SQL Exercise: Countries where assistant referees assist most matches
47. From the following table, write a SQL query to find the countries from where the assistant referees assist most of the matches. Return country name and number of matches.
Sample table: match_details
match_no | play_stage | team_id | win_lose | decided_by | goal_score | penalty_score | ass_ref | player_gk
----------+------------+---------+----------+------------+------------+---------------+---------+-----------
1 | G | 1207 | W | N | 2 | | 80016 | 160140
1 | G | 1216 | L | N | 1 | | 80020 | 160348
2 | G | 1201 | L | N | 0 | | 80003 | 160001
2 | G | 1221 | W | N | 1 | | 80023 | 160463
3 | G | 1224 | W | N | 2 | | 80031 | 160532
3 | G | 1218 | L | N | 1 | | 80025 | 160392
4 | G | 1206 | D | N | 1 | | 80008 | 160117
4 | G | 1217 | D | N | 1 | | 80019 | 160369
5 | G | 1222 | L | N | 0 | | 80011 | 160486
5 | G | 1204 | W | N | 1 | | 80022 | 160071
6 | G | 1213 | W | N | 1 | | 80036 | 160279
6 | G | 1212 | L | N | 0 | | 80029 | 160256
7 | G | 1208 | W | N | 2 | | 80014 | 160163
7 | G | 1223 | L | N | 0 | | 80006 | 160508
8 | G | 1219 | W | N | 1 | | 80018 | 160416
8 | G | 1205 | L | N | 0 | | 80012 | 160093
9 | G | 1215 | D | N | 1 | | 80017 | 160324
9 | G | 1220 | D | N | 1 | | 80010 | 160439
10 | G | 1203 | L | N | 0 | | 80004 | 160047
10 | G | 1211 | W | N | 2 | | 80007 | 160231
11 | G | 1202 | L | N | 0 | | 80026 | 160024
11 | G | 1209 | W | N | 2 | | 80028 | 160187
12 | G | 1214 | D | N | 1 | | 80009 | 160302
12 | G | 1210 | D | N | 1 | | 80015 | 160208
13 | G | 1217 | L | N | 1 | | 80001 | 160369
13 | G | 1218 | W | N | 2 | | 80002 | 160392
14 | G | 1216 | D | N | 1 | | 80030 | 160348
14 | G | 1221 | D | N | 1 | | 80032 | 160463
15 | G | 1207 | W | N | 2 | | 80033 | 160140
15 | G | 1201 | L | N | 0 | | 80027 | 160001
16 | G | 1206 | W | N | 2 | | 80005 | 160117
16 | G | 1224 | L | N | 1 | | 80013 | 160531
17 | G | 1223 | L | N | 0 | | 80035 | 160508
17 | G | 1212 | W | N | 2 | | 80034 | 160256
18 | G | 1208 | D | N | 0 | | 80021 | 160163
18 | G | 1213 | D | N | 0 | | 80024 | 160278
19 | G | 1211 | W | N | 1 | | 80016 | 160231
19 | G | 1220 | L | N | 0 | | 80020 | 160439
20 | G | 1205 | D | N | 2 | | 80004 | 160093
20 | G | 1204 | D | N | 2 | | 80007 | 160071
21 | G | 1219 | W | N | 3 | | 80017 | 160416
21 | G | 1222 | L | N | 0 | | 80010 | 160486
22 | G | 1203 | W | N | 3 | | 80009 | 160047
22 | G | 1215 | L | N | 0 | | 80015 | 160324
23 | G | 1210 | D | N | 1 | | 80030 | 160208
23 | G | 1209 | D | N | 1 | | 80032 | 160187
24 | G | 1214 | D | N | 0 | | 80008 | 160302
24 | G | 1202 | D | N | 0 | | 80019 | 160024
25 | G | 1216 | L | N | 0 | | 80035 | 160348
25 | G | 1201 | W | N | 1 | | 80034 | 160001
26 | G | 1221 | D | N | 0 | | 80001 | 160463
26 | G | 1207 | D | N | 0 | | 80002 | 160140
27 | G | 1217 | L | N | 0 | | 80011 | 160369
27 | G | 1224 | W | N | 3 | | 80022 | 160531
28 | G | 1218 | D | N | 0 | | 80003 | 160392
28 | G | 1206 | D | N | 0 | | 80023 | 160117
29 | G | 1223 | L | N | 0 | | 80031 | 160508
29 | G | 1213 | W | N | 1 | | 80025 | 160278
30 | G | 1212 | L | N | 0 | | 80026 | 160256
30 | G | 1208 | W | N | 1 | | 80028 | 160163
31 | G | 1205 | L | N | 0 | | 80033 | 160093
31 | G | 1222 | W | N | 2 | | 80027 | 160486
32 | G | 1204 | W | N | 2 | | 80021 | 160071
32 | G | 1219 | L | N | 1 | | 80024 | 160416
33 | G | 1210 | W | N | 2 | | 80018 | 160208
33 | G | 1202 | L | N | 1 | | 80012 | 160024
34 | G | 1209 | D | N | 3 | | 80014 | 160187
34 | G | 1214 | D | N | 3 | | 80006 | 160302
35 | G | 1211 | L | N | 0 | | 80036 | 160233
35 | G | 1215 | W | N | 1 | | 80029 | 160324
36 | G | 1220 | L | N | 0 | | 80005 | 160439
36 | G | 1203 | W | N | 1 | | 80013 | 160047
37 | R | 1221 | L | P | 1 | 4 | 80004 | 160463
37 | R | 1213 | W | P | 1 | 5 | 80007 | 160278
38 | R | 1224 | W | N | 1 | | 80014 | 160531
38 | R | 1212 | L | N | 0 | | 80006 | 160256
39 | R | 1204 | L | N | 0 | | 80003 | 160071
39 | R | 1214 | W | N | 1 | | 80023 | 160302
40 | R | 1207 | W | N | 2 | | 80008 | 160140
40 | R | 1215 | L | N | 1 | | 80019 | 160324
41 | R | 1208 | W | N | 3 | | 80018 | 160163
41 | R | 1218 | L | N | 0 | | 80012 | 160392
42 | R | 1209 | L | N | 0 | | 80017 | 160187
42 | R | 1203 | W | N | 4 | | 80010 | 160047
43 | R | 1211 | W | N | 2 | | 80009 | 160231
43 | R | 1219 | L | N | 0 | | 80015 | 160416
44 | R | 1206 | L | N | 1 | | 80001 | 160117
44 | R | 1210 | W | N | 2 | | 80002 | 160208
45 | Q | 1213 | L | P | 1 | 3 | 80005 | 160278
45 | Q | 1214 | W | P | 1 | 5 | 80013 | 160302
46 | Q | 1224 | W | N | 3 | | 80001 | 160531
46 | Q | 1203 | L | N | 1 | | 80002 | 160047
47 | Q | 1208 | W | P | 1 | 6 | 80016 | 160163
47 | Q | 1211 | L | P | 1 | 5 | 80020 | 160231
48 | Q | 1207 | W | N | 5 | | 80021 | 160140
48 | Q | 1210 | L | N | 2 | | 80024 | 160208
49 | S | 1214 | W | N | 2 | | 80011 | 160302
49 | S | 1224 | L | N | 0 | | 80022 | 160531
50 | S | 1207 | W | N | 2 | | 80008 | 160140
50 | S | 1208 | L | N | 1 | | 80019 | 160163
51 | F | 1214 | W | N | 1 | | 80004 | 160302
51 | F | 1207 | L | N | 0 | | 80007 | 160140
Sample table: asst_referee_mast
ass_ref_id | ass_ref_name | country_id
------------+--------------------------+------------
80034 | Tomas Mokrusch | 1205
80038 | Martin Wilczek | 1205
80004 | Simon Beck | 1206
80006 | Stephen Child | 1206
80007 | Jake Collin | 1206
80014 | Mike Mullarkey | 1206
80026 | Frederic Cano | 1207
80028 | Nicolas Danos | 1207
80005 | Mark Borsch | 1208
80013 | Stefan Lupp | 1208
80016 | Gyorgy Ring | 1209
80020 | Vencel Toth | 1209
80033 | Damien McGraith | 1215
80008 | Elenito Di Liberatore | 1211
80019 | Mauro Tonolini | 1211
80021 | Sander van Roekel | 1226
80024 | Erwin Zeinstra | 1226
80025 | Frank Andas | 1229
80031 | Kim Haglund | 1229
80012 | Tomasz Listkiewicz | 1213
80018 | Pawel Sokolnicki | 1213
80029 | Sebastian Gheorghe | 1216
80036 | Octavian Sovre | 1216
80030 | Nikolay Golubev | 1217
80032 | Tikhon Kalugin | 1217
80037 | Anton Averyanov | 1217
80027 | Frank Connor | 1228
80010 | Dalibor Durdevic | 1227
80017 | Milovan Ristic | 1227
80035 | Roman Slysko | 1218
80001 | Jure Praprotnik | 1225
80002 | Robert Vukan | 1225
80003 | Roberto Alonso Fernandez | 1219
80023 | Juan Yuste Jimenez | 1219
80011 | Mathias Klasenius | 1220
80022 | Daniel Warnmark | 1220
80009 | Bahattin Duran | 1222
80015 | Tarik Ongun | 1222
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 country name and the count of distinct match numbers for each country where an assistant referee is involved
SELECT
country_name, -- Selecting the country name from the soccer_country table
count(DISTINCT match_no) -- Counting the distinct match numbers for each country
FROM
match_details a -- Specifying the match_details table with alias 'a'
JOIN
asst_referee_mast c ON a.ass_ref = c.ass_ref_id -- Joining the match_details table with the asst_referee_mast table on the assistant referee ID
JOIN
soccer_country b ON c.country_id = b.country_id -- Joining the asst_referee_mast table with the soccer_country table on the country ID
GROUP BY
country_name -- Grouping the results by country name
HAVING
count(DISTINCT match_no) = ( -- Filtering the results to only include rows where the count of distinct match numbers is equal to...
SELECT
max(mm) -- Selecting the maximum count of distinct match numbers
FROM
( -- Subquery to calculate the count of distinct match numbers for each country and find the maximum count
SELECT
count(DISTINCT match_no) mm -- Counting the distinct match numbers for each country and assigning the result to the alias 'mm'
FROM
match_details a -- Specifying the match_details table with alias 'a'
JOIN
asst_referee_mast c ON a.ass_ref = c.ass_ref_id -- Joining the match_details table with the asst_referee_mast table on the assistant referee ID
JOIN
soccer_country b ON c.country_id = b.country_id -- Joining the asst_referee_mast table with the soccer_country table on the country ID
GROUP BY
country_name -- Grouping the results by country name
) hh -- Assigning the subquery results to the alias 'hh'
);
Sample Output:
country_name | count --------------+------- England | 7 (1 row)
Code Explanation:
The said query in SQL that selects the name of countries and the count of distinct match numbers in the match_details table for each country.
The HAVING clause filters the results to only show the countries whose count of distinct match numbers is equal to the maximum count of distinct match numbers among all countries. The maximum count of distinct match numbers is obtained by a subquery that selects the count of distinct match numbers for each country and then selects the maximum count from those results.
The JOIN clause joins the match_details and asst_referee_mast table based on the ass_ref and ass_ref_id columns, joins the results with the soccer_country tables based on the country_id column to obtain the required data.
Alternative Solution:
Cross Join with Subquery and HAVING:
-- Selecting the country name and the count of distinct match numbers for each country where an assistant referee is involved
SELECT
b.country_name, -- Selecting the country name from the soccer_country table
COUNT(DISTINCT a.match_no) AS Match_Count -- Counting the distinct match numbers for each country and assigning the result to the alias 'Match_Count'
FROM
soccer_country b -- Specifying the soccer_country table with alias 'b'
CROSS JOIN
asst_referee_mast c -- Performing a cross join with the asst_referee_mast table with alias 'c'
LEFT JOIN
match_details a ON a.ass_ref = c.ass_ref_id AND c.country_id = b.country_id -- Left joining the match_details table with the cross join of soccer_country and asst_referee_mast tables on the assistant referee ID and country ID
GROUP BY
b.country_name -- Grouping the results by country name
HAVING
COUNT(DISTINCT a.match_no) = ( -- Filtering the results to only include rows where the count of distinct match numbers is equal to...
SELECT
MAX(cnt) -- Selecting the maximum count of distinct match numbers
FROM
( -- Subquery to calculate the count of distinct match numbers for each country and find the maximum count
SELECT
COUNT(DISTINCT match_no) AS cnt -- Counting the distinct match numbers for each country and assigning the result to the alias 'cnt'
FROM
match_details x -- Specifying the match_details table with alias 'x'
JOIN
asst_referee_mast y ON x.ass_ref = y.ass_ref_id -- Joining the match_details table with the asst_referee_mast table on the assistant referee ID
JOIN
soccer_country z ON y.country_id = z.country_id -- Joining the asst_referee_mast table with the soccer_country table on the country ID
GROUP BY
z.country_name -- Grouping the results by country name
) sub -- Assigning the subquery results to the alias 'sub'
);
Explanation:
This query uses a cross join to generate all possible combinations of country names and assistant referees. It then left joins with match details to count the distinct matches. The HAVING clause filters the results based on the match count being equal to the maximum count.
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Practice Online
Sample Database: soccer
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