SQL Exercise: Find those referees who managed most of the match
52. From the following tables, write a SQL query to find those referees who managed most of the matches. Return referee name, country name and number of matches.
Sample table: match_mast
match_no | play_stage | play_date | results | decided_by | goal_score | venue_id | referee_id | audence | plr_of_match | stop1_sec | stop2_sec
----------+------------+------------+---------+------------+------------+----------+------------+---------+--------------+-----------+-----------
1 | G | 2016-06-11 | WIN | N | 2-1 | 20008 | 70007 | 75113 | 160154 | 131 | 242
2 | G | 2016-06-11 | WIN | N | 0-1 | 20002 | 70012 | 33805 | 160476 | 61 | 182
3 | G | 2016-06-11 | WIN | N | 2-1 | 20001 | 70017 | 37831 | 160540 | 64 | 268
4 | G | 2016-06-12 | DRAW | N | 1-1 | 20005 | 70011 | 62343 | 160128 | 0 | 185
5 | G | 2016-06-12 | WIN | N | 0-1 | 20007 | 70006 | 43842 | 160084 | 125 | 325
6 | G | 2016-06-12 | WIN | N | 1-0 | 20006 | 70014 | 33742 | 160291 | 2 | 246
7 | G | 2016-06-13 | WIN | N | 2-0 | 20003 | 70002 | 43035 | 160176 | 89 | 188
8 | G | 2016-06-13 | WIN | N | 1-0 | 20010 | 70009 | 29400 | 160429 | 360 | 182
9 | G | 2016-06-13 | DRAW | N | 1-1 | 20008 | 70010 | 73419 | 160335 | 67 | 194
10 | G | 2016-06-14 | WIN | N | 0-2 | 20004 | 70005 | 55408 | 160244 | 63 | 189
11 | G | 2016-06-14 | WIN | N | 0-2 | 20001 | 70018 | 34424 | 160197 | 61 | 305
12 | G | 2016-06-15 | DRAW | N | 1-1 | 20009 | 70004 | 38742 | 160320 | 15 | 284
13 | G | 2016-06-15 | WIN | N | 1-2 | 20003 | 70001 | 38989 | 160405 | 62 | 189
14 | G | 2016-06-15 | DRAW | N | 1-1 | 20007 | 70015 | 43576 | 160477 | 74 | 206
15 | G | 2016-06-16 | WIN | N | 2-0 | 20005 | 70013 | 63670 | 160154 | 71 | 374
16 | G | 2016-06-16 | WIN | N | 2-1 | 20002 | 70003 | 34033 | 160540 | 62 | 212
17 | G | 2016-06-16 | WIN | N | 0-2 | 20004 | 70016 | 51043 | 160262 | 7 | 411
18 | G | 2016-06-17 | DRAW | N | 0-0 | 20008 | 70008 | 73648 | 160165 | 6 | 208
19 | G | 2016-06-17 | WIN | N | 1-0 | 20010 | 70007 | 29600 | 160248 | 2 | 264
20 | G | 2016-06-17 | DRAW | N | 2-2 | 20009 | 70005 | 38376 | 160086 | 71 | 280
21 | G | 2016-06-18 | WIN | N | 3-0 | 20006 | 70010 | 33409 | 160429 | 84 | 120
22 | G | 2016-06-18 | WIN | N | 3-0 | 20001 | 70004 | 39493 | 160064 | 11 | 180
23 | G | 2016-06-18 | DRAW | N | 1-1 | 20005 | 70015 | 60842 | 160230 | 61 | 280
24 | G | 2016-06-19 | DRAW | N | 0-0 | 20007 | 70011 | 44291 | 160314 | 3 | 200
25 | G | 2016-06-20 | WIN | N | 0-1 | 20004 | 70016 | 49752 | 160005 | 125 | 328
26 | G | 2016-06-20 | DRAW | N | 0-0 | 20003 | 70001 | 45616 | 160463 | 60 | 122
27 | G | 2016-06-21 | WIN | N | 0-3 | 20010 | 70006 | 28840 | 160544 | 62 | 119
28 | G | 2016-06-21 | DRAW | N | 0-0 | 20009 | 70012 | 39051 | 160392 | 62 | 301
29 | G | 2016-06-21 | WIN | N | 0-1 | 20005 | 70017 | 58874 | 160520 | 29 | 244
30 | G | 2016-06-21 | WIN | N | 0-1 | 20007 | 70018 | 44125 | 160177 | 21 | 195
31 | G | 2016-06-22 | WIN | N | 0-2 | 20002 | 70013 | 32836 | 160504 | 60 | 300
32 | G | 2016-06-22 | WIN | N | 2-1 | 20001 | 70008 | 37245 | 160085 | 70 | 282
33 | G | 2016-06-22 | WIN | N | 2-1 | 20008 | 70009 | 68714 | 160220 | 7 | 244
34 | G | 2016-06-22 | DRAW | N | 3-3 | 20004 | 70002 | 55514 | 160322 | 70 | 185
35 | G | 2016-06-23 | WIN | N | 0-1 | 20003 | 70014 | 44268 | 160333 | 79 | 221
36 | G | 2016-06-23 | WIN | N | 0-1 | 20006 | 70003 | 34011 | 160062 | 63 | 195
37 | R | 2016-06-25 | WIN | P | 1-1 | 20009 | 70005 | 38842 | 160476 | 126 | 243
38 | R | 2016-06-25 | WIN | N | 1-0 | 20007 | 70002 | 44342 | 160547 | 5 | 245
39 | R | 2016-06-26 | WIN | N | 0-1 | 20002 | 70012 | 33523 | 160316 | 61 | 198
40 | R | 2016-06-26 | WIN | N | 2-1 | 20004 | 70011 | 56279 | 160160 | 238 | 203
41 | R | 2016-06-26 | WIN | N | 3-0 | 20003 | 70009 | 44312 | 160173 | 62 | 124
42 | R | 2016-06-27 | WIN | N | 0-4 | 20010 | 70010 | 28921 | 160062 | 3 | 133
43 | R | 2016-06-27 | WIN | N | 2-0 | 20008 | 70004 | 76165 | 160235 | 63 | 243
44 | R | 2016-06-28 | WIN | N | 1-2 | 20006 | 70001 | 33901 | 160217 | 5 | 199
45 | Q | 2016-07-01 | WIN | P | 1-1 | 20005 | 70003 | 62940 | 160316 | 58 | 181
46 | Q | 2016-07-02 | WIN | N | 3-1 | 20003 | 70001 | 45936 | 160550 | 14 | 182
47 | Q | 2016-07-03 | WIN | P | 1-1 | 20001 | 70007 | 38764 | 160163 | 63 | 181
48 | Q | 2016-07-04 | WIN | N | 5-2 | 20008 | 70008 | 76833 | 160159 | 16 | 125
49 | S | 2016-07-07 | WIN | N | 2-0 | 20004 | 70006 | 55679 | 160322 | 2 | 181
50 | S | 2016-07-08 | WIN | N | 2-0 | 20005 | 70011 | 64078 | 160160 | 126 | 275
51 | F | 2016-07-11 | WIN | N | 1-0 | 20008 | 70005 | 75868 | 160307 | 161 | 181
Sample table: referee_mast
referee_id | referee_name | country_id
------------+-------------------------+------------
70001 | Damir Skomina | 1225
70002 | Martin Atkinson | 1206
70003 | Felix Brych | 1208
70004 | Cuneyt Cakir | 1222
70005 | Mark Clattenburg | 1206
70006 | Jonas Eriksson | 1220
70007 | Viktor Kassai | 1209
70008 | Bjorn Kuipers | 1226
70009 | Szymon Marciniak | 1213
70010 | Milorad Mazic | 1227
70011 | Nicola Rizzoli | 1211
70012 | Carlos Velasco Carballo | 1219
70013 | William Collum | 1228
70014 | Ovidiu Hategan | 1216
70015 | Sergei Karasev | 1217
70016 | Pavel Kralovec | 1205
70017 | Svein Oddvar Moen | 1229
70018 | Clement Turpin | 1207
Sample table: soccer_country
country_id | country_abbr | country_name
------------+--------------+---------------------
1201 | ALB | Albania
1202 | AUT | Austria
1203 | BEL | Belgium
1204 | CRO | Croatia
1205 | CZE | Czech Republic
1206 | ENG | England
1207 | FRA | France
1208 | GER | Germany
1209 | HUN | Hungary
1210 | ISL | Iceland
1211 | ITA | Italy
1212 | NIR | Northern Ireland
1213 | POL | Poland
1214 | POR | Portugal
1215 | IRL | Republic of Ireland
1216 | ROU | Romania
1217 | RUS | Russia
1218 | SVK | Slovakia
1219 | ESP | Spain
1220 | SWE | Sweden
1221 | SUI | Switzerland
1222 | TUR | Turkey
1223 | UKR | Ukraine
1224 | WAL | Wales
1225 | SLO | Slovenia
1226 | NED | Netherlands
1227 | SRB | Serbia
1228 | SCO | Scotland
1229 | NOR | Norway
Sample Solution:
SQL Code:
-- Selecting the referee name, country name, and count of matches for each referee in each country
SELECT
c.referee_name, -- Selecting the referee name
b.country_name, -- Selecting the country name
COUNT(a.match_no) -- Counting the number of matches for each referee in each country
FROM
match_mast a -- Specifying the match_mast table with alias 'a'
JOIN
referee_mast c ON a.referee_id = c.referee_id -- Joining the match_mast table with the referee_mast table based on referee ID
JOIN
soccer_country b ON c.country_id = b.country_id -- Joining the referee_mast table with the soccer_country table based on country ID
GROUP BY
c.referee_name, -- Grouping the results by referee name
b.country_name -- Grouping the results by country name
HAVING
COUNT(a.match_no) = ( -- Filtering the results to match the maximum count of matches for a referee in a country
SELECT
MAX(mm) -- Selecting the maximum count of matches
FROM
( -- Subquery to calculate the count of matches for each referee in each country
SELECT
COUNT(a.match_no) AS mm -- Counting the number of matches for each referee in each country
FROM
match_mast a -- Specifying the match_mast table with alias 'a'
JOIN
referee_mast c ON a.referee_id = c.referee_id -- Joining the match_mast table with the referee_mast table based on referee ID
JOIN
soccer_country b ON c.country_id = b.country_id -- Joining the referee_mast table with the soccer_country table based on country ID
GROUP BY
c.referee_name, -- Grouping the results by referee name
b.country_name -- Grouping the results by country name
) hh -- Alias for the subquery
);
Sample Output:
referee_name | country_name | count ------------------+--------------+------- Damir Skomina | Slovenia | 4 Mark Clattenburg | England | 4 Nicola Rizzoli | Italy | 4 (3 rows)
Code Explanation:
The provided query in SQL that retrieves information about referees and the countries they are associated with, as well as the number of matches they have officiated.
The JOIN clause in this query then joins the match_mast and referee_mast tables based on the referee_id column and joins the results with soccer_country tables based on the country_id column.
It then groups the data by referee_name and country_name and calculates the count of matches for each group.
The HAVING clause filters the results and only return the rows where the count of matches is equal to the maximum count of matches in the entire dataset.
Alternative Solution:
Using a Window Function:
-- Selecting the referee name, country name, and match count for the top-ranked referee in each country
SELECT
referee_name, -- Selecting the referee name
country_name, -- Selecting the country name
match_count -- Selecting the match count
FROM
( -- Subquery to generate ranked results based on match count
SELECT
c.referee_name, -- Selecting the referee name
b.country_name, -- Selecting the country name
COUNT(a.match_no) as match_count, -- Counting the number of matches for each referee in each country
RANK() OVER (ORDER BY COUNT(a.match_no) DESC) as rank -- Generating rank based on match count
FROM
match_mast a -- Specifying the match_mast table with alias 'a'
JOIN
referee_mast c ON a.referee_id = c.referee_id -- Joining the match_mast table with the referee_mast table based on referee ID
JOIN
soccer_country b ON c.country_id = b.country_id -- Joining the referee_mast table with the soccer_country table based on country ID
GROUP BY
c.referee_name, -- Grouping the results by referee name
b.country_name -- Grouping the results by country name
) ranked -- Alias for the subquery
-- Filtering the results to select the top-ranked referee in each country
WHERE
rank = 1;
Explanation:
This query uses a window function RANK() to assign a rank to each combination of referee and country based on the count of matches. It then selects the combination with rank 1, which corresponds to the highest match count.
Go to:
PREV : Find the referees managed the number of matches.
NEXT : Find the number of matches each referee managed.
Practice Online
Sample Database: soccer

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