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      "content": "The dataset offers a rich and comprehensive collection of ***MotoGP World Championship*** 🏍️  data, making it an ideal foundation for hosting a machine learning competition focused on two-wheeled motorsport. It encompasses detailed insights into race results, rider statistics, team performance, bike specifications, tire choices, weather conditions, and track characteristics across multiple seasons. This depth of information allows participants to explore performance patterns, forecast race outcomes, model rider and team standings, and analyze the influence of environmental and technical variables on race dynamics.\n\nBy leveraging this dataset, researchers and enthusiasts can develop machine learning models that reveal strategic trends, adapt to evolving technologies, and assess the impact of rule changes and environmental factors on performance. It opens avenues for innovation and competitive analysis, offering a powerful platform to understand the intricacies of MotoGP racing through the lens of data-driven intelligence.\n\n![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F21861189%2F08a354bc3c8914926597bad228492da2%2FBrad%20Binder_Red%20Bull%20KTM_MotoGP_RC16_XLarge.jpeg?generation=1749551385847098&alt=media)\n\n\n\n## Columns\n\n*   `Unique ID`: A unique identifier for each row in the dataset.\n*   `Rider_ID`: Unique identifier assigned to each rider.\n*   `category_x`: The racing category (e.g., MotoGP, Moto2).\n*   `Circuit_Length_km`: Total length of the race circuit in kilometers.\n*   `Laps`: Number of laps in the race.\n*   `Grid_Position`: Starting position of the rider on the grid.\n*   `Avg_Speed_kmh`: Average speed of the rider during the race (in km/h).\n*   `Track_Condition`: Surface condition of the track (e.g., dry, wet).\n*   `Humidity_%`: Humidity level during the session, in percentage.\n*   `Tire_Compound_Front`: Type of tire compound used on the front tire.\n*   `Tire_Compound_Rear`: Type of tire compound used on the rear tire.\n*   `Penalty`: Penalties incurred by the rider during the race.\n*   `Championship_Points`: Total points accumulated in the championship so far.\n*   `Championship_Position`: Current rank in the championship standings.\n*   `Session`: Type of session (Race, Qualifying, Practice, etc.).\n*   `Year_x`: Year in which the session took place.\n*   `Sequence`: Order or sequence of the entry within a session or race.\n*   `Rider`: A unique identifier assigned to each rider.\n*   `Team`: A unique identifier assigned to each team.\n*   `Bike`: A unique identifier assigned to each bike.\n*   `Position`: Final finishing position in the race.\n     (-1 = DNF (Did Not Finish), -2 = DNS (Did Not Start), -3 = DSQ (Disqualified), -4 = DNQ (Did Not Qualify / Technical issue))\n*   `Points`: Points awarded for the race based on finishing position.\n*   `Shortname`: Abbreviated or nickname version of the country.\n*   `Circuit_name`: Full name of the circuit where the race took place.\n*   `Rider_name`: Full name of the rider.\n*   `Team_name`: Full name of the team.\n*   `Bike_name`: Model of the bike.\n*   `Lap_Time_Seconds`: Average time per lap in seconds (Target Variable).\n*   `Corners_per_Lap`: Number of corners in one lap of the circuit.\n*   `Tire_Degradation_Factor_per_Lap`: Average tire wear rate per lap.\n*   `Pit_Stop_Duration_Seconds`: Time spent during pit stops, in seconds.\n*   `Ambient_Temperature_Celsius`: Air temperature during the session.\n*   `Track_Temperature_Celsius`: Track surface temperature during the session.\n*   `Weather`: Weather condition (e.g., sunny, rainy).\n*   `Track`: Track temperature.\n*   `Air`: Air temperature.\n*   `Ground`: Ground or surface temperature of the track.\n*   `Starts`: Total number of race starts in the rider's career.\n*   `Finishes`: Total number of races the rider finished.\n*   `With_points`: Number of races where the rider scored points.\n*   `Podiums`: Number of times the rider finished in the top 3.\n*   `Wins`: Number of race victories.\n*   `Min_year`: First year the rider competed.\n*   `Max_year`: Most recent year the rider was active.\n*  `Years_active`: Total number of active racing years.\n\n## 📁 Files Included:\n\n*   **train.csv** - the training set\n*   **test.csv** - the test set\n*   **sample_submission.csv** - a sample submission file in the correct format\n*   **val.csv** - to check accuracy on unknown data\n\n## 🎯 Task Objective:\n\nYour goal is to predict the `Lap_Time_Seconds` — the average lap time of a rider in a race — using the given features in the dataset.\n\n\n\n\n",
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      "content": "# Burnout 2025: MotoGP Data Analytics Challenge 🏁\n\nIEEE Computer Society MUJ presents *Burnout 2025*! 🌟 Step into the fast-paced world of MotoGP racing and analyse rider performance, lap times, and race strategies across multiple seasons. With a dataset packed with racing stats, this competition provides a comprehensive look at the sport’s dynamics, challenging you to push the boundaries of data science in motorsports.\n\n\n---\n\n## Competition Objective\n\nThe goal is to leverage data analytics, machine learning, and statistical modeling to predict MotoGP race outcomes and uncover insights into racing dynamics. Participants will explore the dataset, identify key patterns, and build predictive models to forecast rider performance, offering a fresh perspective on the sport.\n\n\n---\n\n## Dataset and Features 🗃️\n\nParticipants will work with a detailed MotoGP dataset featuring lap times, rider statistics, weather conditions, race strategies, and team performance metrics. By blending creativity, domain knowledge, and advanced analytics, participants can unlock unique insights into what drives success on the track.\n\n---\n\n##Competition Details\n\n- Round 1 Start Date: 06/14/2025 10:00 AM IST (06/14/2025 04:30 AM UTC)\n- Round 1 End Date: 06/14/2025 10:00 PM IST (06/14/2025 04:30 PM UTC)\n- Round 2 (Presentation): 06/15/2025 2:30 PM IST onwards (06/15/2025 09:00 AM UTC)\n\n\n##Join the Burnout Challenge! 🏆\n\nRev up your analytical engines and dive into the world of MotoGP analytics! Join us to unravel the complexities of racing data and redefine how we understand performance on the track. This is your chance to shine in the intersection of data science and motorsports.\nGood luck, and may the best data scientists race to the top in this thrilling Burnout competition! 💯\n",
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      "name": "Evaluation",
      "content": "##Evaluation Metric\n\nRoot Mean Squared Error (RMSE) is a commonly used evaluation metric for regression problems in Kaggle competitions. It measures the average magnitude of the errors between the predicted and actual values, providing an indication of the model's accuracy.\n\nRMSE is calculated by taking the square root of the mean of the squared differences between the predicted and actual values. The formula for RMSE is as follows:\n\n![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F21861189%2F7e45d48afb70f6830d227d43c4ff869e%2FScreenshot%202025-06-10%20222724.png?generation=1749574701457452&alt=media)\n\nRMSE has the following characteristics:\n\n- It is always non-negative since it involves squaring the differences.\n- It penalizes larger errors more than smaller errors due to the squaring operation.\n- It has the same unit as the target variable, making it easy to interpret.\n\n\nWhen comparing models in a Kaggle competition, a lower Root Mean Squared Error (RMSE) indicates better performance. The model with the lowest RMSE score is considered the most accurate in terms of minimising the differences between the predicted and actual values.\n\nIt's important to note that RMSE is sensitive to outliers since larger errors have a greater impact on the overall score. Therefore, it is crucial to preprocess the data and handle outliers appropriately to obtain reliable RMSE scores.\n\nIn summary, RMSE is a popular evaluation metric for regression problems in Kaggle competitions. It provides a measure of the average magnitude of the errors, allowing participants to assess and compare the accuracy of their models.\n\nParticipants in this competition can leverage a structured approach to gain profound insights into the dataset, crucial for developing accurate and resilient models. The steps of dataset overview, descriptive statistics, data visualizations, and feature engineering play pivotal roles in achieving this goal.",
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      "name": "rules",
      "content": "•\t**Submissions**:\n\n--Teaming or collaboration is permitted.\n--You cannot sign up to Kaggle from multiple accounts and therefore you cannot submit from multiple accounts.\n\n\n•\t**Eligibility Criteria**:\n\nParticipants should be aged 23 or less. Your college ID cards will be asked for verification.\n\n\n•\t**Event Duration**:\n\n--Round 1 of the competition is set for a time period of 12 hours, starting on 14/06/25 at 10:00 AM and ending on 14/06/25 at 10:00 PM. Participants --must submit their solutions within this timeframe. \n\n--For Round 2 of the competition, the presentation slots will be shared on 15/06/25 by 10:00 AM. The presentations will begin on 15/06/25 starting from 02:30 PM.\n\n\n•\t**Evaluation and Selection:**\n\nSubmissions will be evaluated based on the predefined evaluation criteria provided in the Evaluation Criteria document. The result given by Kaggle is final; however, the top 10 ranked submissions in the Private Leaderboard will be selected for a presentation. The final presentation serves to validate participant authorship of the code, and disqualification follows if the judge determines that the machine learning model was not created by the participant.\n\n\n•\t**Submission Process:**\n\nParticipants can submit their solutions by uploading the solution.csv file directly on the Kaggle platform or by using a notebook. Detailed instructions for submission can be found in the Resources and Roadmap document.\n\n\n•\t**Data Format Requirements:**\n\nIt is crucial to ensure that the solution.csv file adheres to the specified format mentioned in the Resources and Roadmap document. Failure to meet the format requirements may result in a submission being disqualified.\n\n\n•\t**Resources and Support:**\n\nParticipants are encouraged to utilize the provided Resources and Roadmap document, which includes learning materials, tutorials, and additional references to enhance their knowledge and skills. Participants are allowed to refer and use external data for training the model, as long as the target variable is the same.\n\n\n•\t**Collaboration and Questions:**\n\nA dedicated WhatsApp group would be created for this competition, serving as a platform for communication and collaboration among participants. It is also a space to ask questions and seek clarifications from the organizers and fellow participants.\n\n\n•\t**Code of Conduct:**\n\nParticipants are expected to maintain a professional and respectful environment throughout the competition. Any form of misconduct, including plagiarism or violation of the competition rules, will result in immediate disqualification. Though, participants are free to google to explore and learn but any form of copying will not be tolerated.\n",
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      "name": "abstract",
      "content": "A high-octane 12-hour datathon 🏍️ that brings together the thrill of MotoGP racing and the power of data analytics! Compete on Kaggle, dive into complex MotoGP datasets, and use machine learning 🧠 to predict race outcomes and uncover game-changing insights. Collaborate, innovate, and race towards analytical excellence in this adrenaline-pumping challenge! 🌟\n",
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      "name": "foundational-rules",
      "content": "The following Kaggle Competition Foundational Rules (“ Foundational Rules ”) apply to every competition regardless of whether the Sponsor creates competition-specific rules. Any competition-specific rules provided by the Sponsor are in addition to these rules, and in the case of any conflict or inconsistency, these Foundational Rules control and nullify contrary competition-specific rules.\n###GENERAL COMPETITION RULES - BINDING AGREEMENT\n####1. ELIGIBILITY\na. To be eligible to enter the Competition, you must be:</h5>\n1. a registered account holder at Kaggle.com; </h6>\n2. the older of 18 years old or the age of majority in your jurisdiction of residence (unless otherwise agreed to by Competition Sponsor and appropriate parental/guardian consents have been obtained by Competition Sponsor); </h6>\n3. not a resident of Crimea, so-called Donetsk People's Republic (DNR) or Luhansk People's Republic (LNR), Cuba, Iran, Syria, or North Korea; and</h6>\n4. not a person or representative of an entity under U.S. export controls or sanctions (see: [https://www.treasury.gov/resourcecenter/sanctions/Programs/Pages/Programs.aspx][1]).</h6>\n\nb. Competitions are open to residents of the United States and worldwide, except that if you are a resident of Crimea, so-called Donetsk People's Republic (DNR) or Luhansk People's Republic (LNR), Cuba, Iran, Syria, North Korea, or are subject to U.S. export controls or sanctions, you may not enter the Competition. Other local rules and regulations may apply to you, so please check your local laws to ensure that you are eligible to participate in skills-based competitions. The Competition Host reserves the right to forego or award alternative Prizes where needed to comply with local laws. If a winner is located in a country where prizes cannot be awarded, then they are not eligible to receive a prize.</h5>\n\nc. If you are entering as a representative of a company, educational institution or other legal entity, or on behalf of your employer, these rules are binding on you, individually, and the entity you represent or where you are an employee. If you are acting within the scope of your employment, or as an agent of another party, you warrant that such party or your employer has full knowledge of your actions and has consented thereto, including your potential receipt of a Prize. You further warrant that your actions do not violate your employer's or entity's policies and procedures.</h5>   \n\nd. The Competition Sponsor reserves the right to verify eligibility and to adjudicate on any dispute at any time. If you provide any false information relating to the Competition concerning your identity, residency, mailing address, telephone number, email address, ownership of right, or information required for entering the Competition, you may be immediately disqualified from the Competition.</h5>\n\n####2. SPONSOR AND HOSTING PLATFORM\n\na. The Competition is sponsored by Competition Sponsor named above. The Competition is hosted on behalf of Competition Sponsor by Kaggle Inc. (\"Kaggle\"). Kaggle is an independent contractor of Competition Sponsor, and is not a party to this or any agreement between you and Competition Sponsor. You understand that Kaggle has no responsibility with respect to selecting the potential Competition winner(s) or awarding any Prizes. Kaggle will perform certain administrative functions relating to hosting the Competition, and you agree to abide by the provisions relating to Kaggle under these Rules. As a Kaggle.com account holder and user of the Kaggle competition platform, remember you have accepted and are subject to the Kaggle Terms of Service at [www.kaggle.com/terms][2] in addition to these Rules.</h5>\n\n####3. COMPETITION PERIOD\na. For the purposes of Prizes, the Competition will run from the Start Date and time to the Final Submission Deadline (such duration the “Competition Period”). The Competition Timeline is subject to change, and Competition Sponsor may introduce additional hurdle deadlines during the Competition Period. Any updated or additional deadlines will be publicized on the Competition Website. It is your responsibility to check the Competition Website regularly to stay informed of any deadline changes. YOU ARE RESPONSIBLE FOR DETERMINING THE CORRESPONDING TIME ZONE IN YOUR LOCATION.</h5>\n\n####4. COMPETITION ENTRY\na. NO PURCHASE NECESSARY TO ENTER OR WIN. To enter the Competition, you must register on the Competition Website prior to the Entry Deadline, and follow the instructions for developing and entering your Submission through the Competition Website. Your Submissions must be made in the manner and format, and in compliance with all other requirements, stated on the Competition Website (the \"Requirements\"). Submissions must be received before any Submission deadlines stated on the Competition Website. Submissions not received by the stated deadlines will not be eligible to receive a Prize.</h5>\nb. Submissions may not use or incorporate information from hand labeling or human prediction of the validation dataset or test data records.</h5>\nc. If the Competition is a multi-stage competition with temporally separate training and/or test data, one or more valid Submissions may be required during each Competition stage in the manner described on the Competition Website in order for the Submissions to be Prize eligible.</h5>\nd. Submissions are void if they are in whole or part illegible, incomplete, damaged, altered, counterfeit, obtained through fraud, or late. Competition Sponsor reserves the right to disqualify any entrant who does not follow these Rules, including making a Submission that does not meet the Requirements. </h5>\n\n####5. INDIVIDUALS AND TEAMS\na. Individual Account. You may make Submissions only under one, unique Kaggle.com account. You will be disqualified if you make Submissions through more than one Kaggle account, or attempt to falsify an account to act as your proxy. You may submit up to the maximum number of Submissions per day as specified on the Competition Website. </h5>\nb. Teams. If permitted under the Competition Website guidelines, multiple individuals may collaborate as a Team; however, you may join or form only one Team. Each Team member must be a single individual with a separate Kaggle account. You must register individually for the Competition before joining a Team. You must confirm your Team membership to make it official by responding to the Team notification message sent to your Kaggle account. Team membership may not exceed the Maximum Team Size stated on the Competition Website.</h5>\nc. Team Merger. Teams may request to merge via the Competition Website. Team mergers may be allowed provided that: (i) the combined Team does not exceed the Maximum Team Size; (ii) the number of Submissions made by the merging Teams does not exceed the number of Submissions permissible for one Team at the date of the merger request; (iii) the merger is completed before the earlier of: any merger deadline or the Competition deadline; and (iv) the proposed combined Team otherwise meets all the requirements of these Rules. </h5>\nd. Private Sharing. No private sharing outside of Teams. Privately sharing code or data outside of Teams is not permitted. It's okay to share code if made available to all Participants on the forums.</h5>\n\n####6. SUBMISSION CODE REQUIREMENTS\na. Private Code Sharing. Unless otherwise specifically permitted under the Competition Website or Competition Specific Rules above, during the Competition Period, you are not allowed to privately share source or executable code developed in connection with or based upon the Competition Data or other source or executable code relevant to the Competition (“Competition Code”). This prohibition includes sharing Competition Code between separate Teams, unless a Team merger occurs. Any such sharing of Competition Code is a breach of these Competition Rules and may result in disqualification.</h5>\nb. Public Code Sharing. You are permitted to publicly share Competition Code, provided that such public sharing does not violate the intellectual property rights of any third party. If you do choose to share Competition Code or other such code, you are required to share it on Kaggle.com on the discussion forum or notebooks associated specifically with the Competition for the benefit of all competitors. By so sharing, you are deemed to have licensed the shared code under an Open Source Initiative-approved license (see [www.opensource.org][3]) that in no event limits commercial use of such Competition Code or model containing or depending on such Competition Code.</h5>\nc. Use of Open Source. Unless otherwise stated in the Specific Competition Rules above, if open source code is used in the model to generate the Submission, then you must only use open source code licensed under an Open Source Initiative-approved license (see [www.opensource.org][4]) that in no event limits commercial use of such code or model containing or depending on such code.</h5>\n\n####7. DETERMINING WINNERS\na. Each Submission will be scored and ranked by the evaluation metric stated on the Competition Website. During the Competition Period, the current ranking will be visible on the Competition Website's Public Leaderboard. The potential winner(s) are determined solely by the leaderboard ranking on the Private Leaderboard, subject to compliance with these Rules. The Public Leaderboard will be based on the public test set and the Private Leaderboard will be based on the private test set.</h5>\nb. In the event of a tie, the Submission that was entered first to the Competition will be the winner. In the event a potential winner is disqualified for any reason, the Submission that received the next highest score rank will be chosen as the potential winner.</h5>\n\n####8. NOTIFICATION OF WINNERS & DISQUALIFICATION\na. The potential winner(s) will be notified by email.</h5> \nb. If a potential winner (i) does not respond to the notification attempt within one (1) week from the first notification attempt or (ii) notifies Kaggle within one week after the Final Submission Deadline that the potential winner does not want to be nominated as a winner or does not want to receive a Prize, then, in each case (i) and (ii) such potential winner will not receive any Prize, and an alternate potential winner will be selected from among all eligible entries received based on the Competition’s judging criteria.</h5>\nc. In case (i) and (ii) above Kaggle may disqualify the Participant.  However, in case (ii) above, if requested by Kaggle, such potential winner may provide code and documentation to verify the Participant’s compliance with these Rules. If the potential winner provides code and documentation to the satisfaction of Kaggle, the Participant will not be disqualified pursuant to this paragraph.</h5>\nd. Competition Sponsor reserves the right to disqualify any Participant from the Competition if the Competition Sponsor reasonably believes that the Participant has attempted to undermine the legitimate operation of the Competition by cheating, deception, or other unfair playing practices or abuses, threatens or harasses any other Participants, Competition Sponsor or Kaggle.</h5>\ne. A disqualified Participant may be removed from the Competition leaderboard, at Kaggle's sole discretion. If a Participant is removed from the Competition Leaderboard, additional winning features associated with the Kaggle competition platform, for example Kaggle points or medals, may also not be awarded.</h5>\nf. The final leaderboard list will be publicly displayed at Kaggle.com. Determinations of Competition Sponsor are final and binding.</h5>\n\n####9. PRIZES\na. Prize(s) are as described on the Competition Website and are only available for winning during the time period described on the Competition Website. The odds of winning any Prize depends on the number of eligible Submissions received during the Competition Period and the skill of the Participants. </h5>\nb. All Prizes are subject to Competition Sponsor's review and verification of the Participant’s eligibility and compliance with these Rules, and the compliance of the winning Submissions with the Submissions Requirements. In the event that the Submission demonstrates non-compliance with these Competition Rules, Competition Sponsor may at its discretion take either of the following actions: (i) disqualify the Submission(s); or (ii) require the potential winner to remediate within one week after notice all issues identified in the Submission(s) (including, without limitation, the resolution of license conflicts, the fulfillment of all obligations required by software licenses, and the removal of any software that violates the software restrictions).</h5>\nc. A potential winner may decline to be nominated as a Competition winner in accordance with Section 3.8.</h5>\nd. Potential winners must return all required Prize acceptance documents within two (2) weeks following notification of such required documents, or such potential winner will be deemed to have forfeited the prize and another potential winner will be selected. Prize(s) will be awarded within approximately thirty (30) days after receipt by Competition Sponsor or Kaggle of the required Prize acceptance documents. Transfer or assignment of a Prize is not allowed. </h5>\ne. You are not eligible to receive any Prize if you do not meet the Eligibility requirements in Section 2.7 and Section 3.1 above.</h5>\nf. If a Team wins a monetary Prize, the Prize money will be allocated in even shares between the eligible Team members, unless the Team unanimously opts for a different Prize split and notifies Kaggle before Prizes are issued.</h5>\n\n####10. TAXES\na. ALL TAXES IMPOSED ON PRIZES ARE THE SOLE RESPONSIBILITY OF THE WINNERS. Payments to potential winners are subject to the express requirement that they submit all documentation requested by Competition Sponsor or Kaggle for compliance with applicable state, federal, local and foreign (including provincial) tax reporting and withholding requirements. Prizes will be net of any taxes that Competition Sponsor is required by law to withhold. If a potential winner fails to provide any required documentation or comply with applicable laws, the Prize may be forfeited and Competition Sponsor may select an alternative potential winner. Any winners who are U.S. residents will receive an IRS Form-1099 in the amount of their Prize.</h5>\n\n####11. GENERAL CONDITIONS\na. All federal, state, provincial and local laws and regulations apply.</h5>\n\n####12. PUBLICITY\na. You agree that Competition Sponsor, Kaggle and its affiliates may use your name and likeness for advertising and promotional purposes without additional compensation, unless prohibited by law.</h5>\n\n####13. PRIVACY\na. You acknowledge and agree that Competition Sponsor and Kaggle may collect, store, share and otherwise use personally identifiable information provided by you during the Kaggle account registration process and the Competition, including but not limited to, name, mailing address, phone number, and email address (“Personal Information”). Kaggle acts as an independent controller with regard to its collection, storage, sharing, and other use of this Personal Information, and will use this Personal Information in accordance with its Privacy Policy <[www.kaggle.com/privacy][6]>, including for administering the Competition. As a Kaggle.com account holder, you have the right to request access to, review, rectification, portability or deletion of any personal data held by Kaggle about you by logging into your account and/or contacting Kaggle Support at <[www.kaggle.com/contact][7]>.</h5>\nb. As part of Competition Sponsor performing this contract between you and the Competition Sponsor, Kaggle will transfer your Personal Information to Competition Sponsor, which acts as an independent controller with regard to this Personal Information. As a controller of such Personal Information, Competition Sponsor agrees to comply with all U.S. and foreign data protection obligations with regard to your Personal Information. Kaggle will transfer your Personal Information to Competition Sponsor in the country specified in the Competition Sponsor Address listed above, which may be a country outside the country of your residence. Such country may not have privacy laws and regulations similar to those of the country of your residence.</h5>\n\n####14. WARRANTY, INDEMNITY AND RELEASE \na. You warrant that your Submission is your own original work and, as such, you are the sole and exclusive owner and rights holder of the Submission, and you have the right to make the Submission and grant all required licenses.  You agree not to make any Submission that: (i) infringes any third party proprietary rights, intellectual property rights, industrial property rights, personal or moral rights or any other rights, including without limitation, copyright, trademark, patent, trade secret, privacy, publicity or confidentiality obligations, or defames any person; or (ii) otherwise violates any applicable U.S. or foreign state or federal law.</h5>\nb. To the maximum extent permitted by law, you indemnify and agree to keep indemnified Competition Entities at all times from and against any liability, claims, demands, losses, damages, costs and expenses resulting from any of your acts, defaults or omissions and/or a breach of any warranty set forth herein. To the maximum extent permitted by law, you agree to defend, indemnify and hold harmless the Competition Entities from and against any and all claims, actions, suits or proceedings, as well as any and all losses, liabilities, damages, costs and expenses (including reasonable attorneys fees) arising out of or accruing from: (a) your Submission or other material uploaded or otherwise provided by you that infringes any third party proprietary rights, intellectual property rights, industrial property rights, personal or moral rights or any other rights, including without limitation, copyright, trademark, patent, trade secret, privacy, publicity or confidentiality obligations, or defames any person; (b) any misrepresentation made by you in connection with the Competition; (c) any non-compliance by you with these Rules or any applicable U.S. or foreign state or federal law; (d) claims brought by persons or entities other than the parties to these Rules arising from or related to your involvement with the Competition; and (e) your acceptance, possession, misuse or use of any Prize, or your participation in the Competition and any Competition-related activity.</h5>\nc. You hereby release Competition Entities from any liability associated with: (a) any malfunction or other problem with the Competition Website; (b) any error in the collection, processing, or retention of any Submission; or (c) any typographical or other error in the printing, offering or announcement of any Prize or winners.</h5>\n\n####15. INTERNET\na. Competition Entities are not responsible for any malfunction of the Competition Website or any late, lost, damaged, misdirected, incomplete, illegible, undeliverable, or destroyed Submissions or entry materials due to system errors, failed, incomplete or garbled computer or other telecommunication transmission malfunctions, hardware or software failures of any kind, lost or unavailable network connections, typographical or system/human errors and failures, technical malfunction(s) of any telephone network or lines, cable connections, satellite transmissions, servers or providers, or computer equipment, traffic congestion on the Internet or at the Competition Website, or any combination thereof, which may limit a Participant’s ability to participate.</h5>\n\n####16. RIGHT TO CANCEL, MODIFY OR DISQUALIFY\na. If for any reason the Competition is not capable of running as planned, including infection by computer virus, bugs, tampering, unauthorized intervention, fraud, technical failures, or any other causes which corrupt or affect the administration, security, fairness, integrity, or proper conduct of the Competition, Competition Sponsor reserves the right to cancel, terminate, modify or suspend the Competition. Competition Sponsor further reserves the right to disqualify any Participant who tampers with the submission process or any other part of the Competition or Competition Website.  Any attempt by a Participant to deliberately damage any website, including the Competition Website, or undermine the legitimate operation of the Competition is a violation of criminal and civil laws. Should such an attempt be made, Competition Sponsor and Kaggle each reserves the right to seek damages from any such Participant to the fullest extent of the applicable law.</h5>\n\n####17. NOT AN OFFER OR CONTRACT OF EMPLOYMENT\na. Under no circumstances will the entry of a Submission, the awarding of a Prize, or anything in these Rules be construed as an offer or contract of employment with Competition Sponsor or any of the Competition Entities. You acknowledge that you have submitted your Submission voluntarily and not in confidence or in trust. You acknowledge that no confidential, fiduciary, agency, employment or other similar relationship is created between you and Competition Sponsor or any of the Competition Entities by your acceptance of these Rules or your entry of your Submission.</h5>\n\n####18. DEFINITIONS\na. \"Competition Data\" are the data or datasets available from the Competition Website for the purpose of use in the Competition, including any prototype or executable code provided on the Competition Website. The Competition Data will contain private and public test sets. Which data belongs to which set will not be made available to Participants. </h5>\nb. An “Entry” is when a Participant has joined, signed up, or accepted the rules of a competition. Entry is required to make a Submission to a competition.</h5>\nc. A “Final Submission” is the Submission selected by the user, or automatically selected by Kaggle in the event not selected by the user, that is/are used for final placement on the competition leaderboard.</h5>\nd. A “Participant” or “Participant User” is an individual who participates in a competition by entering the competition and making a Submission.</h5>\ne. The “Private Leaderboard” is a ranked display of Participants’ Submission scores against the private test set. The Private Leaderboard determines the final standing in the competition.</h5>\nf. The “Public Leaderboard” is a ranked display of Participants’ Submission scores against a representative sample of the test data. This leaderboard is visible throughout the competition.</h5>\ng. A “Sponsor” is responsible for hosting the competition, which includes but is not limited to providing the data for the competition, determining winners, and enforcing competition rules.</h5>\nh. A “Submission” is anything provided by the Participant to the Sponsor to be evaluated for competition purposes and determine leaderboard position. A Submission may be made as a model, notebook, prediction file, or other format as determined by the Sponsor.</h5>\ni. A “Team” is one or more Participants participating together in a Kaggle competition, by officially merging together as a Team within the competition platform.</h5>\n\n  [1]: https://www.treasury.gov/resource-center/sanctions/Programs/Pages/Programs.aspx\n  [2]: http://www.kaggle.com/terms\n  [3]: http://www.opensource.org\n  [4]: http://www.opensource.org\n  [5]: https://www.kaggle.com/WinningModelDocumentationGuidelines\n  [6]: http://www.kaggle.com/privacy\n  [7]: http://www.kaggle.com/contact\n",
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      "content": "Participants are expected to submit the following:\n\n* **Round 1 Submission** : A solution.csv file containing predicted race outcomes (lap time in seconds for each rider) submitted via Kaggle by the Round 1 deadline (06/14/2025, 10:00 PM IST). Maximum 3 submissions allowed per team, with the best submission automatically selected for evaluation. 📤\n* **Jupyter Notebook** : A fully reproducible Jupyter Notebook detailing your analysis, including Exploratory Data Analysis (EDA), feature engineering, and model development, submitted alongside the solution.csv. 📓\n* **Round 2 Presentation** : A PowerPoint (PPT) presentation with exactly 10 slides (including title and thank you slides), submitted via a Google Form link 30 minutes before the scheduled presentation time on 06/15/2025. Each team will present for up to 12 minutes, covering their MotoGP analytics model and answering judges’ questions.📊\n",
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      "name": "Success Criteria",
      "content": "Your submission will be evaluated based on the following criteria:\n\n* **Accuracy of Predictions** : How well your model predicts MotoGP race outcomes, measured by a 50-50 combination of public and private leaderboard scores on Kaggle. 📈\n* **Understanding of the Problem Statement** : Demonstrated grasp of the MotoGP racing dynamics and the challenges outlined in the problem statement. 🧠\n* **Type of Solution Used** : Appropriateness and innovation of the modeling techniques applied (e.g., regression, ensemble methods). 🛠️\n* **Modeling Techniques and Justification** : Quality of the modeling approach, including feature engineering, and the rationale behind your choices. ⚙️\n* **Insights Generated** : Relevance and depth of insights into racing dynamics derived from your analysis. 💡\n* **Presentation Quality** : Clarity, structure, design, and delivery of your Round 2 presentation, ensuring effective communication of your findings. 🎤",
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      "name": "Code Requirements",
      "content": "Submissions must be made through Jupyter Notebooks on Kaggle. To enable the \"Submit\" button after a commit, the following conditions must be met:\n\n* **CPU Notebook < 12 hours run-time** \n* **GPU Notebook < 12 hours run-time** \n\nAll work must be fully reproducible by the contest organisers. Offline pretraining (on external computers) is allowed; just ensure to document your process so we can reproduce it if you win.\n\n**Language**: Kaggle notebooks allow you to write code in Python and R, but participants can virtually code in any language other than that (if they are that brave). All that matters is the submission file that the participants have to upload.\n\nParticipants are required to submit their solutions in a solution.csv file format directly on the Kaggle platform or through a notebook. Ensure the submission adheres to the specified format and includes all necessary predictions or analyses.\n\nBy following these steps meticulously, participants can uncover hidden insights, refine their models, and ultimately contribute to the advancement of predictive modeling in motorsports. 🚀\n",
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      "name": "How to Submit?",
      "content": "## Kaggle Competition - Submission Instructions\n\n### Submission Format\nTo submit your predictions, you need to create a solution.csv file. This file should contain the following two columns:\n\n### ***Column 1: Unique ID***\n- The Unique ID column should contain the unique identifier for each rider. \n- Each row in this column corresponds to a unique row from the dataset.\n\n### ***Column 2: Lap_Time_Seconds***\n- The second column must contain the predicted lap time in seconds for each rider.\nPredict the lap time against ALL unique ids in the test set.\n\n**The target variable is Lap_Time_Seconds.**\n\n###File Structure :\n\nTo understand the structure of the submission file required for this competition, please refer to the sample_submission.csv provided in the dataset description. This file serves as a crucial reference for participants to grasp the expected format and content for submitting their predictions.\n\nThe sample_submission.csv file typically showcases the exact layout and formatting required for submitting predictions. It outlines the columns participants need to include. By examining this sample submission, participants can ensure their submissions adhere to the specified format and are compatible with the evaluation criteria set for the competition.\n\n### **Submitting Your File**\n\nOnce you have created your solution.csv file, follow these steps to submit it:\n\n1. Go to the competition’s submission page.\n2. Click the Submit Predictions button.\n3. Upload your solution.csv file by clicking on the Choose File or Browse button.\n4. Click the Submit button to finalise your submission.\n",
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      "name": "Timeline",
      "content": "Participants are required to submit their predictions according to the timeline given below:\n\n- **Start Date**: 14/06/2025\n- **Start Time**: 10:00 AM IST (04:30 AM UTC)\n- **End Date**: 06/14/2025\n- **End Time**: 10:00 PM IST (04:30 PM UTC)\n",
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    {
      "name": "About Us",
      "content": "![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F21861189%2Fb398582ee7e62642fa4697823fb1e928%2FScreenshot%202025-06-10%20225319.png?generation=1749576231339903&alt=media)\n\n## IEEE MUJ Computer Society\n“*Serving computing at its best with inclusion and diversity*” is the prime motto of the IEEE Computer Society. This society was created keeping in mind IEEE’s continued commitment to providing options at best. The IEEE Computer Society is driven by the central goals of equity, diversity, inclusion, and yearn to serve computing at its perfection.\n\nWith an intent to expand the IEEE’s reach and learnings, this society was started a year back in early 2020. Since then, society has tried every possible course of action by conducting diverse events such as webinars, competitions, workshops, and mentorship programs to set a goal for the young achievers. The members of IEEE CS have been skilled and earned minimal expertise in roughly all possible sub-sections of CS via our accelerator program. The senior student mentors steer them on each stage they take and deliver them with the professional material for further reference.\n\nWe aim to proactively support diversity and inclusion by being the premier source for information, inspiration, and collaboration in computer science and engineering. Connecting members on campus, this IEEE Computer Society empowers the students who wish to advance in technology by delivering tools at all stages of their professional careers.\n\n“*Computer science is the operating system for all innovations*.” At IEEE CS, we look at it similarly, trying to make a better world by working as a team.\n\nFollow us on social media for updates and announcements:👇\n[Instagram](https://www.instagram.com/ieee_csmuj/)\n[X formerly Twitter](https://x.com/ieeecsmuj)\n[LinkedIn](https://www.linkedin.com/company/ieee-cs-muj/mycompany/)\n[Medium](https://medium.com/@ieeecs)\n[WhatsApp](https://chat.whatsapp.com/Luru0TiclKY30jCwlNSf3r)\n\nFor any inquiries or clarifications, please feel free to contact us on the WhatsApp group. If you haven't been added to the group, please contact us through any of the given social media platforms.\n",
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      "name": "Communication",
      "content": "###Staying Connected Throughout Burnout 2025 📢\n* **Registration & Initial Contact** : Participants must register via the Unstop platform. Upon successful registration, you’ll be added to the official WhatsApp group for Burnout 2025. This group will be your primary hub for all updates, announcements, and discussions. 📱\n* **WhatsApp Group** : The WhatsApp group will keep you engaged throughout the event, providing significant competition-related updates, such as the private Kaggle competition link, problem statement releases, and schedule reminders. It’s also the place to ask questions, clear doubts, and seek technical support from the organising team. 💬\n* **Support Availability** : The organising team will be available on WhatsApp for the entire 12-hour duration of Round 1 (06/14/2025, 10:00 AM to 10:00 PM IST) to offer guidance and resolve queries. For Round 2, presentation slots and additional instructions will be shared via the group by 10:00 AM on 06/15/2025. 🕒\n* **Winners Announcement** : Results will be declared on our official social media platform (@ieee_csmuj) and the WhatsApp group shortly after the judging process concludes on 06/15/2025. Stay tuned to celebrate the champions! 🏆\n* **Contact for Queries** : For any additional clarifications, reach out to the organizing team directly: **Aarush Dayal (+918920393074)** or **Tejas Bhadauria (+919044765966)**. 📞",
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    {
      "name": "FAQs",
      "content": "##Frequently Asked Questions ❓\n\n**What is the team size for Burnout 2025?**\nTeams can have 1-2 members. You can compete solo or with a partner—your choice! 👥\n\n**Is there a participation fee?**\nNo, participation in Burnout 2025 is completely free! 💸\n\n**What is the prize pool?**\nThe total prize pool is ₹15,000, with ₹7,000 for 1st place, ₹5,000 for 2nd place, and ₹3,000 for 3rd place. 🏅\n\n**Can I use external data for training my model?**\nYes, participants are allowed to use external data for training, as long as the target variable remains the same as specified in the problem statement. 📊\n\n**How many submissions are allowed in Round 1?**\nEach team can make a maximum of 3 submissions during the 12-hour Round 1. Your best submission will be automatically selected for evaluation. 📤\n\n**What happens if I submit late for Round 1?**\nLate submissions will not be considered. Ensure your solution.csv is submitted on Kaggle by 06/14/2025, 10:00 PM IST. ⏰\n\n**What are the technical requirements for participation?**\nYou’ll need a stable internet connection, a proper setup for Python/R (or your preferred language), and video conferencing capabilities for Round 2 presentations. Ensure your Kaggle notebook runtime is under 12 hours (CPU/GPU). 💻\n\n**What if I face technical issues during the competition?**\nReach out to the organizing team via the WhatsApp group for immediate support. We’ll be available throughout Round 1 to assist with technical queries. 🛠️\n\n**How will Round 2 presentations work?**\nTop teams from Round 1 will present on 06/15/2025 starting at 2:30 PM IST. You’ll need to submit a 10-slide PPT 30 minutes before your slot via a Google Form link and present for up to 12 minutes, including Q&A with judges. 🎤\n\n**What happens if plagiarism is detected?**\nPlagiarism or rule violations will result in immediate disqualification. Ensure your work is original and adheres to the guidelines. 🚫\n",
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