DmC Devil May Cry: Weapon Bundle
Developer Ninja TheoryPublisher Capcom
The Weapon Bundle pack contains all 3 Weapons Packs!
Top SellersNot ranked
Updated Oct 31, 2026.
Wishlist RankNot ranked
Updated Oct 31, 2026.
This app is not in the latest Top Sellers or Wishlist snapshots. It can still gain richer metadata from catalog or watchlist syncs.
Metadata synced: Jul 9, 2026 · Not queued
Prices & bundle history
Steam ↗Not recordedNo cached observation
GG official storesNot recordedNo cached observation
GG keyshopsNot recordedNo cached observation
Steam reviews11177.47747747747748% positive
Recorded bundles0Checked · older than 24h
Cached US/USD prices; checkout prices may differ. Bundle history covers recorded observations and may be incomplete.
Rank History
Recent appearances for this app across complete public snapshots.
| Captured | Top Sellers | Wishlist Rank |
|---|---|---|
| Jul 23, 2026 | #8,557 | - |
| Jul 17, 2026 | #7,459 | - |
| Jul 16, 2026 | #8,897 | - |
| Jul 15, 2026 | #8,410 | - |
| Jul 11, 2026 | #6,190 | - |
Data Coverage
What SteamFueled currently has for this app.
Store metadata
Synced Jul 9, 2026
Reviews
111 reviews
Tags
8 tags synced
Links
2 public links
Current players
Waiting for player count sync
Top Sellers
Not in latest snapshot
Wishlist Rank
Not in latest snapshot
Store Details
Public Steam metadata captured from appdetails. Contact-specific fields stay backend-only.
Platforms
Windows
Steam recommendations
104
Review rating
Mostly Positive
Weighted score
74.6%
Current players
Not synced
Achievements
Not synced
Metacritic
Not synced
Required age
17+
Snapshot Details
Source context for the latest complete public rank snapshots.
Top Sellers
-
-
Previous - - Updated Oct 31, 2026
Snapshot size: 8,953 rows.Steam public Top Sellers rank order from the latest complete SteamFueled snapshot.
Wishlist Rank
-
-
Previous - - Updated Oct 31, 2026
Snapshot size: 5,360 rows.Steam public wishlist-rank order, not an exact private wishlist count.
Tags
Public Steam tags split by source. Store tags and genres are used more heavily for benchmark similarity than feature categories.