Multiple counts and math operator in MySQL - mysql

Question

I have two tables, one contains the results of a game (which game played and number of games won), the second lists how many selections they have gotten right for a given game (i.e % correct).
I need to make a single query to calculate the percentage of times a user has won for each game. Each user may have played a different number of games.
I've tried to do this using COUNT, but if I group the count function to determine the number of times a user has player I can then not get the total number of times the user has won. See fiddle..
http://sqlfiddle.com/#!2/defc3/1
UPDATE result, games_played
SET result.precentage_correct =
(
**SELECT (COUNT(gp.user_id)/COUNT(gp.user_id)*100)**
FROM games_played as gp
WHERE result.user_id = gp.user_id
AND gp.winner != 'n'
AND gp.game = 1
GROUP BY gp.user_id
)
WHERE games_played.user_id = result.user_id
So, somehow I need to have two different COUNT functions with a math operator

Answer 1

You could simply combine two queries, one that selects only winning records, and another that selects all queries. Once you have these two counts, you can select from them to calculate the ratio.
SELECT user_id, 100*SUM(n_win)/SUM(n_total) AS pct_win FROM
(SELECT user_id, COUNT(user_id) AS n_win,
NULL AS n_total
FROM games_played
WHERE winner != 'n'
AND game = 1
GROUP BY user_id
UNION SELECT user_id, NULL AS n_win,
COUNT(user_id) AS n_total
FROM games_played
WHERE game = 1
GROUP BY user_id
) AS counts
GROUP BY counts.user_id;
Note that to combine the queries, one field of either n_win or n_total will be NULL in each subquery. The query will yield:
USER_ID PCT_WIN
1 50
2 66.6667
3 50
4 100
The union of the two subqueries will have two records for each user, one record for which n_win is known, the other record will have the value for n_total. For the first two users, it would look like
USER_ID N_WIN N_TOTAL
1 1 NULL
2 2 NULL
1 NULL 2
2 NULL 3
The outer query selects from that union the user_id and n_win / n_total grouped by user_id, thus yielding 50.0% and 66.6%. I am using SUM because it allows me to collect the non-NULL value for each column for each user.