About BetSmart
Revolutionizing sports betting through data-driven insights
Our Mission
At BetSmart, we are transforming sports betting into a
legitimate alternative asset class, one that rivals
traditional financial markets in both rigor and return
potential.
Like any market, sports betting is riddled with inefficiencies.
The difference? Sports offer a level of structural consistency
that financial markets can't match. In stocks, the rules can
change mid-game from tariffs to macro events. In sports, the
rules are fixed from whistle to whistle. That stability creates
an objective playing field: perfect for algorithmic exploitation.
We apply the principles of quantitative finance to sports betting,
leveraging advanced machine learning to model true outcome probabilities.
Just as a hedge fund might value a stock at $50 and act accordingly,
we value bets based on their true probability and strike when
the market misprices them. If the implied odds are too high,
we fade it. If they're too low, we fire. Our models process billions
of data points across player performance, team dynamics, market
movement, and more to build robust prediction systems. This is
not guesswork. This is disciplined, research-driven execution
at scale. We aren't gambling. We're deploying capital with calculated
edge.
Welcome to the future of investing. Welcome to BetSmart.
Our Algorithms
BetSmart's algorithms are built at the intersection of
data science, behavioral economics, and quantitative
finance. Designed by a team of PhDs, quantitative
researchers, and elite engineers, our models analyze
billions of data points across player performance, team
trends, line movement, public bias, weather, injuries,
and more.
Using a combination of machine learning techniques, including
gradient boosting, time series modeling, and ensemble methods,
we optimize for one goal: sustainable, risk-adjusted returns.
Every pick we release is backed by a statistical framework,
historical testing, and continuous model improvement. This
is betting redefined as research; prediction redefined as
precision.
Our Values
“Our greatest accomplishment is making our clients a lot
of money while keeping their risk mitigated.” - Howard
Marks
Here at BetSmart, our goal is to provide transparency in
an industry that has deceived consumers for decades. We are
here to make money with our clients, not from our clients.
For decades, sports bettors have been misled by “experts”
selling gut picks and hiding losses. We reject that. Our
commitment is to data, transparency, and accountability;
no exceptions.
We're here to build trust, redefine standards, and help our
clients invest like professionals.
Meet Our Team
Graham Robbins
Founder & CEO
Background in computational finance and analytics, developed BetSmart's first algorithm with a 16.70% ROI, leading BetSmart's vision from the front lines.
Joe Solomon
Chief AI Officer
Ph.D. in Mechanical Engineering, Masters in Data Science, Artificial Intelligence, Mechanical Engineering, Bachelors in Aerospace Engineering; Machine Learning Research Scientist spearheading predictive modeling and algorithmic development.
Jonah Melton
Chief Operating Officer
Background in high finance, startup growth, solving problems, delivering results; implementing tactical operational processes, creating strategies and infrastructure to translate our vision into material scalability.
Alex Bernal
Chief Quantitative Officer
Masters in Applied Data Science, Financial Engineering; Bachelors in Economics; Expertise in financial markets, portfolio management, algorithmic trading, machine learning, risk management, statistical backtesting; Quantitative Data Scientist governing the execution of all technological optimization and superior models.
Vinayak Tripathi
Senior Advisor, Quantitative Research
Ph.D. in Economics, Masters in Financial Mathematics, Electrical Engineering, Bachelors in Electrical Engineering; Quantitative Macroeconomic Research Director and Portfolio Manager pioneering optimal analytical frameworks, precise structure, and repeatable processes.
Felix Lindgren
Founding Engineer
Full Stack developer and software wizard, responsible for automating internal and external processes, optimizing front end and back end infrastructure, as well as streamlining algorithmic development.
Akshay Srinivasan
Chief Strategy Officer
Masters in Financial Engineering; Bachelors in Mathematics, Data Science, and Economics; Quantitative Researcher and Strategist applying machine learning, data-informed decision-making, and cross-functional execution to accelerate competitive advantage and sustainable growth.
Shiv Mehta
Quantitative Researcher
Bachelors in Data Science and Cognitive Science specializing in machine learning and neural computation; Machine Learning Researcher and Quantitative Technologist concentrating on GPU-accelerated finance, derivatives modeling, LLM optimization, and statistical arbitrage.
Mason Marchetti
Associate Quantitative Researcher
Masters in Financial Engineering; Bachelors in Integrated Engineering, Computer Science; Quantitative Researcher focusing on fundamental algorithmic analysis and comprehensive risk management.
Get in Touch
Have questions or want to learn more? Join our Discord community or reach out to our team.