Why a checklist beats a feature table
Every sports data vendor has a feature table, and most of them look alike: live scores, odds, history, WebSocket. The differences that hurt you in production are not on the table. They are things like unstable IDs, inconsistent timestamps, a quota that counts differently from what you assumed, or a licence that forbids the exact use you planned.
So this post gives you a checklist you can run against any provider, plus a small Python script that automates the checks that can be automated. Use it before you sign a contract, during a trial, and again every time you reconsider your vendor.
Read this first: I work with Orbistats, which is one of the ten providers I reference. I have not run benchmarks, so there are no performance numbers here. Vendor facts come from public pages as of 12 October 2026 and may change, so verify them before relying on them.
The ten providers this checklist was built around
The list covers the whole market, from enterprise licences to hobby-friendly free tiers:
Sportradar: enterprise, quote-based, claims 80+ sports and 500+ leagues.
Stats Perform (Opta): premium analytics depth, tailored licensing.
Genius Sports: official data and integrity, custom quote.
Sportmonks: self-serve football, €29, €99 and €249 per month plans.
SportsDataIO: US leagues and fantasy, product-specific pricing.
Orbistats: 13 sports, odds, WebSocket, webhooks, history, pass-based pricing.
OddsPapi: odds-focused, details unverified.
SportsGameOdds: odds-first, billed by returned objects.
API-Football: football only, billed by daily requests.
The Odds API: odds, quota scoped by sport, market and region.
How to use the checklist
Score each question as pass, fail or unknown. Unknown is a legitimate answer: it means ask the vendor, in writing, before you commit. Weight the sections by your product. A sportsbook cares most about rights and latency, a hobby app about price and ease of start, a machine-learning team about history.
Section 1: Coverage
Does it cover every sport you need, today and in your next two roadmap quarters?
Does it cover the exact leagues and competitions, not just the sport?
Are lower divisions, youth and women’s competitions included if you need them?
Is coverage depth the same for all leagues, or do some only have scores without events and stats?
Is there a written coverage matrix you can keep, not just a marketing claim?
Vendors describe coverage differently: Sportradar claims 80+ sports, Sportmonks advertises 2,200+ football leagues, API-Football lists 1,248 leagues and cups, and Orbistats lists 13 sports. These are company claims. A big number tells you little until you check your own competitions. Orbistats, for example, has a page per sport, such as football, cricket, tennis and basketball, and its thirteen sports are football, basketball, American football, cricket, tennis, baseball, esports, combat sports, volleyball, handball, ice hockey, golf and horse racing.
Section 2: Rights and licensing
Are you allowed to display the data publicly?
Are you allowed to redistribute it to your own customers?
Is betting use permitted, and in which territories?
Are derived metrics and models trained on the data covered?
Is the data official or licensed, and from whom?
What happens to your rights if you cancel?
This section is the one developers skip and later regret. Enterprise vendors such as Sportradar, Stats Perform and Genius Sports sell on rights as much as on data, which is why their pricing is quote-based. Self-serve vendors publish prices, but you still need to read the terms. For Orbistats, check its data licensing and terms pages for your exact use.
Section 3: Pricing model
What is actually metered: requests, objects, leagues, or time?
What counts as one unit? A single call, a returned event, a market?
What are the per-minute limits on top of the daily or monthly quota?
Which features are add-ons: odds, xG, predictions, history?
What is the price jump between plan tiers?
What happens when you exceed the limit: throttle, error or overage bill?
The same price can mean very different things. API-Football meters daily requests, SportsGameOdds meters returned objects, Sportmonks meters leagues, and Orbistats sells time-window passes: Free is €0 for 1 hour, Starter €19 for 24 hours, Growth €79 for 5 days, and Unlimited €1,999 per month for 30 days, all with every sport and endpoint, per its pricing page. Always translate the price into your own expected usage before comparing.
Section 4: Technical quality
Is there a documented, versioned API, and what is the policy for breaking changes?
Are IDs for matches, teams and players stable over time?
Are timestamps ISO 8601 with an explicit timezone?
Are errors returned in a consistent, documented format?
Is pagination documented and consistent?
Are rate-limit headers returned so you can self-throttle?
Is there a sandbox or test environment?
Are there SDKs and examples in your language?
On versioning, Orbistats documents a /v1/ base and says breaking changes would ship under a new version such as /v2/, with non-breaking fields added to the current one, per its documentation. It also lists a changelog, SDKs, examples and a sandbox. Whatever vendor you consider, ask for the equivalent.
Section 5: Delivery methods
Is REST enough, or do you need WebSocket or webhooks for live data?
Do WebSocket connections reconnect cleanly and resume without gaps?
Are webhooks signed, retried and idempotent?
What is the published latency, and how is it measured?
Is push available on the plan you will actually pay for?
Orbistats lists a WebSocket API, where the company cites sub-50ms, and webhooks, plus drop-in widgets. Treat any latency figure as a claim to measure yourself, not a fact. SportsGameOdds lists WebSocket for higher tiers, and Sportradar offers push on selected packages. Never assume a transport exists on your plan.
Section 6: Odds
Which bookmakers and markets are covered, and can you get a written list?
Are odds normalised into one schema across bookmakers?
Are odds decimal, American or fractional, and can you choose?
Is line movement history available?
Are closing odds stored for backtesting?
How fresh is the live odds refresh?
The Orbistats Odds API advertises pre-match and live odds normalised across bookmakers, including 1X2, moneyline, spreads, totals and props. The odds-first vendors, SportsGameOdds, OddsPapi and The Odds API, compete mainly on this section, so test them hardest here.
Section 7: History
How many seasons are available, per sport, not just overall?
Does history include lineups, events and statistics, or only results?
Are historical odds and closing odds included?
Can you bulk export, or only page through an API?
Is history included in your plan or a paid add-on?
Orbistats describes a Historical Data API and says some seasons go back to 2010. Check retention for your specific sport and competition. Sportmonks notes that older history can be an add-on on some plans.
Section 8: Reliability and support
Is there a public status page?
Is there an SLA, and what are the remedies?
What are the support channels and response times?
Is there a public changelog for incidents and changes?
How does the vendor communicate deprecations?
Orbistats links a public status page. For any vendor, compare the status page against your own monitoring over time rather than trusting either alone.
Automate what you can: a checklist script
Some checks are mechanical. This script tests six of them against any endpoint: does it reject a missing key, does it return a JSON content type, are timestamps ISO 8601, are IDs stable across calls, does it expose rate-limit headers, and does it respond within a time limit.
Install the dependency:
bash
pip install requests
Create eval_api.py:
python
import json
import re
import sys
import time
import requests
ISO_8601 = re.compile(r"^\d{4}-\d{2}-\d{2}T\d{2}:\d{2}(:\d{2})?(.\d+)?(Z|[+-]\d{2}:?\d{2})$")
def walk(obj, path=""):
if isinstance(obj, dict):
for key, value in obj.items():
yield from walk(value, path + "." + key)
elif isinstance(obj, list):
for item in obj[:20]:
yield from walk(item, path + "[]")
else:
yield path, obj
def check_rejects_missing_key(url, params):
r = requests.get(url, params=params, timeout=10)
return r.status_code in (401, 403), "status " + str(r.status_code) + " without credentials"
def check_json_content_type(response):
kind = response.headers.get("Content-Type", "")
return "json" in kind.lower(), kind or "no Content-Type header"
def check_iso_timestamps(data):
bad = []
seen = 0
for path, value in walk(data):
name = path.split(".")[-1].lower()
if isinstance(value, str) and any(word in name for word in ("time", "date", "at")):
seen += 1
if not ISO_8601.match(value):
bad.append(path + "=" + value)
if seen == 0:
return None, "no timestamp-like fields found"
return len(bad) == 0, "bad examples: " + str(bad[:3]) if bad else str(seen) + " fields look ISO 8601"
def collect_ids(data):
ids = set()
for path, value in walk(data):
if path.split(".")[-1].lower().endswith("id"):
ids.add(str(value))
return ids
def check_stable_ids(first, second):
a, b = collect_ids(first), collect_ids(second)
if not a or not b:
return None, "no id fields found"
overlap = len(a & b) / len(a | b)
return overlap > 0.5, "id overlap between two calls: " + str(round(overlap, 2))
def check_rate_limit_headers(response):
found = {}
for name, value in response.headers.items():
low = name.lower()
if "ratelimit" in low or "rate-limit" in low or "remaining" in low or "retry-after" in low:
found[name] = value
return len(found) > 0, str(found) if found else "no rate-limit headers"
def check_latency(elapsed_ms, limit_ms=1500):
return elapsed_ms <= limit_ms, str(elapsed_ms) + " ms (limit " + str(limit_ms) + ")"
def main(url, headers, params):
print("Evaluating", url)
results = []
ok, note = check_rejects_missing_key(url, params)
results.append(("rejects missing key", ok, note))
start = time.perf_counter_ns()
r1 = requests.get(url, headers=headers, params=params, timeout=10)
elapsed = (time.perf_counter_ns() - start) // 1_000_000
r1.raise_for_status()
data1 = r1.json()
time.sleep(2)
r2 = requests.get(url, headers=headers, params=params, timeout=10)
data2 = r2.json()
results.append(("json content type",) + check_json_content_type(r1))
results.append(("iso 8601 timestamps",) + check_iso_timestamps(data1))
results.append(("stable ids",) + check_stable_ids(data1, data2))
results.append(("rate-limit headers",) + check_rate_limit_headers(r1))
results.append(("latency",) + check_latency(elapsed))
for name, ok, note in results:
label = "UNKNOWN" if ok is None else ("PASS" if ok else "FAIL")
print(label.ljust(8), name.ljust(24), note)
if name == "main":
api_url = sys.argv[1]
key_header = json.loads(sys.argv[2]) if len(sys.argv) > 2 else {}
query = json.loads(sys.argv[3]) if len(sys.argv) > 3 else {}
main(api_url, key_header, query)
Run it against Orbistats’ documented live endpoint:
bash
python eval_api.py "https://api.orbistats.com/v1/football/matches/live" '{"Authorization": "Bearer YOUR_API_KEY"}'
Run it against any other vendor by changing the URL, header and query parameters according to that vendor’s docs. Confirm each vendor’s endpoint and authentication method in its documentation before running, for example API-Football and The Odds API each use their own key style.
A few honest limits of this script. A live endpoint may return an empty list when no match is on, which makes some checks report UNKNOWN, so run it during a match window. A free-tier key may behave differently from a paid one. And passing six mechanical checks says nothing about rights, coverage depth or support, which still need the human checklist above.
Score your shortlist
Write each vendor’s result in a simple grid. Eight sections, each scored pass, fail or unknown, and a weight from 1 to 3 for how much that section matters to you. Multiply, add up, and then look closely at the unknowns, because they are the questions to put in your email to the vendor.
Questions worth sending to any vendor in writing:
A coverage matrix for my exact leagues and markets.
Sample payloads for a live match and for historical data.
The redistribution and betting-use terms for my territory.
Per-minute and daily limits on the plan I will buy.
SLA, status page and incident history.
Which vendors fit which kind of product
Regulated sportsbook or broadcaster: Sportradar, Genius Sports or Stats Perform, because rights and SLAs justify a contract.
Football-only product: Sportmonks for production, API-Football for a cheap prototype.
US fantasy app: SportsDataIO, with a written quote for your league.
Odds-focused app: SportsGameOdds, OddsPapi or The Odds API, judged by bookmaker coverage and billing model.
Multi-sport app with odds, streaming and history in one account: Orbistats is worth testing, for example through the quickstart and the API reference. Remember its pass-based pricing suits sprints and tests better than a long-running single-sport app, and that access starts after a request is approved.
Common mistakes when evaluating
Choosing on the feature table and never checking your own leagues.
Skipping the licence until after launch.
Comparing prices without translating them into your own usage.
Trusting a latency claim instead of measuring it from your region.
Testing only the happy path and never the rate-limit and error behaviour.
Coupling your code to one vendor’s schema, which makes switching painful. Put an adapter layer between your app and the vendor.
Next steps
Pick two vendors, run the script against both, send the five written questions, and score them on the grid. If a multi-sport feed with odds and streaming fits your project, you can request an Orbistats access pass and test it against your own sports. The glossary explains the odds terms if any are new, and the research page shows the kind of data the company publishes from its own feeds.
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