.02
How it's scored
0/45Type-checkable codePython without a type-check config
54.6/55Manageable file sizes2/302 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes363,712
source_files_sampled302
oversized_source_files2
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)not applicable to this kind of software
0/20MCP servernot applicable to this kind of software
40/40Runnable examplesexamples, notebooks
Inputs used
example_dirsexamples, notebooks
has_mcp_signalno
api_schema_files
interfaces_expected_of
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto), MCP server. Remaining weights renormalized.

Key facts

3,740GitHub stars
36contributors
70commits, last 12 months
128days since last push
38releases
2bus factor
84open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

More detail

Star and fork history 0 ★ / 723 ⇿
0Stars
723Forks
38Releases

When each star and fork was added, collected from GitHub and bucketed by day. Cumulative growth sits directly above the daily additions it is made of, so the two read against each other: steady organic accretion looks nothing like an abrupt, short-lived burst. Where that difference is measurable, it is reported as growth authenticity.

0125250375500625750714102018-092022-092026-08
Major 0Minor 10Patch 28

Each point covers 8 days.

OpenSSF Scorecard 3.2 / 10
3.2aggregate

Independent, tool-agnostic security assessment from the open-source OpenSSF Scorecard. Each check rewards a security practice, not a specific vendor's tool. Checks Scorecard could not determine are marked n/a and excluded from the security score (never counted as zero).Scorecard v5.5.0 · 2026-08-13 00:04 UTC

10Binary-Artifactsno binaries found in the repo
n/aBranch-Protectioninternal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md
10CI-Tests8 out of 8 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
2Code-ReviewFound 2/9 approved changesets -- score normalized to 2
10Contributorsproject has 4 contributing companies or organizations
n/aDangerous-Workflowno workflows found
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
0Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
n/aPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
n/aToken-PermissionsNo tokens found
0Vulnerabilities31 existing vulnerabilities detected
Direct dependencies 5
RegistryPackageVersion constraintManifest
PyPInumpy>=1.26.0pyproject.toml
PyPInumpy>=2.1.0pyproject.toml
PyPIpandas>=2.1.0pyproject.toml
PyPIpandas>=2.2.0pyproject.toml
PyPIrequests(>=2.32.3,<3.0.0)pyproject.toml
All dependencies 62

Full resolved dependency set from the GitHub dependency graph: 5 direct and 57 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPInumpy1.26.4direct
PyPInumpy2.4.2direct
PyPIpandas2.1.4direct
PyPIpandas3.0.1direct
PyPIrequests2.32.5direct
PyPIannotated-types0.7.0indirect
PyPIcertifi2026.1.4indirect
PyPIcfgv3.5.0indirect
PyPIcharset-normalizer3.4.4indirect
PyPIclick8.3.1indirect
PyPIclick-option-group0.5.9indirect
PyPIcolorama0.4.6indirect
PyPIcoverage7.13.4indirect
PyPIdeprecated1.3.1indirect
PyPIdistlib0.4.0indirect
PyPIdotty-dict1.3.0indirect
PyPIdotty-dict1.3.1indirect
PyPIexceptiongroup1.3.1indirect
PyPIfilelock3.24.3indirect
PyPIgitdb4.0.12indirect
PyPIgitpython3.1.46indirect
PyPIidentify2.6.16indirect
PyPIidna3.11indirect
PyPIimportlib-resources6.5.2indirect
PyPIiniconfig2.3.0indirect
PyPIjinja23.1.6indirect
PyPImarkdown-it-py4.0.0indirect
PyPImarkupsafe3.0.3indirect
PyPImdurl0.1.2indirect
PyPInodeenv1.10.0indirect
PyPIpackaging26.0indirect
PyPIplatformdirs4.9.2indirect
PyPIpluggy1.6.0indirect
PyPIpre-commit4.5.1indirect
PyPIpydantic2.12.5indirect
PyPIpydantic-core2.41.5indirect
PyPIpygments2.19.2indirect
PyPIpytest8.4.2indirect
PyPIpytest-cov4.1.0indirect
PyPIpytest-recording0.13.4indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpython-gitlab5.6.0indirect
PyPIpython-semantic-release9.21.1indirect
PyPIpytz2025.2indirect
PyPIpyyaml6.0.3indirect
PyPIrequests-toolbelt1.0.0indirect
PyPIrich14.3.3indirect
PyPIruff0.15.2indirect
PyPIsetuptools82.0.0indirect
PyPIsetuptools-scm9.2.2indirect
PyPIshellingham1.5.4indirect
PyPIsix1.17.0indirect
PyPIsmmap5.0.2indirect
PyPItomli2.4.0indirect
PyPItomlkit0.14.0indirect
PyPItyping-extensions4.15.0indirect
PyPItyping-inspection0.4.2indirect
PyPItzdata2025.3indirect
PyPIurllib32.6.3indirect
PyPIvcrpy8.1.1indirect
PyPIvirtualenv20.38.0indirect
PyPIwrapt2.1.1indirect
Dependency advisories 0

Installing pypi:nba_api@1.11.4 pulls in 9 packages, direct and transitive: 0 carry known advisories, of which 0 are direct dependencies.

No known advisories affect the assessed dependencies.

An advisory means the version recorded in the dependency graph falls inside an advisory’s affected range. Reachability is not analysed, and the graph includes development and test pins — a finding may concern tooling rather than shipped software.

Raw JSON report machine-readable

Feedback

Spotted something off in this report, or have thoughts to share? Wrong measurements, missed tooling, ideas, questions — anything is welcome. Every message is read and gets a response.

The message is kept through sign-in.

Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.

Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v2.10.0, schema v0.31.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statisticsPyPI.