NYC Data Science Academy| Blog
Bootcamps
Lifetime Job Support Available Financing Available
Bootcamps
Data Science with Machine Learning Flagship 🏆 Data Analytics Bootcamp Artificial Intelligence Bootcamp New Release 🎉
Free Lesson
Intro to Data Science New Release 🎉
Find Inspiration
Find Alumni with Similar Background
Job Outlook
Occupational Outlook Graduate Outcomes Must See 🔥
Alumni
Success Stories Testimonials Alumni Directory Alumni Exclusive Study Program
Courses
View Bundled Courses
Financing Available
Bootcamp Prep Popular 🔥 Data Science Mastery Data Science Launchpad with Python View AI Courses Generative AI for Everyone New 🎉 Generative AI for Finance New 🎉 Generative AI for Marketing New 🎉
Bundle Up
Learn More and Save More
Combination of data science courses.
View Data Science Courses
Beginner
Introductory Python
Intermediate
Data Science Python: Data Analysis and Visualization Popular 🔥 Data Science R: Data Analysis and Visualization
Advanced
Data Science Python: Machine Learning Popular 🔥 Data Science R: Machine Learning Designing and Implementing Production MLOps New 🎉 Natural Language Processing for Production (NLP) New 🎉
Find Inspiration
Get Course Recommendation Must Try 💎 An Ultimate Guide to Become a Data Scientist
For Companies
For Companies
Corporate Offerings Hiring Partners Candidate Portfolio Hire Our Graduates
Students Work
Students Work
All Posts Capstone Data Visualization Machine Learning Python Projects R Projects
Tutorials
About
About
About Us Accreditation Contact Us Join Us FAQ Webinars Subscription An Ultimate Guide to
Become a Data Scientist
    Login
NYC Data Science Acedemy
Bootcamps
Courses
Students Work
About
Bootcamps
Bootcamps
Data Science with Machine Learning Flagship
Data Analytics Bootcamp
Artificial Intelligence Bootcamp New Release 🎉
Free Lessons
Intro to Data Science New Release 🎉
Find Inspiration
Find Alumni with Similar Background
Job Outlook
Occupational Outlook
Graduate Outcomes Must See 🔥
Alumni
Success Stories
Testimonials
Alumni Directory
Alumni Exclusive Study Program
Courses
Bundles
financing available
View All Bundles
Bootcamp Prep
Data Science Mastery
Data Science Launchpad with Python NEW!
View AI Courses
Generative AI for Everyone
Generative AI for Finance
Generative AI for Marketing
View Data Science Courses
View All Professional Development Courses
Beginner
Introductory Python
Intermediate
Python: Data Analysis and Visualization
R: Data Analysis and Visualization
Advanced
Python: Machine Learning
R: Machine Learning
Designing and Implementing Production MLOps
Natural Language Processing for Production (NLP)
For Companies
Corporate Offerings
Hiring Partners
Candidate Portfolio
Hire Our Graduates
Students Work
All Posts
Capstone
Data Visualization
Machine Learning
Python Projects
R Projects
About
Accreditation
About Us
Contact Us
Join Us
FAQ
Webinars
Subscription
An Ultimate Guide to Become a Data Scientist
Tutorials
Data Analytics
  • Learn Pandas
  • Learn NumPy
  • Learn SciPy
  • Learn Matplotlib
Machine Learning
  • Boosting
  • Random Forest
  • Linear Regression
  • Decision Tree
  • PCA
Interview by Companies
  • JPMC
  • Google
  • Facebook
Artificial Intelligence
  • Learn Generative AI
  • Learn ChatGPT-3.5
  • Learn ChatGPT-4
  • Learn Google Bard
Coding
  • Learn Python
  • Learn SQL
  • Learn MySQL
  • Learn NoSQL
  • Learn PySpark
  • Learn PyTorch
Interview Questions
  • Python Hard
  • R Easy
  • R Hard
  • SQL Easy
  • SQL Hard
  • Python Easy
Data Science Blog > Data Visualization > Beyond the Podium: A Global Journey Through Formula 1 History

Beyond the Podium: A Global Journey Through Formula 1 History

Tomer Choresh
Posted on Apr 29, 2024

 

Introduction

I first got hooked on Formula One during the COVID-19 pandemic. Since 2021, I’ve moved from just watching the Netflix show (Drive to Survive) to reading about it. This sport is exciting because of its fast races and the history of great drivers and teams. Finding it endlessly fascinating, I decided to research it in depth and make it the topic of my data science project. I explored interesting aspects of Formula One by asking three questions:

  1. Which country won the most championships?
  2. Where does the US rank in Formula One?
  3. How has Formula One evolved?


 The evolution of Formula One

Formula One is famous worldwide for its fast cars and high-tech competitions. It was established in 1950 and has grown a lot since then. Teams use smart strategies and advanced technology to win races.

In the beginning, some constructors had multiple drivers in the same race. The sport has evolved through the years as cars have been reshaped by technology, aerodynamics, fuel, and tires, among many parameters. In other words, this is not your grandfather’s or even father’s Formula One experience.

How does it work today?

There are only 10 constructors (teams), and 20 drivers in every race weekend on track. Each team can use two cars (and two drivers), and there are 2 competitions.

  1. Drivers’ championship (individual)
  2. Constructors’ championship (team effort)

The constructors make up the team that builds the car and designs an aerodynamic body. It also sometimes designs and builds the engine. The team has the authority to sign a new driver or release one. They usually have two main drivers and one or two backup drivers in any case of need..


Data

While there are many factors involved in racing, the key data points have mostly been consolidated into Kaggle dataset that covers the championship race data from 1950-2020. This comprehensive dataset covers almost the whole history of this sport, providing 14 informative files about races, drivers, constructors, circuits, and many more. 

While the data was easily accessible, it still took some prep work to make it usable for my purposes to find the answers to the three questions I had defined. I had to merge many files into one table for almost every graph I wanted to create.

  

Analysis and Insights

First Question:

Which country won the most championships? When I looked at the data, it was clear that the UK stands out. UK drivers lead in almost every category. Together, they have won 20 championships – far more than any single country – as you can see in the graph below (Figure 1).

Number of drivers' championships. UK with the most - 20

Figure 1, Number Of Drivers' Championships.

 

The point system is the best way to understand who is the best here. I decided to check the total drivers’ points, and the British drivers got the most. It also leads in the constructors’ championship and even the number of drivers and constructor. The UK won the most podiums, which means, it is obviously the best-ranked country for racing championships (Figure 2).

#Podiums by nationality. The UK with more than 700, German in second place with around 400 and so on.

Figure 2, Podiums By Nationality.

 


Second Question:

Where does the US rank in Formula One? While searching for the answer to that question, I discovered a very interesting reality. The US has put a lot of effort into Formula One. The US is home to the greatest number of race tracks in the world (Figure 3). It also has had a lot of drivers and teams throughout history (Figure 4). Note the difference between the number of circuits in the US and the rest of the world.

This would lead one to believe that the US is a leader in most Formula One categories. But when I checked the results, I saw that the US isn't doing as well as expected. US drivers tend to score lower than those in the top ten countries. In fact, when measured in terms of driver’s points, the US only ranks in 11th place, though it achieves 8th place in the total constructors’ points.

 

The US with 12 circuits, the next country is France with 7, Spain with 6, and Portugal, UK and Italy with 4

Figure 3, The US Invests In Circuits.

165 British drivers, 158 American, which put the US in the second place it number of drivers

Figure 4, Second Place In Number Of Drivers For The US.

 


Third Question:

In the last part of my project, I discuss the evolution of Formula One. I divided the data into three time periods to see trends. This way I could visualize how the rules and technology have changed. Right away, I noticed big differences. The number of drivers in each race used to vary substantially, from 10 to 55, but now there are always around 20 (Figure 5). 

first era (1950-1974) between 10-55 drivers in a race. the second era (1975-1999) with 15-39. And (2000-2023) with 18-24 drivers.

Figure 5, Number Of Drivers In Each Race.

 

increasing number of races from 7 to 22 through history

Figure 6, Number Of Races Every Year.

The sport has also become more popular, which you can see by the increasing number of races each season. The graph above shows the number of races steadily climbing since 1950. The unusually steep drop in 2020 is likely due to the pandemic. The number of races hit new highs in subsequent years (Figure 6).

I also looked at drivers' ages when they scored their first points (Figure 7). In the early days, the oldest driver was around the age of 54. Today, drivers start their campaign when they’re younger, usually around 17 or 18. But there are still some new drivers who only score their first points between 25 and 30.

To achieve success in modern Formula One, drivers often begin their racing careers at a younger age compared to earlier times. Historically, participants in races tended to be older. An analysis of the age at which drivers scored their first points highlights this shift. Initially, it was common for drivers to earn their first points at ages older than 35. In contrast, today's drivers typically secure their first points between the ages of 18 and 30, reflecting a trend toward younger competitors entering the sport.

Decreasing from the range of 25 to 54 in the early time, compared to today when they are between 17 to 30.

Figure 7, Drivers' First Points' Age.

 

The way points are given out has changed several times too. And It can be shown by looking at the total points through the eras I checked. Another interesting insight I’ve noticed was how today’s teams are not that far apart from each other in terms of the number of points. In contrast, in the earlier era, there was a much greater difference between the winning teams and others.  

 

Conclusion and future work

 

The changes in Formula One show how the sport adapts to keep up with increasing concerns about safety while also meeting the demand for greater speed. At the beginning, there were not so many regulations. Every driver with a fast car could join the race with his equipment. The number of fatality accidents in the early stage was insane. 

Today, an insistence on improving those numbers has led to safer and more reliable cars, as well as better training for drivers. The driver today has to have a special license to drive those cars. I don’t know if the point system we have today will last forever, but I believe that the FIA (Fédération Internationale de l'Automobile), the governing body of motor sport, will try to keep this sport in a good place with safe circuits, and keep developing safety for the drivers and the team.

I wish I could have a deeper analysis of regulatory changes such as safety, circuits, engines. It’s fascinating to me to understand this and follow the trends about these topics. I also didn’t discuss sprint races, shorter and more intense versions of the races, added to enhance the race weekend. The schedule of a sprint weekend is challenging for the drivers and can give an opportunity for any of them to deliver a good result and get points. Unfortunately, as the sprint format is new and has started in 2021 with only a few races during the season, there is not enough data on it to analyze the impact of this trend. 

 

Thank you for reading my blog about F1 through the lens of countries and their achievements. Hope you enjoyed it.

I invite you to take a look at my GitHub for more of my work. And you are very welcome to reach me on my linkedin.

About Author

Tomer Choresh

Data enthusiast and aspiring data scientist, currently deepening my expertise in data analytics. Passionate about uncovering insights that drive impactful decisions. Eager to collaborate with like-minded professionals and explore innovative solutions. Based in New York
View all posts by Tomer Choresh >

Related Articles

Capstone
Catching Fraud in the Healthcare System
Capstone
The Convenience Factor: How Grocery Stores Impact Property Values
Capstone
Acquisition Due Dilligence Automation for Smaller Firms
Machine Learning
Pandemic Effects on the Ames Housing Market and Lifestyle
Machine Learning
The Ames Data Set: Sales Price Tackled With Diverse Models

Leave a Comment

No comments found.

View Posts by Categories

All Posts 2399 posts
AI 7 posts
AI Agent 2 posts
AI-based hotel recommendation 1 posts
AIForGood 1 posts
Alumni 60 posts
Animated Maps 1 posts
APIs 41 posts
Artificial Intelligence 2 posts
Artificial Intelligence 2 posts
AWS 13 posts
Banking 1 posts
Big Data 50 posts
Branch Analysis 1 posts
Capstone 206 posts
Career Education 7 posts
CLIP 1 posts
Community 72 posts
Congestion Zone 1 posts
Content Recommendation 1 posts
Cosine SImilarity 1 posts
Data Analysis 5 posts
Data Engineering 1 posts
Data Engineering 3 posts
Data Science 7 posts
Data Science News and Sharing 73 posts
Data Visualization 324 posts
Events 5 posts
Featured 37 posts
Function calling 1 posts
FutureTech 1 posts
Generative AI 5 posts
Hadoop 13 posts
Image Classification 1 posts
Innovation 2 posts
Kmeans Cluster 1 posts
LLM 6 posts
Machine Learning 364 posts
Marketing 1 posts
Meetup 144 posts
MLOPs 1 posts
Model Deployment 1 posts
Nagamas69 1 posts
NLP 1 posts
OpenAI 5 posts
OpenNYC Data 1 posts
pySpark 1 posts
Python 16 posts
Python 458 posts
Python data analysis 4 posts
Python Shiny 2 posts
R 404 posts
R Data Analysis 1 posts
R Shiny 560 posts
R Visualization 445 posts
RAG 1 posts
RoBERTa 1 posts
semantic rearch 2 posts
Spark 17 posts
SQL 1 posts
Streamlit 2 posts
Student Works 1687 posts
Tableau 12 posts
TensorFlow 3 posts
Traffic 1 posts
User Preference Modeling 1 posts
Vector database 2 posts
Web Scraping 483 posts
wukong138 1 posts

Our Recent Popular Posts

AI 4 AI: ChatGPT Unifies My Blog Posts
by Vinod Chugani
Dec 18, 2022
Meet Your Machine Learning Mentors: Kyle Gallatin
by Vivian Zhang
Nov 4, 2020
NICU Admissions and CCHD: Predicting Based on Data Analysis
by Paul Lee, Aron Berke, Bee Kim, Bettina Meier and Ira Villar
Jan 7, 2020

View Posts by Tags

#python #trainwithnycdsa 2019 2020 Revenue 3-points agriculture air quality airbnb airline alcohol Alex Baransky algorithm alumni Alumni Interview Alumni Reviews Alumni Spotlight alumni story Alumnus ames dataset ames housing dataset apartment rent API Application artist aws bank loans beautiful soup Best Bootcamp Best Data Science 2019 Best Data Science Bootcamp Best Data Science Bootcamp 2020 Best Ranked Big Data Book Launch Book-Signing bootcamp Bootcamp Alumni Bootcamp Prep boston safety Bundles cake recipe California Cancer Research capstone car price Career Career Day ChatGPT citibike classic cars classpass clustering Coding Course Demo Course Report covid 19 credit credit card crime frequency crops D3.js data data analysis Data Analyst data analytics data for tripadvisor reviews data science Data Science Academy Data Science Bootcamp Data science jobs Data Science Reviews Data Scientist Data Scientist Jobs data visualization database Deep Learning Demo Day Discount disney dplyr drug data e-commerce economy employee employee burnout employer networking environment feature engineering Finance Financial Data Science fitness studio Flask flight delay football gbm Get Hired ggplot2 googleVis H20 Hadoop hallmark holiday movie happiness healthcare frauds higgs boson Hiring hiring partner events Hiring Partners hotels housing housing data housing predictions housing price hy-vee Income industry Industry Experts Injuries Instructor Blog Instructor Interview insurance italki Job Job Placement Jobs Jon Krohn JP Morgan Chase Kaggle Kickstarter las vegas airport lasso regression Lead Data Scienctist Lead Data Scientist leaflet league linear regression Logistic Regression machine learning Maps market matplotlib Medical Research Meet the team meetup methal health miami beach movie music Napoli NBA netflix Networking neural network Neural networks New Courses NHL nlp NYC NYC Data Science nyc data science academy NYC Open Data nyc property NYCDSA NYCDSA Alumni Online Online Bootcamp Online Training Open Data painter pandas Part-time performance phoenix pollutants Portfolio Development precision measurement prediction Prework Programming public safety PwC python Python Data Analysis python machine learning python scrapy python web scraping python webscraping Python Workshop R R Data Analysis R language R Programming R Shiny r studio R Visualization R Workshop R-bloggers random forest Ranking recommendation recommendation system regression Remote remote data science bootcamp Scrapy scrapy visualization seaborn seafood type Selenium sentiment analysis sentiment classification Shiny Shiny Dashboard Spark Special Special Summer Sports statistics streaming Student Interview Student Showcase SVM Switchup Tableau teachers team team performance TensorFlow Testimonial tf-idf Top Data Science Bootcamp Top manufacturing companies Transfers tweets twitter videos visualization wallstreet wallstreetbets web scraping Weekend Course What to expect whiskey whiskeyadvocate wildfire word cloud word2vec XGBoost yelp youtube trending ZORI

NYC Data Science Academy

NYC Data Science Academy teaches data science, trains companies and their employees to better profit from data, excels at big data project consulting, and connects trained Data Scientists to our industry.

NYC Data Science Academy is licensed by New York State Education Department.

Get detailed curriculum information about our
amazing bootcamp!

Please enter a valid email address
Sign up completed. Thank you!

Offerings

  • HOME
  • DATA SCIENCE BOOTCAMP
  • ONLINE DATA SCIENCE BOOTCAMP
  • Professional Development Courses
  • CORPORATE OFFERINGS
  • HIRING PARTNERS
  • About

  • About Us
  • Alumni
  • Blog
  • FAQ
  • Contact Us
  • Refund Policy
  • Join Us
  • SOCIAL MEDIA

    © 2025 NYC Data Science Academy
    All rights reserved. | Site Map
    Privacy Policy | Terms of Service
    Bootcamp Application