SPORTSDATA.IO
Discovery Lab
Strategic Repositioning
Internal Strategy Review • March 2026
Confidential
Why We Built Discovery Lab
- Consistent inbound from students, hobbyists, and weekend builders with small budgets
- We didn't want to turn them away — they're future commercial customers
- Designed as self-serve and lightweight: low support cost, zero sales touch
- Always a complement to the commercial API, never a replacement
The original thesis was sound: give small users a sandbox, graduate them to commercial when they're ready.
What's Changed Since Launch
Market shifts
- AI coding tools explosion — anyone can build a betting dashboard in a weekend
- Demand for live/near-live data at this tier has surged
- The addressable market is much bigger than "students"
Our results
- Strong SEO traffic and inbound interest
- But conversion hasn't followed
- Visitors browse, hit the pricing page, and leave
- The funnel is attracting the right people — but the product isn't closing them
The market moved. Our packaging didn't.
Current Product Snapshot
|
Fantasy |
Odds |
Fantasy + Odds |
| Annual Price |
$599/yr |
$599/yr |
$899/yr |
| Effective Monthly |
~$50/mo |
~$50/mo |
~$75/mo |
| API Calls/Day |
100 – 1,000 |
100 – 1,000 |
100 – 1,000 |
| Data Freshness |
Next-day delayed |
Next-day delayed |
Next-day delayed |
| Data Types |
Fantasy only |
Odds only |
Both |
Tiers differentiate by data type (Fantasy vs Odds). Freshness and volume are the same everywhere.
Competitive Landscape: Low-Cost APIs
Where Discovery Lab sits relative to metered/self-serve competitors today — and where the proposed tiers would land.
| Provider |
Entry Price |
Mid-Tier |
Free Tier |
Data Scope |
Freshness |
Metering |
| Discovery Lab (proposed) |
$29/mo |
$79/mo |
No |
All sports, scores + odds + fantasy |
Next-day → 15-min |
250–10K calls/day |
| The Odds API |
$30/mo |
$59–119/mo |
500 credits/mo |
Odds only, 70+ sports |
Live |
Credits/mo |
| TheRundown |
$50/mo |
$99–299/mo |
20K pts/day |
Odds + scores, US sports |
Real-time |
Requests/mo |
| SportMonks |
€39/mo |
€69–219/mo |
Yes (limited) |
Football/cricket focused |
Live |
By leagues selected |
| AllSportsAPI |
$74/mo |
$111–149/mo |
260 calls/hr |
Soccer-centric |
Live |
Calls/hr |
| Entity Sport |
$150/mo |
$250–500/mo |
Dev API |
Cricket-heavy, per sport |
Live |
1–4M calls/mo |
| Goalserve |
$125/mo |
$150–1,000/mo |
30-day trial |
20+ sports, per sport |
2–4s updates |
Unlimited (by sport) |
| Rolling Insights |
$100/mo |
$300–600/mo |
30-day trial |
US sports, per sport |
Post-game / Live |
Unlimited (by sport) |
Most competitors offer live data at the low tier. Our proposed $29 entry is price-competitive, but freshness is our key trade-off — and the upgrade lever.
The Positioning Gap
True Hobbyists
Want: <$20/mo
←
Discovery Lab Today
$50–75/mo, next-day data
→
Serious Builders
Need: fresh data
- We say "students and hobbyists" but price at $50–75/mo
- Too expensive for true hobbyists, too crippled for builders
- No man's land: not cheap enough to be an impulse buy, not capable enough to be useful
- The person building an AI odds tool sees "next-day delivery" and leaves
Who's Actually Showing Up
The New Buyer: "AI-Assisted Builder"
- Prompted an AI to build a sports betting app — now needs real data
- Has a $30–150/mo budget and is willing to pay for quality
- Wants all data types — doesn't think in Fantasy vs Odds buckets
- Will pay more for less delay, not for more data categories
- Technical enough to use an API, but not enterprise — no procurement process
This buyer didn't exist at scale two years ago. They're here now, and our packaging doesn't serve them.
Recommendation: Repackage Around Freshness & Volume
Eliminate data-type tiers. Give everyone all data. Differentiate on what actually matters.
|
Starter |
Pro |
| Price |
$29/mo |
$79/mo |
$149/mo |
| Data Types |
All |
All |
All |
| Freshness |
Next-day |
1-hour delay |
15-min delay |
| API Calls/Day |
250 |
2,500 |
10,000 |
| History Depth |
Current season |
1 season (scores & basic stats) |
3 seasons (scores & basic stats) |
| Sports |
All available |
All available |
All available |
Builder tier highlighted as expected volume leader. Historical data is scores & basic stats only — no odds line movement. Full archive available on commercial API.
Why This Works
Lower entry point
$29/mo is an impulse buy. Higher conversion from free-tier browsers. Credit card, not a procurement decision.
All data unlocked
No confusion, faster time-to-value. Users don't have to guess which bundle they need. They just start building.
Natural expansion
Freshness is the upgrade lever. As apps get users, builders need fresher data. Upgrades happen organically.
Pipeline to commercial
Pro users who outgrow 15-min delay become commercial leads. Clear graduation path, warm handoff to sales.
Protecting the Commercial API
The cannibalization concern is real — and manageable.
Freshness Ceiling
15-min delay at best
vs real-time commercial
No SLA
Best-effort uptime
No contractual guarantees
Metered Calls
Hard daily cap
vs unlimited commercial
No Support
Self-serve docs only
vs dedicated support
Commercial clients need: real-time data, unlimited volume, SLA, and dedicated support. Discovery Lab can't deliver any of those. The products don't compete — Discovery Lab feeds the commercial pipeline.
Alternatives Considered
Option A: Keep current model, lower prices Partial fix
Reduces friction but doesn't fix the structural issue. Data-type tiering still confuses buyers. Freshness gap remains. Revenue drops without conversion lift.
Option B: Add a true free tier with aggressive limits High risk
Captures more top-of-funnel but creates support burden with zero revenue. Free users are loud and demanding. Hard to convert free → paid without a compelling step-up.
Option C: Repackage around freshness & volume Recommended
Aligns packaging with what buyers actually value. Low entry point drives conversion. Freshness ladder drives expansion. Clean graduation to commercial. Best balance of growth and margin.
Quick Wins to Execute Now
Regardless of the packaging decision, these moves can happen immediately:
- Make free last-season data the hero of the funnel
Let people taste the data before asking for money. Capture emails on download.
- Kill CSV as a headline feature
API-first buyers don't care about CSV. It dilutes the message and attracts the wrong audience.
- Update messaging: "students and hobbyists" → "builders and creators"
Reflect who's actually buying. Signal that this is a real product, not a toy.
- Add a "freshness" column to the pricing page
Even before repackaging, make the upgrade path obvious. Show what you get at the next level.
Next Steps
Validate
- Test proposed price points with existing Discovery Lab users
- Survey recent drop-offs on why they didn't convert
- Model revenue impact: conservative, base, optimistic scenarios
Build
- Engineering scoping for tiered freshness delivery
- Metering infrastructure for new call-volume tiers
- History-depth access controls
Launch
- Redesign pricing page around new tiers
- Update all messaging and positioning
- Migrate existing subscribers to closest new tier
- Announce to existing user base
Timeline target
Quick wins: execute within 2 weeks
Full repackaging: target next quarter launch
Measure: 90-day conversion comparison