Reliable observations
Preserve original data and receipt times. Track provenance, identity, and freshness so research can be reproduced.
Sports data. Market intelligence. Research.
Quantitative intelligence for sports event markets.
Dime Line is building an AI-powered, multi-sport research platform that connects sports data, market pricing, and probabilistic models.
Early-stage · Research and platform development
Our premise
A forecast is only as useful as
the evidence behind it.
Sports outcomes are uncertain. Market prices carry information. Our work starts with reliable data and asks whether a model adds value through chronological testing, calibration, and forward observation.
01 / Research approach
Build the evidence.
Then test the hypothesis.
One shared research process, from the original observation to a decision that can be explained.
Probabilities in context
Use sportsbook and prediction-market pricing as information-rich baselines. Evaluate uncertainty and calibration alongside accuracy.
Forward evidence
Test chronologically and out of sample. Account for fees and execution assumptions before qualifying a strategy.
How we think about AI and decision-making
AI agents are part of the planned research and operations framework: structuring information, monitoring data quality, and assisting evaluation. Models and agents do not independently authorize capital.
Human approval and qualification evidence are required before live-money automation. Research results are uncertain and do not guarantee future returns.
02 / Platform direction
A shared foundation.
A multi-sport horizon.
We are building reusable infrastructure for data capture, research, model evaluation, and risk-aware decision-making.
The foundation taking shape
From source data
to reproducible research.
Data captureProvenance & replayModel evaluationExecution simulation
Data capture, provenance, and offline replay are the current building blocks. Model governance, research agents, execution simulation, and portfolio risk management are planned layers.
NFLCurrent research focus
Data infrastructure and research migration.
NBANext sport planned
Ingestion and moneyline research.
NHLPlanned
After the shared NFL and NBA foundation.
MLBPlanned
Longer-term seasonal research coverage.
The platform is in development. Multi-sport production coverage and live trading are not currently offered.
03 / Company
Engineering a disciplined
research process.
Dime Line is an early-stage quantitative sports technology company. Our goal is to make sports event-market research more reproducible, transparent, and aware of real-world execution constraints.
Omar Becerra
Founder & Quantitative Systems Engineer
Omar brings a software and data engineering background across backend systems, cloud infrastructure, and applied machine learning.
04 / Partnerships
Better research starts
with strong foundations.
We are seeking data, infrastructure, and academic collaborators while we build and validate the platform.
Data & market access
Research access, historical datasets, API credits, extended trials, and early-stage pricing.
Cloud & infrastructure
Startup credits, technical mentorship, and support for reliable data and research infrastructure.
Academic collaboration
Scoped projects in sports data reliability, entity matching, freshness monitoring, and reproducible evaluation.
Discuss a research or infrastructure collaboration.
hello@dimelinellc.com