
Chainsaw Warrior (Classic)
Auroch Digital · 2013-10-07
Modes: Single player
Releases: Oct 02, 2013 (Android), Sep 01, 2013 (PC (Microsoft Windows)), Oct 07, 2013 (Linux), Sep 01, 2013 (Mac), Sep 23, 2013 (iOS)
Chainsaw Warrior from Games Workshop is the classic game for one strong-nerved player! It's 2032 and spatial warping has opened a hole into another dimension in the midst of the old municipal buildings at the heart of Manhattan. Bizarre and dangerous creatures are flooding into our dimension.
0 players in-game as of 2026-08-30 08:00 UTC (census sample)
It's the year 2032 and spatial warping has opened a hole into another dimension in the midst of the old municipal buildings at the heart of Manhattan. Bizarre and dangerous creatures are flooding into our dimension, intent on destruction. Behind their actions is a controlling intelligence known as 'Darkness', who intends to drag New York back into the warp - destroying it utterly! Air strikes, ground assaults and WMDs have all failed to stop the swarming forces from beyond. All that remains is a single hope: a shadowy ex-special forces soldier, enhanced for combat and known only as 'Chainsaw (Storyline via IGDB)
Health check
- · Not enough review history collected yet to judge health.
- · Top 44% of 11,424 Adventure games in the census by review count.
Review-multiple estimate from 395 total reviews — how this is computed.
Players online
Price history
Completion
- · 12.6% of players earned Easy
- · 2.5% of players earned Turnin'
- · 1.4% of players earned Throne of skulls
Global achievement rates from Steam.
Details
Player tags
RPGIndieHorrorZombiesStrategySurvivalAdventureCard GameDifficultBoard Game
Census log
- 2026-08-23Highest concurrent player count the census has recorded: 2 (2026-08-23).
Computed from census-recorded observations only — dates are observation dates.
Players also track
Star Control®: OriginsUnclaimed WorldENDLESS Legend™SurvivalistReverse CrawlJudgment: Apocalypse Survival SimulationDungeon Of Dragon KnightCHANGE: A Homeless Survival Experience
Similarity via IGDB.