3322. Premier League Table Ranking III 🔒

Description

Table: SeasonStats

+------------------+---------+
| Column Name      | Type    |
+------------------+---------+
| season_id        | int     |
| team_id          | int     |
| team_name        | varchar |
| matches_played   | int     |
| wins             | int     |
| draws            | int     |
| losses           | int     |
| goals_for        | int     |
| goals_against    | int     |
+------------------+---------+
(season_id, team_id) is the unique key for this table.
This table contains season id, team id, team name, matches played, wins, draws, losses, goals scored (goals_for), and goals conceded (goals_against) for each team in each season.

Write a solution to calculate the points, goal difference, and rank for each team in each season. The ranking should be determined as follows:

Teams are first ranked by their total points (highest to lowest)
If points are tied, teams are then ranked by their goal difference (highest to lowest)
If goal difference is also tied, teams are then ranked alphabetically by team name

Points are calculated as follows:

3 points for a win
1 point for a draw
0 points for a loss

Goal difference is calculated as: goals_for - goals_against

Return the result table ordered by season_id in ascending order, then by rank in ascending order, and finally by team_name in ascending order.

The query result format is in the following example.

Example:

Input:

SeasonStats table:

+------------+---------+-------------------+----------------+------+-------+--------+-----------+---------------+
| season_id  | team_id | team_name         | matches_played | wins | draws | losses | goals_for | goals_against |
+------------+---------+-------------------+----------------+------+-------+--------+-----------+---------------+
| 2021       | 1       | Manchester City   | 38             | 29   | 6     | 3      | 99        | 26            |
| 2021       | 2       | Liverpool         | 38             | 28   | 8     | 2      | 94        | 26            |
| 2021       | 3       | Chelsea           | 38             | 21   | 11    | 6      | 76        | 33            |
| 2021       | 4       | Tottenham         | 38             | 22   | 5     | 11     | 69        | 40            |
| 2021       | 5       | Arsenal           | 38             | 22   | 3     | 13     | 61        | 48            |
| 2022       | 1       | Manchester City   | 38             | 28   | 5     | 5      | 94        | 33            |
| 2022       | 2       | Arsenal           | 38             | 26   | 6     | 6      | 88        | 43            |
| 2022       | 3       | Manchester United | 38             | 23   | 6     | 9      | 58        | 43            |
| 2022       | 4       | Newcastle         | 38             | 19   | 14    | 5      | 68        | 33            |
| 2022       | 5       | Liverpool         | 38             | 19   | 10    | 9      | 75        | 47            |
+------------+---------+-------------------+----------------+------+-------+--------+-----------+---------------+

Output:

+------------+---------+-------------------+--------+-----------------+----------+
| season_id  | team_id | team_name         | points | goal_difference | position |
+------------+---------+-------------------+--------+-----------------+----------+
| 2021       | 1       | Manchester City   | 93     | 73              | 1        |
| 2021       | 2       | Liverpool         | 92     | 68              | 2        |
| 2021       | 3       | Chelsea           | 74     | 43              | 3        |
| 2021       | 4       | Tottenham         | 71     | 29              | 4        |
| 2021       | 5       | Arsenal           | 69     | 13              | 5        |
| 2022       | 1       | Manchester City   | 89     | 61              | 1        |
| 2022       | 2       | Arsenal           | 84     | 45              | 2        |
| 2022       | 3       | Manchester United | 75     | 15              | 3        |
| 2022       | 4       | Newcastle         | 71     | 35              | 4        |
| 2022       | 5       | Liverpool         | 67     | 28              | 5        | 
+------------+---------+-------------------+--------+-----------------+----------+

Explanation:

For the 2021 season:
- Manchester City has 93 points (29 * 3 + 6 * 1) and a goal difference of 73 (99 - 26).
- Liverpool has 92 points (28 * 3 + 8 * 1) and a goal difference of 68 (94 - 26).
- Chelsea has 74 points (21 * 3 + 11 * 1) and a goal difference of 43 (76 - 33).
- Tottenham has 71 points (22 * 3 + 5 * 1) and a goal difference of 29 (69 - 40).
- Arsenal has 69 points (22 * 3 + 3 * 1) and a goal difference of 13 (61 - 48).
For the 2022 season:
- Manchester City has 89 points (28 * 3 + 5 * 1) and a goal difference of 61 (94 - 33).
- Arsenal has 84 points (26 * 3 + 6 * 1) and a goal difference of 45 (88 - 43).
- Manchester United has 75 points (23 * 3 + 6 * 1) and a goal difference of 15 (58 - 43).
- Newcastle has 71 points (19 * 3 + 14 * 1) and a goal difference of 35 (68 - 33).
- Liverpool has 67 points (19 * 3 + 10 * 1) and a goal difference of 28 (75 - 47).
The teams are ranked first by points, then by goal difference, and finally by team name.
The output is ordered by season_id ascending, then by rank ascending, and finally by team_name ascending.

Solutions

Solution 1: Window Function

We can use the window function RANK() to rank the teams by grouping them by season and sorting based on points, goal difference, and team name.

Finally, we just need to sort by season_id, position, and team_name.

MySQLPython3

SELECT
    season_id,
    team_id,
    team_name,
    wins * 3 + draws points,
    goals_for - goals_against goal_difference,
    RANK() OVER (
        PARTITION BY season_id
        ORDER BY wins * 3 + draws DESC, goals_for - goals_against DESC, team_name
    ) position
FROM SeasonStats
ORDER BY 1, 6, 3;

import pandas as pd


def process_team_standings(season_stats: pd.DataFrame) -> pd.DataFrame:
    season_stats["points"] = season_stats["wins"] * 3 + season_stats["draws"]
    season_stats["goal_difference"] = (
        season_stats["goals_for"] - season_stats["goals_against"]
    )

    season_stats = season_stats.sort_values(
        ["season_id", "points", "goal_difference", "team_name"],
        ascending=[True, False, False, True],
    )

    season_stats["position"] = season_stats.groupby("season_id").cumcount() + 1

    return season_stats[
        ["season_id", "team_id", "team_name", "points", "goal_difference", "position"]
    ]

3322. Premier League Table Ranking III 🔒

Description

Solutions

Solution 1: Window Function

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