About RacingLine

The story behind RacingLine's quantitative approach to F1 predictions.

How It Started

In early 2023, a group of F1 fans built a prediction model for our own race weekend betting. One of us, a data scientist, led the technical development. The model's performance quickly exceeded our expectations, consistently identifying value the bookmakers missed.

After extensive research, we discovered we had created something unique: the first dedicated F1 prediction and handicapping service of its kind. No one else was combining rigorous quantitative analysis with F1 expertise to find value bets.

With Formula 1's explosive growth in popularity, we realized we weren't the only fans looking for a more intelligent approach to betting on races. That's why we've made RacingLine available to other enthusiasts who appreciate data-driven insights and proven results.

Performance Metrics

Our verified results across three seasons of F1.

18%

Return on Investment

63%

Win Rate

124

Bets Placed

Our Methodology

Quantitative Foundation

Led by a PhD in data science, our team applies advanced statistical techniques to F1 data. This includes machine learning models, Bayesian inference, and time series analysis to identify market inefficiencies.

Adaptive Modeling

Our models continuously incorporate new data, adapting to regulation changes, team developments, and evolving track characteristics. This ensures our predictions remain accurate as the sport evolves.

Risk Management

We employ sophisticated risk management techniques, including modified Kelly Criterion stake sizing and maximum drawdown limits. This approach prioritizes long-term sustainability over short-term gains.

Data Infrastructure

Our database encompasses comprehensive F1 data: race results, qualifying performances, practice sessions, weather conditions, and track-specific variables dating back to 2018. When our calculated probabilities diverge significantly from market odds, we identify value betting opportunities.

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