Aaron Cleavin
Elder Member
All
I am in the process (well advanced) of building a very generic ASL player ratings engine based on the GLICKO Methodology
and covering both friendly and tournament play.
The GLICKO methodology is an improvement over the original ELO (Chess Ratings system)
It is designed to take account not only of the ratings difference of players when computing Rating changes but also the deviation (Volatility) of a players rating.
It is designed for computation of rating over a period rather than game by game (I have chosen 2 month periods as per the papers recommendations).
The focus initially is on building the engine and getting a sizable of data ingested and validated to fairly rigorous standards.
Every game recorded must have
Playing Date
Attacking player
Defending Player
Scenario Code
Result (Attacker wins of loses (W/L))
GameType (Tournament/Friendly)
TournamentCode (If a Tournament Game)
Methods of submitting tournament games going forward are under consideration, whether only TD's or players as well can submitt tourney results is very much TBD.
No three player games or draws are supported
Each Player must have a Nationality
Each Scenario must have 1-2 Attacking side, 1-2 Defending Sides, 1-2 Designers, A publication, a code , a name
The core db objects are
Publisher, Publication, Nationality, Person, Scenario, Game, Gametype, Tournament, Rating
Once this initial seed is done, work will commence on the Web interface to the system. ultimately it will likely be hosted on AWS (Amazon Web Services)
Security privacy and respect for others ways of looking at things, catering fro as many people as possible with divergent view on the functionality and usefulness of such and engine
will all be core values.
I have received an large number of offers of assistance on this undertaking and once the seed is complete (April 30th 2019) I will be really actively engaging on these offers.
Status and detail reports to follow
What I have covered here is very much just the top layer I can assure though that the db and engine design and consistency checking is very much at a professional level, I have put about 100 hours into this so far and it is much further along than I had expected.
For those interested the Core stack is
PostgreSQL : db , SQL, PL/pgSQL
Web interface: Python/Django
A whole lot of Excel for Data Cleansing Seeding and validation.
I am in the process (well advanced) of building a very generic ASL player ratings engine based on the GLICKO Methodology
and covering both friendly and tournament play.
The GLICKO methodology is an improvement over the original ELO (Chess Ratings system)
It is designed to take account not only of the ratings difference of players when computing Rating changes but also the deviation (Volatility) of a players rating.
It is designed for computation of rating over a period rather than game by game (I have chosen 2 month periods as per the papers recommendations).
The focus initially is on building the engine and getting a sizable of data ingested and validated to fairly rigorous standards.
Every game recorded must have
Playing Date
Attacking player
Defending Player
Scenario Code
Result (Attacker wins of loses (W/L))
GameType (Tournament/Friendly)
TournamentCode (If a Tournament Game)
Methods of submitting tournament games going forward are under consideration, whether only TD's or players as well can submitt tourney results is very much TBD.
No three player games or draws are supported
Each Player must have a Nationality
Each Scenario must have 1-2 Attacking side, 1-2 Defending Sides, 1-2 Designers, A publication, a code , a name
The core db objects are
Publisher, Publication, Nationality, Person, Scenario, Game, Gametype, Tournament, Rating
Once this initial seed is done, work will commence on the Web interface to the system. ultimately it will likely be hosted on AWS (Amazon Web Services)
Security privacy and respect for others ways of looking at things, catering fro as many people as possible with divergent view on the functionality and usefulness of such and engine
will all be core values.
I have received an large number of offers of assistance on this undertaking and once the seed is complete (April 30th 2019) I will be really actively engaging on these offers.
Status and detail reports to follow
What I have covered here is very much just the top layer I can assure though that the db and engine design and consistency checking is very much at a professional level, I have put about 100 hours into this so far and it is much further along than I had expected.
For those interested the Core stack is
PostgreSQL : db , SQL, PL/pgSQL
Web interface: Python/Django
A whole lot of Excel for Data Cleansing Seeding and validation.