Statement: by late january detroit was the lowest scoring team

Input Table: 2003 - 04 detroit red wings season

Step 1: Select rows where 'date' is after or equal to '2003-01-01' and before or equal to '2004-01-31'.
date visitor score home decision attendance record
0002-01-01 detroit 4 - 1 carolina joseph 17053 24 - 12 - 4 - 1
0001-01-03 anaheim 1 - 3 detroit legace 20066 25 - 12 - 4 - 1
0000-01-05 nashville 0 - 6 detroit joseph 20066 26 - 12 - 4 - 1
0001-01-07 boston 3 - 0 detroit joseph 20066 26 - 13 - 4 - 1
0000-01-10 detroit 1 - 2 boston joseph 17565 26 - 13 - 4 - 2
9999-01-14 chicago 2 - 4 detroit legace 20066 27 - 13 - 4 - 2
0000-01-16 phoenix 3 - 3 detroit joseph 20066 27 - 13 - 5 - 2
9999-01-19 detroit 1 - 2 san jose joseph 17361 27 - 14 - 5 - 2
9999-01-21 detroit 2 - 2 anaheim legace 17174 27 - 14 - 6 - 2
9999-01-22 detroit 5 - 4 los angeles joseph 18118 28 - 14 - 6 - 2
9999-01-24 detroit 2 - 5 phoenix joseph 19019 28 - 15 - 6 - 2
9999-01-26 detroit 2 - 2 dallas legace 18532 28 - 15 - 7 - 2
9999-01-29 new jersey 2 - 5 detroit joseph 20066 29 - 15 - 7 - 2
9999-01-31 carolina 4 - 4 detroit legace 20066 30 - 15 - 8 - 2
Step 2: Extract the numerical value from the 'score' column by splitting the string on '-' and selecting the first element to add column 'home_score' to existing table.
date visitor score home decision attendance record
Step 3: Extract the numerical value from the 'score' column by splitting the string on '-' and selecting the second element to add column 'visitor_score' to existing table.
date visitor score home decision attendance record home_score
Step 4: Select rows where 'home_score' is less than or equal to 2.
date visitor score home decision attendance record home_score visitor_score
Step 5: Use a `CASE` statement to return TRUE if the number of rows is equal to the number of rows in the table, otherwise return FALSE.
date visitor score home decision attendance record home_score visitor_score
Final output table:
verification_result
TRUE

Prediction: TRUE