Difference between revisions of "1718t1is428T14/Proposal"

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Held annually since 1950, the FIA Formula One World Championship is a race series that garners a massive base of fans and spectators, and  has become one of the most coveted automotive events and spectator sports of all time. Each F1 championship, known as a "season", consist of approximately 20 races, each known as a "Grand Prix", held in circuits in different countries all over the world. The results of each race are tabulated in a points-based system to determine two annual Championship winners, one among drivers and one among constructors(teams).  
 
Held annually since 1950, the FIA Formula One World Championship is a race series that garners a massive base of fans and spectators, and  has become one of the most coveted automotive events and spectator sports of all time. Each F1 championship, known as a "season", consist of approximately 20 races, each known as a "Grand Prix", held in circuits in different countries all over the world. The results of each race are tabulated in a points-based system to determine two annual Championship winners, one among drivers and one among constructors(teams).  
  
 +
Objectives:
 
Our project aims to provide insights to F1 drivers and teams by generating comprehensive visual data representations, segmented by the various factors that affect victory in an F1 Grand Prix (based on historical data) to help teams generate more effective strategies to increase their likelihood of victory.
 
Our project aims to provide insights to F1 drivers and teams by generating comprehensive visual data representations, segmented by the various factors that affect victory in an F1 Grand Prix (based on historical data) to help teams generate more effective strategies to increase their likelihood of victory.
  
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Our project will be using the official dataset from Overwatch, available on [....] as well as specialized Overwatch tracking site such as Overbuff.com and Master Overwatch. As raw data downloading options are currently unavailable, our group has chosen to transcribe the data to our own Excel spreadsheet.  
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Our project will be using datasets from online sources which track and list fundamental information such as lap times and pit stop times, available on websites such as statsf1.com. We will also transcribe the data to our own Excel spreadsheets and process them to sieve out important information.  
  
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Our project will analyze the following attributes from the dataset:
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Our project will analyze the following attributes from the datasets:
  
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** Hero
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** Drivers
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** Pick rate
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** Grand Prix Locations each Season
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** Win rate
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** Lap times
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** Tie rate
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** Pit stop times
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** On fire
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** Pit stop strategies
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** Elims
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** Tyre strategies
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** Obj. Kills
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** Budgets
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** Obj Time
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** Constructors
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** Damage
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** Weather
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** Final results
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** Vehicle Breakdowns
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** Crashes
  
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Additionally, our project will also use another dataset for the combination of different heroes’ ultimates. In particular, this will be a  matrix that details the effectiveness of a hero’s ultimate when used together with another hero’s ultimate. Effectiveness is measured with the following ranges of value:
 
  
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Bad: counterproductive when 2 ultimates are played together
 
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Ineffective: ultimates that are of similar types or types that do not combine well
 
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Maybe: ultimates can combine to but not the best
 
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A bit: ultimates combine to give medium effects
 
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Defense: ultimates combine to give good effects
 
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Nice: ultimates combine efficiently to give very good effects
 
  
  
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Our approach to this problem is to first define a competitive player’s journey through a 2.5-month-long competitive season of Overwatch, then provide insights in each step of this journey to ensure the best possible performance. As the season begins, the player will participate in 10 ‘Placement Matches’ (PM). The player’s performance in these matches will determine his/her ‘Skill Ratings’ (SR), a value to denote player standings. Players are placed in different ‘Tiers’ based on SR as shown below (e.g. A player with SR between 1-1499 is placed in Bronze tier). Each post-PM competitive match thereafter causes the player’s SR to increase with each victory, or decrease with each loss, and the player’s Tier adjusts accordingly.
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Our approach to this problem is to first define a professional F1 driver's journey through an F1 season, which lasts for about 20 Grand Prix races. We will then create easily-understood visual data representations to link the above attributes to the victory rates of drivers and constructors, with the aim of allowing the audience to easily deduce the best strategies and other factors that is most likely to help them achieve victory in a race or in an entire season. This may be separated not only into specific sets of races (e.g. best strategy to win 1 race vs. best strategy to win an entire season), but also into specific locations (best strategy on Monaco Grand Prix circuit), budget availability, or specific weather conditions, among others. In addition, it may even include a combination of factors (best strategy to win a race in Monaco Grand Prix in wet weather, given a budget of approximately $100 million). The user of the final resulting program will be able to select the factors according to his current situation and/or the driver or constructor whose performance he is interested in assessing.
 +
 
 +
In addition, research will be done to supplement the best strategies and find out why they have historically led to the greatest number of victories. This will help the user to understand what leads to such victories, hence extending the purpose of our visualizations beyond mere data - they will also help the user to tailor the strategies to their own needs to reflect other factors which may not be included in our project, or discover new strategies based on the data that we have analyzed.
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It is especially important for a player to perform well in the PM because this is the best opportunity for a player to quickly obtain high SR, and therefore high standings. Post-PM victories contribute comparatively small amounts to a player’s SR, unless many victories are obtained, but this takes much more time. The exact Overwatch algorithm for SR calculation during PM is unknown, but it is speculated to be based on the player’s individual performance during the PM (as opposed to team performance). Some players lose all 10 matches but still receive a high Tier, such as Grandmaster, due to high individual performance. In this project, it is therefore assumed that only individual performance affects the SR a player obtains from the PM.
 
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This project will be separated into two sections. The first section will focus on the PM, To maximize a player’s individual performance in the PM, we will advise the most suitable heroes to select based on a player’s best skillsets and preferred playstyle.
 
  
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The second section of the project will focus on post-PM matches. In these matches, there are several factors affecting the SR gained, but the most dominant factor by far is whether the player’s team wins or loses. Therefore, maximizing team performance will be prioritized over individual performance. We have identified four main aspects that affect team performance, namely the player’s team composition, map-based strategies, individual heroes’ ultimate abilities, and the enemy team’s composition. Through analysis of data regarding these factors, we will maximize the chances of team victory by providing strategies highlighting the most effective hero combinations for the team.
 
  
  

Revision as of 02:07, 11 November 2017



Title2.jpg

Formula One, better known as F1, is the highest class of racing for open-wheel automobiles that is sanctioned by the Fédération Internationale de l'Automobile (FIA),the governing body of motor sports. Open-wheel cars are cars with wheels outside of the main body, of which F1 cars are the most well-known. With their powerful engines and lightweight, aerodynamic bodies, F1 cars are capable of speeds of up to 375 km/h and are one of the fastest in the world in terms of acceleration, cornering, and overall lap times around a road circuit.

Held annually since 1950, the FIA Formula One World Championship is a race series that garners a massive base of fans and spectators, and has become one of the most coveted automotive events and spectator sports of all time. Each F1 championship, known as a "season", consist of approximately 20 races, each known as a "Grand Prix", held in circuits in different countries all over the world. The results of each race are tabulated in a points-based system to determine two annual Championship winners, one among drivers and one among constructors(teams).

Objectives: Our project aims to provide insights to F1 drivers and teams by generating comprehensive visual data representations, segmented by the various factors that affect victory in an F1 Grand Prix (based on historical data) to help teams generate more effective strategies to increase their likelihood of victory.



Title3.jpg

Our project will be using datasets from online sources which track and list fundamental information such as lap times and pit stop times, available on websites such as statsf1.com. We will also transcribe the data to our own Excel spreadsheets and process them to sieve out important information.

Our project will analyze the following attributes from the datasets:

    • Drivers
    • Grand Prix Locations each Season
    • Lap times
    • Pit stop times
    • Pit stop strategies
    • Tyre strategies
    • Budgets
    • Constructors
    • Weather
    • Final results
    • Vehicle Breakdowns
    • Crashes




Title4.jpg

Our approach to this problem is to first define a professional F1 driver's journey through an F1 season, which lasts for about 20 Grand Prix races. We will then create easily-understood visual data representations to link the above attributes to the victory rates of drivers and constructors, with the aim of allowing the audience to easily deduce the best strategies and other factors that is most likely to help them achieve victory in a race or in an entire season. This may be separated not only into specific sets of races (e.g. best strategy to win 1 race vs. best strategy to win an entire season), but also into specific locations (best strategy on Monaco Grand Prix circuit), budget availability, or specific weather conditions, among others. In addition, it may even include a combination of factors (best strategy to win a race in Monaco Grand Prix in wet weather, given a budget of approximately $100 million). The user of the final resulting program will be able to select the factors according to his current situation and/or the driver or constructor whose performance he is interested in assessing.

In addition, research will be done to supplement the best strategies and find out why they have historically led to the greatest number of victories. This will help the user to understand what leads to such victories, hence extending the purpose of our visualizations beyond mere data - they will also help the user to tailor the strategies to their own needs to reflect other factors which may not be included in our project, or discover new strategies based on the data that we have analyzed.



Tier ranking.png






Title5.jpg





Title6.jpg

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