Sunday, September 25, 2011

F1 2011 Singapore Qualifying - Sector Times and Speeds

Whilst FP2 is typically the session we can get a feel for long run stint times, and as a result, maybe some idea of race pace, the qualifying session is the first session for which we get official FIA timing sheets detailing sector times and speeds.

Here's a summary view over the sector times and speeds taken from the qualifying sessions:

How to read it: at first glance, this graphic might seem rather difficult to read, so here are some pointers. Each box compares two pieces of data for each of the 24 drivers (that is in each chart, each circle represents one of the 24 drivers). The data that we plot is taken from the set of best sector times and speeds achieved by each driver during qualifying. If you look down the diagonal that goes top left to bottom right, you will see a label - Sector1, Sector 2, and so on. That label defines the x-axis category along a row, and the y-axis gategory up and down the corresponding column. If we look at the second box along the top row, it this represents Sector 2 times along the x-axis and Sector 1 times on the y-axis. If we look at the third box down the rightmost column, it represents the trap speed on the x-axis and the Sector 3 time on the y-axis.

We can use this chart to get a feel for how speeds and sector times correlate over the track. (That is, the extent to which the fastest cars get the quickest times - which is not always the case...) If each got exactly the same time in each sector as it did in the first sector, then if we plotted the sector 1 times against the sector 2 or sector 3 times, the points would all lay along a diagonal line. If the sector time was a simple function of the speed (so if sectorTime = k x sectorSpeed), we would also get the points laying on a diagonal line. The extent to which points fall off the diagonal gives us an indication as to how much the cars vary in perfromance across each sector.

In the images shown it's not obvious which car corresponds to which circle (though we could at a push work it out from the timing sheets).

To try to make the graph a little easier to read, I experimented with adding a little colour, in this case corresponding to the teams.

Here we can see a little (but only a little!) more clearly how the teams are distributed in terms of performance. SO for example, we see the faint yellow symbols (Red Bull) have very quick sector times (sector1, sector2, sector3), but they are really quite slow according to the inter1 speed trap, middling on inter2 and speed trap speeds, and pretty fast at the finish.

To check our reading of the charts, we can sort the results according to sector time or speed trap by clicking on the sortable table column headers below:

If there are any other insights you think you can get from the above charts, please add them on the comments. If you have any ideas of charts you might one to look at in more detail, and how they might be improved to make them clearer to "read", please post suggestions (and maybe even R code?!;-) in the comments too:-)

PS Here's how the chart was generated (R code):

### @export "data-constants"

### @export "data-import"
gsqAPI = function(key,query,gid){ return( read.csv( paste( sep="", '', 'tqx=out:csv', '&tq=', curlEscape(query), '&key=', key, '&gid=', curlEscape(gid) ) ) ) }

qualidata=gsqAPI(sskey,'select *',gid='7')
qualidata=subset(qualidata,sector1 > 0 & sector2 > 0 & sector3 > 0)
pairs(qualidata[c(4,5,6,10,11,12,13)], col=qualidata$team)

What I think this sort of chart may be useful for is getting an at-a-glimpse overview of where the major differences in respective performance lay, under the assumption that those sectors may be the sectors that will make an actual difference to the race...

The question now is, how can we zoom in to any particular chart shown in the lattice grid above, and look at each point labeled with the corresponding driver's name...?

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