# PropsData.io | Sportsbetting Statistics (@propsdataio) on x

- id: koinon:creator:x_propsdataio
- url: https://koinonlink.com/kol/x/propsdataio
- schema_version: 1.4

## Identity
- platform: x
- handle: propsdataio
- platform_url: https://twitter.com/propsdataio
- website: http://propsdata.io
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 2830
- following: 330
- posts_total: 2185
- posts_observed: 1
- posts_per_day: 3.121
- account_age_days: 700
- verified: true
- size_tier: nano

## Engagement
- status: peak_post_only
- peak_post_engagement_rate: 0.00318
- best_post_interactions: 9
- measurement_source: x_post_interactions
- measurement_formula: interactions on one post — likes, or likes + reposts + replies depending on the discovery path (the two are not distinguishable in the stored data)
- comparable_pool: peak_interactions
- status_note: We have only the single best observed post, so no mean exists. peak_post_engagement_rate is an UPPER BOUND, systematically higher than an average — never compare it against an average rate.
- unit_note: engagement_rate and peak_post_engagement_rate are ratios (0-1); avg_interactions_per_post and best_post_interactions are absolute counts. Read status before reading any number: a null rate has several different causes and status says which one applies here.

## Content
- category: finance
- subcategory: investing
- category_confidence: 0.9
- category_source: derived_from_recent_content
- topics: Sports betting statistics, Expected goals analysis, Player performance probabilities, Football match betting markets, Odds and market evaluation
- bio: ⚽️ Sports betting Software 👨‍💻 https://t.co/DAv6IGU2Y2 📊 Visuals instead of boring numbers - statistics built for sports bettors 🔞 https://t.co/huD3pjDDTC

## Audience (inferred)
- status: present
- description: Sports bettors who use data and visuals for football/soccer betting decisions
- roles: consumer
- seniority: consumer
- pain_points: Raw stats being hard to interpret quickly, Finding value in betting markets like outrights, Accurately assessing player goal probabilities, Turning numbers into actionable betting insights
- posts_analysed: 3
- confidence: 0.4

## Commercial (inferred)
- audience_buyer_fit: 0.9
- promotion_intent: 0.85
- open_to_collaboration: false
- contact: Koinon does not publish creator contact details.

## Quality signals
- authenticity_score: 65
- authenticity_basis: engagement_observed
- credibility_score: 65
- flagged_for_review: false
- koinon_bd_grade: A — measures Koinon partner-outreach fit, not creator quality
- interpretation: Signals for triage, not verdicts. A flag means the profile is worth a manual check.

## Evidence
- [x_propsdataio#b62e6f7d] ✅✅✅ (https://twitter.com/propsdataio/status/2071171842774028751)
- [x_propsdataio#a0239c6b] https://t.co/xOfwJ9yzcF
- [x_propsdataio#219beba8] This is how smart the outrights market is… Even had Mbappe @ 2.75 when the whistle blew in England - Argentina. https://t.co/jE21xPKGJg
- [x_propsdataio#b7f22397] Mbappe: 1 Game, 45% chance to score 1+ Goals. 🇫🇷 0.598 Expected Goals Messi: 2 Games 40% chance to score in each game. 🇦🇷 1.022 Expected Goals Kane: 2 Games 40% Chance to score in each. 🏴󠁧󠁢󠁥󠁮󠁧󠁿 1.022 Expected Goals Bellingham: 2 Games 30% Chance to score in each. 🏴󠁧�

## Provenance
Every inferred field below carries how it was produced. Facts stay facts; inferences stay inferences.

- audience.description: source_type=ai_inferred, confidence=0.4, freshness_days=76, method=llm_persona_from_recent_content
- audience.roles: source_type=ai_inferred, confidence=0.4, freshness_days=76, method=llm_persona_from_recent_content
- audience.seniority: source_type=ai_inferred, confidence=0.4, freshness_days=76, method=llm_persona_from_recent_content
- commercial.audience_buyer_fit: source_type=ai_inferred, confidence=0.6, freshness_days=81, method=llm_scorer — Relative signal within Koinon indexing, not a market-wide score.
- commercial.promotion_intent: source_type=ai_inferred, confidence=0.6, freshness_days=81, method=llm_scorer
- quality.anomaly_flags: source_type=heuristic, confidence=0.5, freshness_days=115, method=profile_snapshot_and_engagement_ratio_heuristic — Means "worth a manual check", NOT confirmed fraud. Flags can be wrong and are not a verdict about the person.
- quality.authenticity_score: source_type=heuristic, confidence=0.5, freshness_days=81, method=Profile-shape heuristic from a single snapshot (follower count, following ratio, account age, posting volume, verification), reduced for engagement red flags where post engagement was collected. Where only a follower count is available the score saturates at 58. — The input set differs by platform; do not compare this score across platforms.
- quality.koinon_bd_grade: source_type=ai_inferred, confidence=0.5, freshness_days=115, method=llm_partner_fit_classifier + fit_score >= 0.6 AND authenticity >= 60 => A; fit_score >= 0.4 AND authenticity >= 45 => B; else C. authenticity < 30 or a promotional-pattern flag => quarantine. — Koinon partner-outreach fit, not creator quality.
- reach.followers: source_type=observed, confidence=0.95, freshness_days=115, method=platform_profile

## Freshness
- profile_checked_days_ago: 115
- content_analysed_days_ago: 81
- audience_updated_days_ago: 76

## AI retrieval
- indexing_requests: 12
- user_triggered_requests: 0
- note: Being indexed in bulk is not the same as being retrieved to answer a question.

## This profile
- Claim or correct: https://koinonlink.com/claim?k=x_propsdataio
- Request removal: https://koinonlink.com/claim?k=x_propsdataio
- Terms: https://koinonlink.com/for-ai