2024 F1 Round 08 Monaco Analytics Package

The following content is included in the Formula 1 pre-event and post-event package. Pre-event data sets will be available within two days following the previous race. Post-event data sets will be available within a timely manor of the race conclusion. This time frame can vary depending on how quickly the governing body releases the official results.

Analysis conducted prior to a race weekend determines historical performance at a specific venue and in-season form. In this category, the following data points are available:

• Performance index rankings from the previous year at the same venue (if applicable)
• In-season average performance index rankings
• In-season performance index trajectory rankings
• Head-to-Head Probabilities
• Outright Winning Probabilities
• Post-Qualifying updates for Head-to-Head Probabilities
• Post-Qualifying updates for Outright Winning Probabilities

Analysis conducted after a race to analyze athlete performance. In this category, the following data feeds are available:

• Athlete performance index % improvement between current race and in-season averages
• Athlete performance index % improvement between current race and last year at the same venue (if applicable)
• Performance index rankings amongst athletes for the specific race
• Performance index rankings amongst athletes within quartile laps of the specific race
• Head-to-Head results
• Outright Winning results

Please Note: For all performance index rankings and trajectories, a smaller number is better

Qualifying Position

The starting position of an athlete which is determined by the Saturday qualifying round(s). For F1, pre-race grid penalties are taken into account.

Final Position

The order in which athletes finish the event. Pre-race/in-race penalties are taken into account for final position. For F1, post-race penalties are not taken into account as they do not reflect the in-race performance of an athlete. Official F1 classification can be offered to relay final position with post-race penalties taken into account and is used to resolve H2H and outright markets.

Net Movement

Measures an athlete's pure displacement through the entire race relative to starting and finishing position. This reflects how many positions an athlete gained or lost in total.

Net vs Volatility

Measures the balance between the total number of times an athlete changes position on a lap basis vs the final position change from start to finish. A balance between net and volatility is preferred as it reflects the ability of an athlete to overtake and hold a position without a back and forth battle.

Speed

A measure of how fast an athlete can navigate through a given number of laps.

Consistency

A measure of variance in lap times each athlete stays within throughout the entirety of the race.

Efficiency

A measure of athlete performance throughout a race relative to how hard the athlete had to work to finish in the position achieved.

Cornerstone

A measure of how well an athlete can get off the starting grid and set a competitive pace within the first lap of the race.

Quartile Advantage

A measure of athlete performance in terms of quartiles within an event to better understand how an athlete executes over the course of a race. For example, if a race is 44 laps, the first quartile will be indexed including the first 11 laps of the race and the second quartile will be indexed over laps 12 through 22.

% Improvement

Measures the improvement or decline in performance across indexes in the form of a percent. A negative % reflects a decline in performance whereas a positive % reflects an improvement.

Trajectory

Refers to the rate of change in a specific performance index. This helps to identify who is on a rise, decline or plateau in performance. Trajectory values have been scaled for easier interpretation. A smaller trajectory value identifies improvement whereas a larger value depicts a decline in performance. A value close to zero resembles a plateau in performance.

Finish Position Key

If an athlete does not have a final position in an event, one of the following results will be listed

DNQ = Did not qualify

DNS = Did not start race

DNF = Did not finish race

JSON file structure

Please download and view sample files available with this offer.

Data Collection

All source data was responsibly aggregated from publicly accessible sources.

Apex146 offers analytical and technical resources supporting the action sports industry. A proprietary athlete performance indexing platform sits at the core of everything we produce from AI driven content to event simulations and in-depth athlete statistics. Apex146's partnership with AWS has unlocked an efficient and scalable architecture that delivers against market demands.

Platform Pillars

1. Raw Data Ingestion and Performance Index Design
2. Performance Indexing Through Machine Learning
3. Race Modeling Through High Frequency Race Simulations
4. Telling The Story Through Gen AI

The Apex146 team currently covers Formula 1, MotoGP (TM), MXGP, UCI Downhill Mountain Biking, Grand Tour Cycling and FIS World Cup Skiing.