## Problem You are given a list of `2n` players each with a skill rating. Split them into two teams of exactly `n` players such that the absolute difference in total skill between the two teams is minimized. Return the minimum possible difference. ```python def min_team_difference(ratings: list[int]) -> int: """len(ratings) is always even. Return min |sum(team1) - sum(team2)|.""" pass ``` ``` Input: ratings = [3, 1, 4, 2] Output: 0 # Team1=[3,2]=5, Team2=[1,4]=5 -> diff=0 Input: ratings = [1, 2, 3, 4, 5, 6] Output: 1 # Total=21, need each team close to 10.5 # Team1=[1,4,6]=11, Team2=[2,3,5]=10 -> diff=1 Input: ratings = [10, 1, 1, 1] Output: 7 # Team1=[10,1]=11, Team2=[1,1]=2 -> diff=9 # Team1=[1,1]=2, Team2=[10,1]=11 -> diff=9 # Optimal: same. ``` ## Follow-ups 1. Is this NP-hard in general? What constraint makes a DP solution tractable here? 2. Describe the DP state and transition for solving this exactly. 3. If teams don't have to be equal size, how does the problem simplify or change? 4. Extend: each player has two attributes (skill, cost) and you want to minimize skill difference subject to total cost <= budget.

InterviewDB Experience · Los Angeles

Team Split: Divide Players into Two Balanced Teams

Onsite

Interview Experience

Problem You are given a list of 2n players each with a skill rating. Split them into two teams of exactly n players such that the absolute difference in total skill between the two teams is minimized. Return the minimum possible difference. Follow-ups Is this NP-hard in general? What constraint makes a DP solution tractable here? Describe the DP state and transition for solving this exactly. If teams don't have to be equal size, how does the problem simplify or change? Extend: each player has tw…

Full Details

🔒

Unlock all Zoox questions

Full insider details, leaked discussions, and candidate experiences.

Get full access — from $50/mo

About This Question

This is a candidate experience report from a zoox interview during the onsite round.

It covers the following topics: Coding, Onsite, Dynamic Programming .

Topics

Coding Onsite Dynamic Programming

About Zoox Interview Reports

This question was reported by a candidate who interviewed at Zoox. LeakCode aggregates interview reports from 10+ sources, including 1Point3Acres, Glassdoor, LeetCode Discuss, Blind, Reddit, Indeed, and Nowcoder. Each report is translated where necessary, deduplicated against existing entries, and tagged by company, role, round type, and reporting date.

Use this question as one calibration data point, not a memorization target. Companies typically rotate their question pools every 2-4 months; the exact wording of a 2024 question may differ from what you encounter today. The underlying pattern, difficulty level, and follow-up depth at Zoox are the higher-signal extractions to take from this report.

For broader preparation context, the Zoox interview process typically includes a recruiter screen, one or two technical phone screens, and a 4-5 round on-site loop covering coding, system design (at L4+ levels), and behavioral. Reports tagged on LeakCode show the round-by-round distribution and typical difficulty calibration. To browse questions filtered by round type and seniority, use the company hub linked above.

How To Practice This Type of Question

Solve similar problems on LeetCode under timed conditions (25-35 minutes per medium difficulty). The goal is pattern recognition: recognize the underlying technique (sliding window, two-pointer, BFS, memoized recursion, etc.) within 60-90 seconds of reading. Strong candidates verbalize their hypothesis out loud before coding, then iterate based on feedback. Weak candidates dive into implementation immediately, lose time on the wrong approach, and run out of time for follow-ups.

Companies update their question pools every 2-4 months. The exact wording of any given question may have been retired by the time you interview. Focus your prep on the pattern, not the specific problem. The patterns that appear in Zoox reports consistently are the ones worth investing in; one-off niche problems are not.

During Your Zoox Round

Apply the standard interview round template: clarify requirements (2-3 minutes), state your approach out loud and confirm direction with the interviewer (3-5 minutes), code with narration (15-25 minutes), test with concrete examples including edge cases (5 minutes), discuss optimization or trade-offs if time permits (5 minutes). This template is universally accepted across FAANG and adjacent companies; deviating from it produces weaker interviewer feedback signal.

The single most predictive failure mode in Zoox reports tagged "no hire": not asking clarifying questions. Interviewers are explicitly trained to weight this. Strong candidates ask 3-5 clarifying questions even on problems that look obvious; weak candidates dive into code immediately. The clarifying-question check is often the first signal recorded in the interviewer's written notes.