Examples
Examples
Try the starting example
- Player rating
- 1600
- Opponent rating
- 1800
- Supplied base-10 logistic rating scale
- 400
- Games for expected-point scenario
- 10
- Player expected fraction of one point per game
- 0.240253
- Opponent expected fraction of one point per game
- 0.759747
- Player expected points across supplied games
- 2.402531
- Player rating minus opponent rating
- -200
Try another scenario
- Player rating
- 1600
- Opponent rating
- 1600
- Supplied base-10 logistic rating scale
- 400
- Games for expected-point scenario
- 10
- Player expected fraction of one point per game
- 0.5
- Opponent expected fraction of one point per game
- 0.5
- Player expected points across supplied games
- 5
- Player rating minus opponent rating
- 0
Calculation method
Calculation method
Player expected fraction of one point per game
1/(1+10^((opponent−player)/scale)).
Opponent expected fraction of one point per game
One minus player score expectation.
Player expected points across supplied games
Game count×expected fraction; linear expectation does not determine win/draw/loss probabilities separately.
Player rating minus opponent rating
Supplied player−opponent rating.
Symbols and units
- a
- Player rating
- b
- Opponent rating
- c
- Supplied base-10 logistic rating scale
- d
- Games for expected-point scenario
Use the units shown. A list keeps the order in which you enter its values. The symbol ^ means “raised to the power of”.
Assumptions & limits
Assumptions & limits
- A smooth Elo-style logistic expected-SCORE model at a supplied scale, not a calibrated win probability or official FIDE rating-table calculation. A score expectation does not identify separate win and draw chances.
Are these inputs private?
These calculations run in your browser. A shared link contains the values you choose to share. Only questions submitted to the separate AI finder are sent to OpenAI.
Further reading
Background reading; this does not imply endorsement or independent review of SumFizz.