ncaapyscraper

Rosters, coaches and schedules for every sport at almost 1,000 NCAA schools, from Division I down to Division III. Use it from the command line or from Python, and you get clean JSON back.

pip install ncaapyscraper

import ncaapyscraper as nps

nps.get_roster("duke", "football")
nps.get_schedule("alabama", "mens-basketball")

Don't want to run anything? A fresh copy of all of it is published every week, see Download the data.

Download the data

Every Monday a GitHub Action scrapes every supported school and publishes the result under Releases.

• ncaapyscraper-data.zip has one JSON file per school plus index.json
• index.json on its own lists every school with its conference, division and file name

Bios are left out of the weekly data to keep it small. Run it yourself if you need them.

Command line

One school, everything

ncaapyscraper duke

A few schools, by key or by website

ncaapyscraper alabama navy goduke.com

Football only

ncaapyscraper ohio_state --sport football

Basketball schedules for the whole SEC (basketball matches men's and women's)

ncaapyscraper --conference sec --sport basketball --schedules

Every FCS school, athletes only

ncaapyscraper --division fcs --players

Women's soccer rosters across Division III, no bios

ncaapyscraper --division 3 --sport womens-soccer --players --no-bios

Find a school's key, or see what's in a conference

ncaapyscraper --list -c "big sky"
ncaapyscraper --conferences

Each school is saved to output/<key>.json. Pick another folder with -o.

--players, --coaches and --schedules can be combined. Without any of them you get all three.

Python

The get_ functions return plain lists of dicts, one row per player, coach or game, with school, sport and season on every row.

import ncaapyscraper as nps

roster = nps.get_roster("duke", "football")
coaches = nps.get_coaches("navy", "football")
games = nps.get_schedule("stanford", "basketball")      # men's and women's

school = nps.get_school("villanova", sports=["football"], data=["players", "schedules"])

nps.list_schools("sec")                                 # or division="fbs", 1, 2, 3

Straight into pandas

import pandas as pd

df = pd.DataFrame(nps.get_roster("texas", "baseball"))

They work in Jupyter too.

For lots of schools at once there's an async version. It keeps every school's site to a few requests at a time, and yields each school as it finishes.

import asyncio
import ncaapyscraper as nps

async def main():
    keys = [school["key"] for school in nps.list_schools("ivy")]

    async for key, result in nps.fetch_schools(keys, sports="football", parallel=8):
        if isinstance(result, Exception):
            print(key, "failed", result)
            continue

        print(key, sum(len(sport["players"]) for sport in result["sports"]))

asyncio.run(main())

fetch_school, fetch_roster, fetch_coaches and fetch_schedule are the async versions of the get_ functions.

A school that isn't on the list yet? Pass a dict instead of a key.

nps.get_school({"name": "Boise State University", "site": "broncosports.com", "platform": "sidearm"})

JSON response

One file (or dict) per school, grouped by sport. Missing values are null.

{
  "key": "duke",
  "school": "Duke University",
  "conference": "Atlantic Coast Conference",
  "division": 1,
  "subdivision": "FBS",
  "state": "NC",
  "site": "https://goduke.com",
  "platform": "sidearm",
  "scraped_at": "2026-11-05T07:29:39Z",
  "sports": [
    {
      "sport": "Football",
      "gender": "men",
      "season": "2026",
      "players": [
        {
          "name": "Jordan Smith",
          "first_name": "Jordan",
          "last_name": "Smith",
          "shirt_no": "24",
          "position": "RB",
          "height": "5-10",
          "weight": 205,
          "player_class": "Senior",
          "hometown": "Charlotte, N.C.",
          "highschool": "Myers Park",
          "previous_school": "East Carolina",
          "major": "Economics",
          "gender": "men",
          "image_url": "https://goduke.com/images/2026/7/27/smith_jordan.jpg",
          "profile_url": "https://goduke.com/sports/football/roster/jordan-smith/24470",
          "bio": null
        }
      ],
      "coaches": [
        {
          "name": "Chris Allen",
          "first_name": "Chris",
          "last_name": "Allen",
          "title": "Head Coach",
          "image_url": "https://goduke.com/images/2024/3/6/allen_chris.jpg",
          "profile_url": "https://goduke.com/sports/football/roster/coaches/chris-allen/5388",
          "bio": "Chris Allen was named head coach in December 2023..."
        }
      ],
      "schedule": [
        {
          "date": "2026-09-05",
          "time": "5:00 PM",
          "datetime_utc": "2026-09-05T21:00:00Z",
          "opponent": "Tulane",
          "home_away": "home",
          "location": "Durham, N.C.",
          "venue": "Brooks Field at Wallace Wade Stadium",
          "is_conference": false,
          "result": "W",
          "score": "17-3",
          "tournament": null,
          "tv": "ACC Network",
          "image_url": "https://goduke.com/images/logos/Tulane-Wave.png"
        }
      ]
    }
  ]
}

• coaches includes support staff, title tells you who's who
• date and time are the school's local time. datetime_utc is filled for schools on the SIDEARM API and WMT
• score is always the school's score first, result is W, L or T
• gender on a player only matters for co-ed teams like track and swimming
• subdivision is FBS, FCS or null
• How much detail you get depends on what the school puts on its site. Bios, majors and weights are often missing for smaller schools
• With --players, --coaches or --schedules you only get those keys in each sport

Supported schools

Every NCAA school whose athletics site runs on SIDEARM Sports or WMT Digital, which is most of them. The full list with keys is in docs/schools.md, or run ncaapyscraper --list.

Schools on other platforms (PrestoSports and custom builds) aren't covered yet.

Docs

The docs folder is an unofficial reference for the APIs and pages these sites use, handy even if you write your own scraper.

• SIDEARM API
• WMT API
• Older SIDEARM sites

Adding a new school

NAIA, junior colleges and anything else on the same platforms work too.

1. Find the school's athletics website
2. Open these in the browser, the first one that shows JSON tells you the platform
   • https://<site>/api/v2/Sports → sidearm
   • https://<site>/website-api/sports → wmt
   • https://<site>/services/adaptive_components.ashx?type=main-navigation&count=10&start=0&extra=%7B%7D → sidearm_legacy
3. Try it straight away by passing a dict to get_school (see Python)
4. To add it for everyone, add a row to ncaapyscraper/schools.csv and open a PR

key,name,conference,division,subdivision,state,site,platform
my_school,My School University,My Conference,3,,OH,myschoolathletics.com,sidearm_legacy

Development

1. Clone the repo and go into the folder
2. Run python3 -m venv env and source env/bin/activate
3. Run pip install -e ".[dev]"
4. Run pytest

Needs Python 3.10+.

License

MIT