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Tracks

Below is a list of all of the tracks that I have developed, roughly grouped by style, and defined with some metrics. Stylistic groupings are something that I'm constantly tweaking but this represents my current thinking. For consistence, I've standardized the name of all tracks based on their locations (city/country). Tracks themselves and the FIA have been inconsistent over the years about what a track / grand prix is called.

Many tracks have changed over the years. The years that this track represents and Grand Prix run on that layout are noted.

If you are interested in a detailed description of how I build tracks I wrote three posts on my blog describing my process:

  1. Preparing to Build a New Track
  2. Turning Research Into a New Track
  3. Testing, Testing, Testing A New Track

Key: L = length, 3w = 3-wide, C = corners, L/C = length / corner

 
Red Tracks
  Location 1st Year L 3w C L/C Score Front Back Fast Slow Sample
  Mogyoród, Hungary 2003 63 38% 9 7.0 -1.75 5.1 0.4 4.0 -2.7 4
  Imola, Italy 1995 74 24% 9 8.2 -1.39 0 0 -8.8 -1.3 1
  Indianapolis, USA 2000 61 67% 9 6.8 -1.32 3.4 -2.3 1.4 -3.2 4
  Barcelona, Spain 2007 60 40% 8 7.5 -1.28 1.4 -1.6 3.7 -2.7 6
  Nürburg, Germany 2002 74 31% 8 9.3 -1.27 3.3 -1.9 5.3 -0.8 11
  Singapore 2008 73 21% 11 6.6 -1.03 4.1 0.4 1.2 0.1 6
 
Yellow Tracks
  Location 1st Year L 3w C L/C Score Front Back Fast Slow Sample
  Francorchamps, Belgium 2007 97 61% 9 10.8 -0.88 4.4 -0.8 1.3 -2.1 10
  Francorchamps, Belgium 1985 97 60% 9 10.8 -- 5.0 0.0 8.7 0.7 1
  Monte Carlo 1986 51 45% 7 7.3 -0.82 -2.4 -5.0 5.1 6.7 6
  Silverstone, UK 1997 74 35% 8 9.3 -0.67 4.5 0.8 7.8 0.0 3
  São Paulo, Brazil 1990 67 46% 8 8.4 -0.60 1.8 -1.2 4.6 1.3 7
  Greater Noida, India 2011 73 62% 9 8.1 -0.46 0.0 0.0 0.0 0.0 0
  Sakhir, Bahrain 2004 80 51% 8 10.0 -.044 4.6 -3.0 5.4 -1.7 4
  Estoril, Portugal 1984 65 55% 7 9.3 -0.35 3.7 2.0 2.1 3.4 4
  Suzuka, Japan 2003 83 18% 8 10.4 -0.28 1.3 -0.3 4.0 -2.6 5
  Montreal, Canada 1996 65 65% 7 9.3 -0.26 3.6 1.5 3.8 2.8 9
 
Green Tracks
  Location 1st Year L 3w C L/C Score Front Back Fast Slow Sample
  Istanbul, Turkey 2005 76 47% 8 9.5 -0.17 3.3 -1.6 -4.4 -1.4 8
  Melbourne, Australia 1996 76 42% 8 9.5 -0.06 0.8 -0.1 0.5 -0.7 9
  Silverstone, UK 2011 84 55% 9 9.3 0.00 4.3 0.6 1.1 -3.6 3
  Silverstone, UK 2010 84 55% 9 9.3 -- 0.0 0.0 0.0 0.0 0
  Spielberg, Austria 1997 63 38% 7 9.0 0.02 3.2 1.5 0.0 -1.4 12
  Mexico City 2015 63 71% 8 7.9 0.14 -0.8 -0.5 -0.8 2.3 3
  Yeongam, Korea 2010 82 48% 8 10.3 0.20 1.2 1.4 3.2 -1.1 5
 
Blue Tracks
  Location 1st Year L 3w C L/C Score Front Back Fast Slow Sample
  Austin, US 2012 80 79% 9 8.9 0.30 0.4 0.7 1.7 0.2 7
  Oyama, Japan 1976 60 75% 5 12.0 0.30 0.5 0.0 -1.3 -0.9 8
  Abu Dhabi, UAE 2009 80 65% 8 10.0 0.36 1.5 -0.5 3.4 3.0 6
  Valencia, Spain 2008 77 31% 8 9.6 0.42 1.3 1.8 0.0 -0.4 4
  Hockenheim, Germany 2002 68 75% 7 9.7 0.50 0.5 0.0 -1.3 0.9 6
  Monza, Italy 2000 81 56% 6 13.5 0.85 1.7 0.1 4.0 0.7 4
 
Purple Tracks
  Location 1st Year L 3w C L/C Score Front Back Fast Slow Sample
  Baku, Azerbaijan 2016 86 70% 10 8.6 1.18 -1.1 -0.4 -1.6 3.2 7
  Sepang, Malaysia 1999 82 59% 8 10.3 1.28 -0.9 1.4 -6.5 2.5 5
  Sepang, Malaysia 2016 82 59% 8 10.3 -- -0.8 -5.5 0.0 0.0 1
  Castellet, France 1971 83 71% 7 11.9 1.62 -2.4 -2.2 -0.9 1.2 4
  Francorchamps, Belgium 1983 97 60% 9 10.8 1.68 1.3 -4.0 -8.2 0.0 1
  Sochi, Russia 2014 83 100% 8 10.4 1.70 0.3 1.3 -4.3 2.1 1
  Shanghai, China 2004 80 78% 7 11.4 1.84 -5.3 1.8 0.0 4.4 1
 
Medians
  L 3w C L/C Front Back Fast Slow Sample
  Median Track 76 55% 8 9.5 1.4 0.0 1.1 0.0

Track Measurements:
None of these measures means a lot by themselves, but together I think they provide a decent picture of what kind of track you are looking at. Note that when I have fewer than 4 races with result data, I lean most on the track profile. When I have 10 or more races of results data I lean most on results data. In between, I mix the two.

  • Track Profile
    • length: total spaces the shortest way around the track. By itself this is probably only a decent indication of how long it will take to play on the track. On a track-by-track basis, one space converts to about 0.07 km, 0.04 miles, or 76 yards.
    • 3-wide: percentage of the track that is 3-wide as opposed to 2-wide. Less 3-wide track will generally makes it harder to pass.
    • corners: the number of corners. Not all corners are created equal, but generally more corners will demand more wear.
    • length/corners: length divided by corners. A very good indicated of how tight a track is. "Tight" meaning that a track generally packs more corners into less space which typically makes for a particular kind of track.
    • medium straights: medium straights are defined as being 10 or 15 spaces long. Medium straights will likely get a car to its top speed for at least a turn.
    • long straights: long straights are defined as being 16 or more spaces long. Cars can spend multiple turns at top speed on a long straight.
  • Score
    • A track's score looks at a combination of the track profile and results data depending on how big my sample size is. A negative score means that the track encourages playing from the front. These scores are adjusted such that a -1.00 track has shown that it is 1 standard deviation more beneficial to running from the front.
    • Because CFR tends to generically encourage racing from the front, the Green tracks actually slightly encourage racing from the front. By current data Austin and Oyama are the closest to being completely balanced between front and back strategies.
    • At sample size 10, the score is based completely on results data. At sample size 0, the score is based completely on track profile data. AT sample size 4 the score is 40% results data and 60% track profile.
    • The 1985 Francorchamps and 2010 Silverstone tracks are so similar to other versions of the same tracks, that I do not give them unique scores. Until I have more results data, I will assume that they will end up with the same score as their similar cousin.
  • Results Data
    • Front & Back: Average number of points scored by someone starting the race in the first 2 rows or last 2 rows of the grid as cmopared to the average points scored by a car starting in the middle 2 rows of the starting grid. So a car starting in the front 2 rows at Valencia has scored on average 1.3 more points than the cars who started in the middle 2 lanes.
    • Fast & Slow: Average number of points scored by someone with a 100 or 120 start speed (fast) or 20 start speed (slow) as compared to the average number of points scored by a car with a 60 start speed. So cars starting Abu Dhabi with a 20 start speed have so far scored 3 more points than cars starting with a 60 start speed.
    • Sample: Number of races where I have qualifying data. For most tracks I have less data involving start speeds.

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