I am designing a data capture method for a client for inplay sporting events and he wants to record the odds movements for later analysis in Excel once every half second. I want to get this right so that it's easy to use the data down the line for analysis in other packages.
A bit more background and assumptions.
- Each event can have between 4 - 40 contenders (c)
- Each event has 10 variables that apply equally to all contenders (e)
- Each contender has 20 variables of same heading/type with values unique to contender (i)
In essence I need to choose between
- 1. Having 1 timeframe on 1 row, so each timeframe capture has
Columns required = e+max(c)i = 810
Rows required = 1
Good: Easy to manipulate, data on one row, 1 row describes all contenders in event per row.
Bad: Huge number of columns, lots of blank column data if c is less than max(c), hard to search names across multiple columns
- 2. Having 1 timeframe on multiple rows, so each timeframe has
Columns required = e+i =30
Rows required = c
Good: Less columns, easy to search/filter as all names in the same column
Bad: Timeframes in different rows for different contenders
Does it matter? Is it easy for packages to handle data in both forms? My client doesn't know the answer but wants the best solution! I'm tending towards 2. as it's much easier to manage and search in database terms but not sure about preparation for time series analysis? Can anyone one with experience offer some advice?