Step 1: Select rows where 'away_team_score' is the maximum value in the 'away_team_score' column.
| home_team |
home_team_score |
away_team |
away_team_score |
venue |
crowd |
date |
| geelong |
13.12 (90) |
hawthorn |
7.6 (48) |
kardinia park |
16870 |
1954-08-14 |
| collingwood |
12.16 (88) |
south melbourne |
13.12 (90) |
victoria park |
18556 |
1954-08-14 |
| carlton |
10.16 (76) |
essendon |
11.14 (80) |
princes park |
29744 |
1954-08-14 |
| richmond |
10.18 (78) |
melbourne |
15.4 (94) |
punt road oval |
24000 |
1954-08-14 |
| north melbourne |
9.14 (68) |
footscray |
9.14 (68) |
arden street oval |
22000 |
1954-08-14 |
| st kilda |
13.14 (92) |
fitzroy |
9.15 (69) |
junction oval |
11500 |
1954-08-14 |
Step 2: Select rows where 'away_team' is 'melbourne'.
| home_team |
home_team_score |
away_team |
away_team_score |
venue |
crowd |
date |
| st kilda |
13.14 (92) |
fitzroy |
9.15 (69) |
junction oval |
11500 |
1954-08-14 |
Step 3: Use a `CASE` statement to return TRUE if the number of rows is equal to 1, otherwise return FALSE.
| home_team |
home_team_score |
away_team |
away_team_score |
venue |
crowd |
date |
Final output table:
| verification_result |
| FALSE |
Prediction: FALSE