Jump Freighter Kill Statistics

I’ve been working with @Lockefox over the past few days to setup his Eve-Prosper zKillboard scraper on my Raspberry Pi LAMP instance that I have in my home lab in order to do some data analysis.


Let there be Database Rows

The only edits that I had to make to the project code were the database connection details in scraper.ini and a narrowing down of ship classes listed in toaster_shiplist.json. After getting the data into mySQL and importing the invTypes and mapSolarSystems tables from the static dump into my database, I could start to filter and sort the results.

Kicking off the scraper:

pi@charon ~/eve_prosper $ python zkb_scraper.py — startdate=2013-12-01
DB Connection:          GOOD
zKillboard connection:  GOOD
no crash log found.  Executing as normal
Parsed Capital Industrial Ship: [200, 29713239, 0, ‘2013-04-08’] sleep=20.0
Parsed Capital Industrial Ship: [290, 27468307, 1, ‘2012-12-30’] sleep=20.0

Here is the query to get Racial JFs and also include the solar system name and security value:

— Get Racial JFs
SELECT destruction_data.date, destruction_data.week, destruction_data.typeID, destruction_data.systemID, destruction_data.destroyed, invTypes.typeName, mapSolarSystems.solarSystemName, mapSolarSystems.security
FROM destruction_data
JOIN invTypes
ON (destruction_data.typeID = invTypes.typeID)
JOIN mapSolarSystems
ON (destruction_data.systemID = mapSolarSystems.solarsystemID)
WHERE destruction_data.typeID IN (28850, 28844, 28848, 28846)
ORDER BY destruction_data.date DESC


Out of 975 Jump Freighter kills covering 334 days, there is an average of 20 a week killed. It turns out that you are most likely to get caught in Lowsec in a Rhea.



When we look at kills by system, Purjola (0.5), a Highsec system in the Forge stands out as the system with the most losses at 54. Not surprisingly the Lowsec system of Sagain (0.4) comes in second, most likely due to the terrible kickout station that I have covered here.



More coming soon as I start to think of what types of statistics and trends I can pull out of the data. If you have something you would like me to look at, please leave a comment or tweet @K162space.