Rank Teams by Votes

Rank Teams by Votes

What is this problem about?

The Rank Teams by Votes problem gives you voting records where each voter ranks teams. Rank teams by: first-place votes, then second-place votes (for ties), then third-place, etc. If still tied, sort alphabetically. This coding problem uses custom multi-key sorting with vote frequency counting. The array, hash table, counting, sorting, and string interview pattern is demonstrated.

Why is this asked in interviews?

Microsoft, Amazon, Google, and Bloomberg ask this to test custom comparator design with multi-key sorting. It validates the ability to count votes per position and sort with a complex tie-breaking rule.

Algorithmic pattern used

Vote frequency counting + custom sort. For each team, build a frequency array: votes[team][position] = count of times team received that position. Sort teams by their vote frequency vectors (descending), breaking final ties alphabetically.

Example explanation

votes=["ABC","ACB","ABC","ACB","ACB"]. Teams={A,B,C}. Counts: A=[5,0,0], B=[0,2,3], C=[0,3,2]. Sort descending:

• Position 1: A=5>B=0=C=0. A is first.
• Position 2: C=3>B=2. C before B. Result: "ACB".

Common mistakes candidates make

• Counting overall votes instead of per-position votes.
• Wrong sorting direction (must be descending for votes, ascending for alphabetical tie-break).
• Not building the frequency array correctly.
• Custom comparator returning wrong sign.

Interview preparation tip

Rank Teams by Votes is a multi-key sorting problem. Build a frequency vector per item, then sort with a comparator that checks each key in order. The last tiebreaker (alphabetical) inverts the pattern (ascending). Practice building custom comparators for complex sorting keys: "sort by multiple criteria," "stable sort with priority." This pattern appears in leaderboards, voting systems, and election algorithms.