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tour-de-france

Here are 8 public repositories matching this topic..., thomascamminady / letourdataset.

Every cyclist and stage of the Tour de France (up to including 2024) in four CSV files.

• Updated Aug 2, 2024

alastairrushworth / tdf

🚴🏅📊Tour de France winners and stages data

• Updated Feb 19, 2024

edavis25 / Fantasy-Cycling

Application for running a fantasy cycling league.

• Updated Jan 5, 2023

onlyandrewn / tour-de-france

How has the Tour de France changed in the last 100 years?

• Updated Jul 10, 2022
• Jupyter Notebook

IllusionInk / tour_de_drugs

Narrative visualisation depicting the widespread consumption and adoption of drugs in the most prestigious cycle race of the world - Tour De France

• Updated May 21, 2019

Nerconer / tour-france-winners-list

Python script for building a Tour de France winners list

• Updated Mar 6, 2017

Aditya-Coomar / La-Course

24h Le Mans and Tour de France

• Updated Apr 8, 2024

RemedyData / Dahel_Tour_de_France_Analysis_Internship

Dahel Consultant and Techies Internship: This is a project that entails the analysis of a Tour de France (Tourism)

• Updated Apr 9, 2024

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Le Tour de France dataset webscraping

Jul 2, 2021 • Romain Ferraton

LeTour data set

This file downloads raw data about every rider of every Tour de France (from 1903 up to 2020). This data will then be postprocessed and stored in CSV format. Executing this notebook might take some minutes.

1) Retrieve urls for data extract

First we generate the urls that we need to download the raw HTML pages from the letour.fr website to work offline from here on. The dataframe dflink will stores the respective url for each year. Take a look at view-source:https://www.letour.fr/en/history (at around line 1143-1890).

107 rows × 1 columns

2) Get data from HTML pages and convert results to dataframes

2.1) create function that convert hhh mm’ ss’’ to seconds, 2.2) create a function that will retrieve elements from a source html page located on an input url, 2.3) loop on the dflink dataframe to get data from each url source.

9067 rows × 13 columns

3) Clean up the data

4) write data to csv.

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NTT revamps technology platform for 2020 Tour de France

After a two-month delay caused by COVID-19 pandemic, the 2020 Tour de France (TDF) kicked off last weekend on August 29, the first time since the end of World War II that the international cycling event  is not taking place in July.

The three-week  race, which will run through September 20,  features a total of 176 riders spread across 22 teams with 8 riders per team, traversing a distance of nearly 3,500km in various terrains all over the country.

Like many contemporary sporting events, TDF  has embraced digital transformation, delivering real-time live action from the field to technology-savvy cycling fans on the internet, who long abandoned the traditional television to watch the race on their desktops, laptops, phone and  tablets. TDF organiser Amaury Sport Organisation (ASO) has been working with technology partner NTT to deepen fan engagement on the new channels through interactive and immersive experiences that add value to the live broadcast.

Five years ago, NTT installed sensors installed under the saddle of every bike in the race, capturing real-time data on speed and GPS location through a moving mesh network to the NTT Cloud.

From the two pieces of information (speed and location) obtained from the tracking device on a bike, NTT generates 60 data points per rider, per second . The company then has just a few minutes to generate engaging data visualisations and animations for the live broadcast and other channels.

Then, NTT pushes 10 to 12 data-driven stories to the live broadcast at every stage, and over stories every day on social media.

With live tracking of riders and providing real-time data for broadcasters, the set of services has grown each year. Highlights include enhanced data analytics, a full Race Center website, the use of artificial intelligence and machine learning to provide greater insight into the race, the use of augmented reality, and the creation of fantasy leagues linked to the race.

Updating the technology platform

Even before the pandemic reared its head, NTT was hard at work upgrading a couple of key elements of the technology platform behind the digital innovations in the annual cycling event, according to Rob Webster, vice president of the Advanced Technology Group for Sport at NTT.

First to get the makeover is the real-time  analytics platform, which processes the data from the bike and makes them sensible.

“Why do we need a real time analytics platform? The dirty secret of the IoT world is that the data is not clean,” Webster said during a recent webcast. “As an example of what we face, we get GPS data from those sensors. GPS data has a margin of error of about 10 to 20 metres around where the sensor really is.  Imagine a bike moving up the Alps and we get a reading for a particular rider in that area between all of the group. Where exactly is that rider?  So, we actually have to constantly monitor where the riders are, who are they riding with and how fast they are going so that we can correct the GPS errors and snap them into the route in the most likely location that they really are. That is why we need to run real-time data processing.”

NTT has built the TDF data analytics platform from the ground up.  This year, it has migrated to an open-source platform, building a containerised solution that can be deployed on a modular basis. Websters gave two reasons for the move.

“Five years ago, open-source was not sufficiently robust to deal with the extremely low latency that we have to deal with. That has changed and we are now able to take advantage of the incredible technology changes that have happened in the open source world.

“The second reason is that we have learned a whole lot in the last five years, and we understood that we don’t only support the tour, but within the tour, different stages are different. Time trials are different to a normal stage. Therefore, it is easier to build the platform in a much more modular basis – reusable functions that can be rearranged in different ways or used in different sequences. How long the riders have been riding for on the normal stage is different to  how long riders have been riding for on a time trial where they work on different start times.”

The next key element of the TDF technology platform to be rejigged is the API layer, which makes the GPS, speed and other reference data available. NTT retired its own inhouse API solution in favour of using a set of PaaS services from Microsoft Azure.

“While the API layer has to be robust, there isn’t anything that we are doing with the API that is truly unique to us. So, rather than build our own API, we shifted to using a set of PaaS services from Azure. It is a matter of configuring the API technologies that Microsoft has  built on the Azure platform, but we do not need to invest a whole lot of time in building our own unique API. There is no value there,” Webster explained.

The API layer was initially built to support the Race Center website and app, which provides live tracking of the race. It grew over the years to support new applications such as the commentators app.

“It was designed to support specific applications.  This year, we have shifted - coming  at it from an information architecture point of view. It radically simplify the number and complexity of the endpoints. And that has paid huge dividends in terms of supporting all the consumers from the website and applications and things. We’ve got far fewer endpoints that we need to manage, and they are far easier for the third-party developers or even internal developers, other organisations that are using these APIs. It is a much cleaner model for us to use,” Webster said.

The Race Center website is another area that has a significant technology change this year. It was originally intended as a desktop app albeit it’s mobile enabled. However, noting that usage statics over the last five years showed a strong growth towards mobile, NTT has revamped the website into a mobile-first solution.

“This year we focused on delivering a mobile first solution, but also aligning it more tightly with ASO’s digital strategy.  So now the Race Center is much closer in terms of look and feel, and in how it is embedded, its architecture and its functions with the other ASO race websites that they run. I am really hoping the ASO provides a more seamless and consistent experience for fans,” Webster said.

Meanwhile, one the new digital enhancements introduced to the TDF this years is the Augmented Reality Data (AR) app.

In addition to the live race footage, the app will provide selected users with a unique way of viewing and interacting with live race data and the amazing landscapes of the Tour de France. For the first time this will allow fans to appreciate the scale of the event in 3D from their home. With an unprecedented view from the sky, they will see the riders among the mountains, valleys, rivers and lakes, and have access to interactive live data on the race while feeling like they’re actually viewing the race from a helicopter.

Creating the Virtual Zone Technique

NTT decided not to send a team to France to man the NTT control centre, which is basically  a large truck positioned at the finish line of each stage  and keeps an eye on all technology operations.

Instead, the company developed the Virtual Zone Technique that brings together different technologies to deliver its Tour de France services remotely for the first time.

“We came up the idea of using all our digital and collaboration platforms to create a Virtual Zone Technique, so people sitting in Melbourne or Johannesburg would have the same level of access to the data, videos and conversations they were used to in the physical Zone Technique,” said Peter Gray, SVP Advanced Technology Group – Sports at NTT.

The Zone Technique is the technology environment that supports everything NTT  does at the Tour de France, from gathering and analysing live-tracking data to creating data visualizations and stories that are published on various platforms and as part of the live broadcast.

“Remote execution has given us the opportunity to bring together a lot of services that weren’t together before – video streams from the end of the race, data monitoring, and an observability platform that allows the team to view everything through one portal, for example,” Gray said.

Gigi has more than 15 years of experience in technology journalism, covering various aspects of enterprise IT and telecommunications from both business and technology perspective. Before joining CXOCIETY as editor for FutureIoT in July 2019, she was assistant editor of ComputerWorld Hong Kong. Based in Hong Kong, she started with regional IT publications under CMP Asia (now Informa), including Asia Computer Weekly, Intelligent Enterprise Asia and Network Computing Asia and Teledotcom Asia. She had contributed articles to South China Morning Post, TechTarget and PC Market among others.

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Tour de france data.

This dataset is tdf_tweets.csv , a table of 1000 ‘tweets’ harvested from the Twitter Streaming API using a a modified version of tweepy, a pre-existing Python library.

In fact, the original dataset was much larger, consisting of roughly 42,000 tweets. These were filtered out from dozens of gigabytes of Twitter data using a long R script . This script took around 1 day to run on a fast computer! A random selection of 1000 of these tweets was selected for this module. To overcome confidentiality issues, a number of changes were made to the files using another R script called tdf-clean because it cleans Tour de France data. Get it?!

Key features of this script include:

Removal of superfluous variables

Raw Twitter data contains lots of data. To reduce size, the table was shunk both in length (number of rows) and in width (number of columns):

Removal of sensitive text

It is hard to identify what constitutes ‘sensitive’ text, so any words which were unusual, contained html links or the identifying @ symbol were removed:

Setting maximum number of words

To make the text shorter and more manageable, a maximum word length was set. To remove excess words, a new R function was defined and run on the dataset:

Analysing the data

To begin to analyse the data, there are many options. R is a powerful data analysis tool; to load and begin to analyse the data in R, try the following:

table: Latitude and longitude of tweets

table: Sample of text associate with tweets

Public sample Data files

Pedaling through the years: analyzing the evolution of le tour de france data.

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Tour de France - statistics & facts

Recordbreakers, the yellow jersey, 2021 edition, key insights.

Detailed statistics

Tour de France entrants and finishers 1903-2024

Tour de France 2021: general riders ranking, by times

Tour de France 2021 : general teams ranking, by times

Editor’s Picks Current statistics on this topic

Individual Sports

Budget of selected Tour de France teams 2023

Winner's average speed in the Tour de France 1903-2024

Tour de France total French TV audience 2022-2023

Further recommended statistics

Event history.

• Premium Statistic Tour de France entrants and finishers 1903-2024
• Basic Statistic Most Tour de France wins 1903-2024, by country
• Premium Statistic Winner's average speed in the Tour de France 1903-2024

Number of entrants and finishers in the Tour de France from 1903 to 2024

Most Tour de France wins 1903-2024, by country

Countries with the most Tour de France victories as of 2024

Winner's average speed in the Tour de France 1903-2024

Tour de France winner's average speed from 1903 to 2024 (in kilometers per hour)

• Premium Statistic Tour de France 2021: general riders ranking, by times
• Premium Statistic Tour de France 2021 : general teams ranking, by times
• Premium Statistic Tour de France 2021: best sprinters, by number of points
• Premium Statistic Tour de France 2021: Best climbers, by number of points
• Premium Statistic Salaries of the highest-paid Tour de France riders 2021
• Premium Statistic Budget of selected Tour de France teams 2023
• Premium Statistic Tour de France performance bonuses 2021

General riders ranking of the Tour de France in 2021, by times (in minutes)

General teams ranking of the Tour de France in 2021, by times (in minutes)

Tour de France 2021: best sprinters, by number of points

Ranking of the Tour de France sprinters in 2021, by number of points

Tour de France 2021: Best climbers, by number of points

Ranking of the Tour de France climbers in 2021, by number of points

Salaries of the highest-paid Tour de France riders 2021

Highest-paid Tour de France cyclists in 2021 (in million euros)

Tour de France teams with the biggest budgets in 2023 (in million U.S. dollars)

Tour de France performance bonuses 2021

Value of the Tour de France individual general classification bonuses in 2021 (in euros)

• Basic Statistic Tour de France riders with the most victories 1903-2024
• Basic Statistic Riders with the most days in the Tour de France yellow jersey 1903-2024
• Basic Statistic Tour de France riders with the most stage wins 1903-2024
• Premium Statistic Riders with the most Tour de France entries 1903-2024
• Premium Statistic Tour de France best-performing countries 1903-2024, by podium position

Tour de France riders with the most victories 1903-2024

Cyclists with the most Tour de France victories as of 2024

Riders with the most days in the Tour de France yellow jersey 1903-2024

Cyclists that have spent the most days in the yellow jersey at the Tour de France as of 2024

Tour de France riders with the most stage wins 1903-2024

Cyclists with the most Tour de France stage wins as of 2024

Riders with the most Tour de France entries 1903-2024

Cyclists with the most starts in the Tour de France as of 2024

Tour de France best-performing countries 1903-2024, by podium position

Countries with the most Tour de France victories from 1903 to 2024, by podium position

TV audience and sponsorship

• Premium Statistic Tour de France total French TV audience 2022-2023
• Premium Statistic TV channels broadcasting Tour de France 2021
• Premium Statistic Tour de France live broadcasters 2021, by geographical area
• Premium Statistic Tour de France sponsor partners 2021, by type
• Premium Statistic Tour de France revenue distribution 2019

Number of TV viewers of the Tour de France in France in 2022 and 2023 (in millions)

TV channels broadcasting Tour de France 2021

Number of TV channels broadcasting the Tour de France in 2021

Tour de France live broadcasters 2021, by geographical area

Number of broadcasters with live coverage rights for the Tour de France in 2021, by geographical area

Tour de France sponsor partners 2021, by type

Number of Tour de France sponsorship partners in 2021, by type

Tour de France revenue distribution 2019

Tour de France revenue in 2019, by source

Fan interest

• Premium Statistic Interest in watching Tour de France 2020 and 2021, by country
• Premium Statistic Share of the French population intending to follow the Tour de France 2021
• Premium Statistic Influencing factors for watching Tour de France 2021, by nation
• Premium Statistic Deterrents for not watching Tour de France 2021, by nation

Interest in watching Tour de France 2020 and 2021, by country

Level of interest in the Tour de France in selected countries worldwide in 2020 and 2021

Share of the French population intending to follow the Tour de France 2021

Share of the population intending to follow the Tour de France in France from 2016 to 2021

Influencing factors for watching Tour de France 2021, by nation

Most common reasons for watching the Tour de France in selected countries worldwide in 2021

Deterrents for not watching Tour de France 2021, by nation

Most common reasons for not watching the Tour de France in selected countries worldwide in 2021

Anti-doping rule violations

• Premium Statistic Sports with the most anti-doping rule violations worldwide 2020
• Premium Statistic Tour de France riders who committed anti-doping violations 1968-2023
• Premium Statistic Confidence in Tour de France teams for complying with the anti-doping rules 2023

Sports with the most anti-doping rule violations worldwide 2020

Number of anti-doping rule violations worldwide in 2020, by sport

Tour de France riders who committed anti-doping violations 1968-2023

Share of Tour de France riders who committed anti-doping rule violations from 1968 to 2023

Confidence in Tour de France teams for complying with the anti-doping rules 2023

Level of trust in the Tour de France teams in complying with the anti-doping rules in 2023, by team

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10 years of coinnovation transforms the Tour de France and Tour de France Femmes avec Zwift

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• Immersive race experience for fans
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Use technology to bring a real race to real fans.

The partnership between the Tour de France and NTT DATA began in 2014, when we installed IoT-enabled rider tracking and data-gathering – just in time for the 2015 Tour de France. For the first time in the history of the race, live data from the trackers was shared on television broadcasts, giving fans second-by-second information on rider speeds and locations.

2024 marks a decade of our collaboration as the Official Technology Partner of the Tour de France and, since 2022, the Tour de France Femmes avec Zwift. Our enduring partnership has revolutionized the management of the world’s most prestigious cycling event, created a more immersive fan experience and pushed the boundaries of technological innovation. The innovations pioneered at the Tour de France have accelerated the digital transformation of professional cycling, showcasing how putting data at the fingertips of fans and officials can transform the way races are managed and experienced.

To bring the race to the fans, we combine cutting-edge technologies such as IoT, machine learning, artificial intelligence and edge computing. The IoT sensors underneath bicycle saddles transmit a constant stream of latitude, longitude and speed data. This live telemetry feeds into the TV broadcast, social media and other digital channels, giving fans and followers a greater understanding of team tactics and individual rider performance, and greatly enhancing their experience of the race.

Technology also gives race organizers a complete view of race operations, empowering them to make fast, informed, data-driven decisions to address any incidents in real time.

From in-depth analytics and visualizations to the digital twin of the event, 3D race tracker and an AI-enabled digital human, our solutions showcase the indomitable spirit of the riders in the peloton and help the organizers to manage the race effectively and keep operations running smoothly.

"We want our fans to have an exceptional experience, whether they’re at home or on the roadside cheering on the race. Without the platforms and technology that we built and managed with NTT DATA this simply wouldn’t be possible."

Consistent experience across a challenging route.

Each year, fans and riders wait in suspense to find out just where the race will take place, as the routes for the Tour de France and Tour de France Femmes avec Zwift change for each edition. All they know for sure is that some of the stages will span remote parts of France and Europe.

This is the beauty of having an entire continent as your event location – but it’s also a technological challenge.

With race officials and broadcasters moving to different cities and remote locations every day, the network has to be flexible and reliable enough to connect fans, organizers and officials to the race environment and the riders in real time.

In our first year as Official Technology Partner, our solution focused mainly on the IoT sensors attached to each bike. The raw data gathered from these tracking devices was processed by our cloud-based data analytics platform and enhanced with additional data, such as local weather conditions, to generate detailed insights using machine learning models. These insights were then shared across various race channels, including live broadcasts, applications and social media, providing fans with engaging, near real-time experiences.

Fast-forward through 10 years of constantly improving and evolving our solution, we now have a digital twin of the race. It combines layers of real-time information to create a digital version of the event, mirroring all its real-world complexities. The digital twin includes information on race vehicles, the publicity caravan, event assets, staff locations, the event village, occupancy of VIP and other zones, and even weather conditions. Race officials and security teams now have the necessary insights to make important decisions fast.

The digital twin allows us to further enhance the fan experience, with new visualizations and exciting stories being created every year. The Tour de France Fantasy League and the Tour de France Femmes Fantasy League offer another way for fans to engage with the race.

In 2022, we introduced our digital human, Marianne to further enhance the fan experience. This lifelike avatar, located in our Tech Truck at the event, answered questions and provided information around the Tour de France to NTT DATA clients.

"Technology plays a vital part in helping us innovate at the speed fans expect from their mobile and cloud-based applications, all the while providing event insights, rich analytics, and intelligent digital solutions."

A winning experience for riders, fans and race organizers.

Through a decade of partnership, the two organizations have continued to push the boundaries of what can be done with data. By connecting what’s happening at the very edge of the network to passionate fans and race organizers, we’ve fundamentally changed the way the race is viewed and managed. The technology platform powering the Tour de France ensures 100% uptime, so distributed, international teams can work together to ensure a great experience.

Enhanced fan engagement

The Tour de France has successfully connected with millions of fans worldwide, providing them with rich and immersive experiences. Through the Race Center platform, fans can access real-time data, social media updates and commentary, including Fantasy Leagues and virtual time-trial gaps.

The digital twin and real-time analytics give a complete view of events affecting the race as they unfold. This enables the organizers to proactively identify and address potential issues before they impact the race.

A joint passion for innovation

The Tour de France and NTT DATA have fostered a culture of collaboration and innovation, constantly exploring opportunities that technology brings to these iconic races.

Why NTT DATA

Partnership, about amaury sport organisation, related case studies, absa cape epic connects mountain bikers in the untamed wilds to global fans, achieving nzcis’s vision for a smart sports city, penske entertainment transforms data into exceptional fan experiences, speak to an expert.

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