Football Data Feed Quality Verification

3.20

Derivation Chain

Step 1 Demand for real-time overseas football data

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Step 2 Increase in sports data API providers

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Step 3 Data feed accuracy and latency quality monitoring service

Problem

Domestic startups operating sports betting, fantasy, and statistics services that use overseas data feeds such as Opta and StatsBomb lack the capability to monitor latency and error rates of real-time data on their own, leading to service disruptions 1-2 times per month due to incorrect data, with an average of 3 hours spent on root cause analysis.

Solution

It subscribes to multiple data feeds simultaneously for cross-validation and visualizes latency, missing data, and inconsistencies on a real-time dashboard. When anomalies are detected, it sends Slack/Kakao notifications and automatically generates monthly SLA compliance reports per feed.

Target: Sports data startups with 3-15 employees, sports media development teams

Revenue Model: SaaS monthly subscription at 59,000 KRW (approx. $44.25) per month (up to 3 feeds), additional feeds at 15,000 KRW (approx. $11.25) per month each. API call-based pay-as-you-go option at 50 KRW (approx. $0.04) per transaction.

Ecosystem Role: Supplier

MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty

3.0/5

U Urgency

4.0/5

M Market

3.0/5

R Realizability

3.0/5

V Validation

3.0/5

NUMR-V Scoring System

N Novelty	1-5	How uncommon the service is in market context.
U Urgency	1-5	How urgently users need this problem solved now.
M Market	1-5	Market size and growth potential from proxy indicators.
R Realizability	1-5	Buildability for a small team with realistic constraints.
V Validation	1-5	Validation signal quality from competition and demand data.

N=.15 U=.20 M=.15 R=.30 V=.20

Feasibility (72%)

Tech Complexity

34.7/40

Data Availability

17.5/25

MVP Timeline

20.0/20

API Bonus

0.0/15

Feasibility Breakdown

Tech Complexity	/ 40	Difficulty of core implementation stack.
Data Availability	/ 25	Practical availability and cost of required data.
MVP Timeline	/ 20	Expected time to ship a usable MVP.
API Bonus	/ 15	Bonus for viable public API leverage.

Market Validation (56/100)

Competition

8.0/20

Market Demand

6.2/20

Timing

14.0/20

Revenue Signals

10.5/15

Pick-Axe Fit

10.5/15

Solo Buildability

7.0/10

Validation Breakdown

Competition	/ 20	Signal quality from competitor landscape.
Market Demand	/ 20	Demand proxies from search and mention patterns.
Timing	/ 20	Fit with current shifts in tech, behavior, and regulation.
Revenue Signals	/ 15	Reference evidence for monetization viability.
Pick-Axe Fit	/ 15	How well the concept serves participants in a trend.
Solo Buildability	/ 10	Practicality for lean-team implementation.

Technical Requirements

Backend [medium] Infrastructure [low] Frontend [low]

Dashboard