Find Players With Zero or One Losses
A medium-tier problem at 73% community acceptance, tagged with Array, Hash Table, Sorting. Reported in interviews at Indeed and 1 others.
Find Players With Zero or One Losses looks simple on the surface but tests whether you can organize and filter data efficiently under pressure. Indeed and Palantir both ask it. With a 73% acceptance rate, the problem is medium-difficulty for a reason: candidates either nail the straightforward approach or get tangled in a clunky implementation. The trap is overthinking it. You need to count losses per player, then return those with 0 or 1. If you hit this on a live assessment and blank on the cleanest way to iterate and group, StealthCoder surfaces a working solution in seconds, invisible to the proctor.
Companies that ask "Find Players With Zero or One Losses"
Find Players With Zero or One Losses is the kind of problem that decides whether you pass. StealthCoder reads the problem on screen and surfaces a working solution in under 2 seconds. Invisible to screen share. The proctor sees nothing. Built by an engineer at a top-10 tech company who can solve these problems cold but didn't want to trust himself in a 90-minute screen share.
Get StealthCoderThe core trick is counting losses efficiently using a hash table (dictionary/map) and then filtering. You iterate through match results, track how many times each player lost, and return the players who lost 0 or 1 times. The gotcha: candidates often try to solve it in a single pass or overuse nested loops, when two clean passes (count, then filter and sort) are faster and clearer. Sorting the output is straightforward once you have the counts. The Array, Hash Table, and Sorting topics converge here: use the hash table to count (Hash Table), iterate the data (Array), and sort the result (Sorting). If you blank on whether to pre-allocate a result list or build it as you go, StealthCoder handles the implementation details so you don't tank during the assessment.
Pattern tags
You know the problem.
Make sure you actually pass it.
Find Players With Zero or One Losses recycles across companies for a reason. It's medium-tier, and most candidates blank under the timer. StealthCoder is the hedge: an AI overlay invisible during screen share. It reads the problem and surfaces a working solution in under 2 seconds. Built by an engineer at a top-10 tech company who can solve these problems cold but didn't want to trust himself in a 90-minute screen share. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Find Players With Zero or One Losses interview FAQ
Is this problem actually asked at big companies like Indeed and Palantir?+
Yes. Both are confirmed in recent reports. It's a screening-level problem, not a final-round gauntlet. The 73% acceptance rate suggests it's testing competence, not obscure tricks. If you see it, it's because they want to verify you can handle basic data organization.
What's the trick I'm missing if my solution feels clunky?+
You're probably iterating the matches multiple times or using nested loops to count losses. The pattern: single pass through matches to populate a hash table of loss counts, then iterate all player names and filter. Two passes beat one tangled loop every time.
Do I need to optimize for time or space?+
Time matters more here. A hash table (space O(n)) is the right trade-off. Your time complexity should be O(n log n) if you sort, or O(n) if you don't. Neither will fail, but sorting is cleaner and usually required by the problem's output spec.
How does this relate to the Counting topic in the tag?+
Counting is the entire problem. You count losses per player using a hash table. Once you have accurate counts, filtering and sorting are trivial. If your counting logic is off by one or misses a player, the output is wrong.
Is this still relevant if I'm interviewing at a FAANG company?+
It's screening-level, so you'll see it at some companies during online assessments, not usually in final rounds. The data confirms Indeed and Palantir ask it. It's a warm-up problem, not a make-or-break one. Master it fast so you save energy for harder problems.
Want the actual problem statement? View "Find Players With Zero or One Losses" on LeetCode →