Skip to main content

Pattern: Slimy Expulsion Boots

EpicLeatherworking
Open in the auction house

Advertisements

Price

Last scan Nov 6, 2026, 00:00 UTC

Last seen price on Bloodscalp (US)

41,077g 61s 0c
Not listed in the last 7 days. This is the newest listing a scan recorded, not a live price.
Lowest buyout
41,077g 61s 0c
Listings at that scan
1
  • Regional auction data, hourly
  • 154 scans
How prices are measured
  • Pattern: Slimy Expulsion Boots
  • Item Level: 1
  • Leatherworking
  • Required Level: 1
  • Sell price: 50g 0s 0c
Sources: 1 recipe

Sources

Recipe, 1 source

  • Slimy Expulsion Boots

Most sources come from published game data.

Advertisements

Market

Bloodscalp (US)

Price History

Bloodscalp (US)
Low
9,999g 99s 0c
Average
48,364g 83s 0c
High
125,124g 82s 0c
Samples
154
The 7-day average needs at least a week of history; pick a wider range than 1D.Show the 7-day average market price
Price history for Pattern: Slimy Expulsion Boots, 1 week, Bloodscalp (US)
Time (UTC)Lowest buyoutAverageQuantity
Mar 1, 0045,037g45,037g1
Mar 2, 0045,037g45,037g1
Mar 3, 0045,037g45,037g1
Mar 10, 0089,224g89,224g1
Mar 12, 0089,224g89,224g2
Mar 13, 0044,153g71,196g3
Mar 18, 0037,637g37,637g1
Mar 21, 0034,472g34,472g1
Mar 23, 0029,526g29,526g2
Mar 27, 0017,500g17,500g1
Mar 28, 0017,500g17,500g2
Apr 3, 0024,700g24,700g1
Apr 8, 0026,071g26,071g1
Apr 9, 0026,071g26,071g1
Apr 10, 0026,853g26,853g1
Apr 11, 0019,996g24,110g2
Apr 12, 0019,996g22,281g2
Apr 13, 0019,996g27,813g1
Apr 14, 0019,996g33,346g3
Apr 15, 0019,996g27,619g3
Apr 16, 0019,996g19,996g2
Apr 17, 0017,900g19,696g2
Apr 18, 0017,899g18,860g3
Apr 19, 0017,899g17,899g2
Apr 20, 0017,899g17,899g3
Apr 21, 0012,888g13,812g4
Apr 22, 0012,888g12,889g4
Apr 23, 0012,889g12,889g2
May 2, 0047,821g47,821g1
May 3, 0047,821g47,821g1
May 4, 0047,821g47,821g1
May 5, 0033,777g33,777g1
May 6, 0033,777g33,777g1
May 7, 0033,777g33,777g1
May 10, 0031,440g31,440g1
May 11, 0031,440g31,440g1
May 12, 0031,440g31,440g2
May 13, 0031,440g31,440g2
May 14, 0031,440g31,440g1
May 22, 0047,821g47,821g1
May 25, 0047,800g47,800g1
May 26, 0047,800g47,800g1
May 27, 0047,800g47,800g1
May 28, 0064,290g64,290g1
May 29, 0064,290g64,290g1
Jun 4, 0064,290g64,290g1
Jun 5, 0064,290g64,290g1
Jun 6, 0064,290g64,290g1
Jun 11, 0048,272g48,352g1
Jun 12, 0048,272g48,272g1
Jun 13, 0048,272g48,272g1
Jun 17, 0047,000g47,000g1
Jun 19, 0047,960g47,960g1
Jun 20, 0047,960g47,960g1
Jun 21, 0047,960g47,960g1
Jun 22, 0047,820g47,820g1
Jun 23, 0047,820g47,820g1
Jun 24, 0047,820g47,820g1
Jun 29, 0049,766g49,766g1
Jun 30, 0049,766g49,766g1
Jul 1, 0049,766g65,388g1
Jul 2, 0096,631g96,631g1
Jul 3, 0096,631g96,631g1
Jul 12, 0049,573g49,573g1
Jul 13, 0049,573g49,573g1
Jul 18, 0047,820g47,820g1
Jul 19, 0047,820g64,523g1
Jul 20, 0094,192g94,872g2
Jul 21, 0067,015g88,471g3
Jul 22, 0067,015g70,121g2
Jul 23, 0067,006g67,009g2
Jul 24, 0067,006g67,006g1
Jul 25, 0067,006g67,006g2
Jul 26, 0066,997g67,001g3
Jul 27, 0066,997g66,999g3
Jul 28, 0066,997g66,997g1
Jul 29, 0049,772g61,559g1
Jul 30, 0049,772g49,777g2
Jul 31, 0049,772g49,776g2
Aug 1, 0049,772g49,772g2
Aug 2, 0049,763g49,770g3
Aug 3, 0049,763g49,766g1
Aug 4, 0049,763g49,763g1
Aug 5, 00101,666g101,666g1
Aug 6, 0067,094g87,261g2
Aug 7, 0067,094g68,822g1
Aug 8, 0067,094g67,094g1
Aug 9, 0049,709g49,709g1
Aug 10, 0049,700g49,705g2
Aug 11, 0049,700g49,703g2
Aug 12, 0049,700g49,700g1
Aug 13, 0049,999g49,999g1
Aug 14, 0049,999g49,999g1
Aug 15, 0049,999g49,999g1
Aug 16, 0094,998g101,565g1
Aug 17, 0094,998g98,787g2
Aug 18, 0094,998g96,593g1
Aug 19, 00125,125g125,125g1
Aug 23, 0048,971g48,971g1
Aug 24, 0048,971g48,971g1
Aug 25, 0048,971g48,971g1
Aug 26, 0049,985g49,985g1
Aug 27, 0049,985g49,985g1
Aug 28, 0049,976g49,977g1
Aug 29, 0049,976g49,976g1
Aug 30, 0049,976g49,976g1
Aug 31, 0049,976g49,976g1
Sep 1, 0044,327g44,327g2
Sep 2, 0044,327g44,327g2
Sep 3, 0043,369g43,869g1
Sep 4, 0043,360g43,365g2
Sep 5, 0043,360g43,362g3
Sep 6, 0043,351g43,359g1
Sep 7, 0043,351g43,351g2
Sep 8, 0043,351g43,351g3
Sep 9, 0043,351g43,351g2
Sep 10, 0043,351g43,351g1
Sep 11, 0090,000g90,000g1
Sep 12, 0090,000g90,000g2
Sep 13, 0090,000g90,000g2
Sep 14, 0042,941g77,166g1
Sep 15, 0042,941g58,627g3
Sep 16, 0010,000g53,249g3
Sep 17, 0010,000g10,000g1
Sep 24, 0044,999g44,999g1
Sep 25, 0044,999g44,999g1
Sep 26, 0044,999g44,999g1
Sep 27, 0018,592g18,592g1
Sep 28, 0018,592g21,405g1
Sep 29, 0018,592g34,344g1
Sep 30, 0041,095g41,095g1
Oct 8, 0035,220g35,220g1
Oct 9, 0035,213g35,218g3
Oct 10, 0035,213g35,216g2
Oct 11, 0035,213g35,213g1
Oct 12, 0026,498g26,498g1
Oct 13, 0026,498g26,498g2
Oct 14, 0026,498g26,498g1
Oct 18, 0019,525g21,482g1
Oct 19, 0019,525g25,396g2
Oct 20, 0031,266g31,266g1
Oct 22, 0033,386g33,386g1
Oct 23, 0033,386g33,386g1
Oct 24, 0033,386g33,386g1
Oct 26, 0040,192g40,192g1
Oct 27, 0040,192g40,192g1
Oct 28, 0040,192g40,192g2
Oct 29, 0040,192g40,192g1
Nov 1, 0071,956g75,235g2
Nov 2, 0041,078g71,175g2
Nov 3, 0041,078g47,672g1
Nov 4, 0041,078g41,078g2
Nov 5, 0041,078g41,078g1
Nov 6, 0041,078g41,078g1
  • Lowest buyout
  • Average
  • Quantity
  • Latest lowest price
Daily average for Pattern: Slimy Expulsion Boots
Day (UTC)AverageUnits listed
Nov 641,077g 61s 0c1
Nov 541,077g 61s 0c1
Nov 441,077g 61s 0c2
Nov 347,671g 82s 90c1
Nov 271,174g 70s 78c2
Nov 175,234g 92s 15c2
Oct 2940,192g 7s 0c1
Oct 2840,192g 7s 0c2
Oct 2740,192g 7s 0c1
Oct 2640,192g 7s 0c1
Oct 2433,385g 92s 0c1
Oct 2333,385g 92s 0c1
Oct 2233,385g 92s 0c1
Oct 2031,266g 15s 0c1
Oct 1925,395g 67s 0c2
Oct 1821,482g 1s 67c1
Oct 1426,497g 71s 0c1
Oct 1326,497g 71s 0c2
Oct 1226,497g 71s 0c1
Oct 1135,213g 12s 0c1
Oct 1035,216g 48s 0c2
Oct 935,217g 94s 76c3
Oct 835,220g 12s 0c1
Sep 3041,094g 83s 0c1
Sep 2934,343g 87s 0c1
Sep 2821,404g 53s 0c1
Sep 2718,591g 63s 0c1
Sep 2644,999g 1s 0c1
Sep 2544,999g 1s 0c1
Sep 2444,999g 1s 0c1

Sparse data for 1 week: showing all available history.

Trading hours: the cheaper and dearer hours of the week, in UTC

Trading Hours

See when Pattern: Slimy Expulsion Boots tends to trade below or above its usual price, based on the last 30 days.

The grid follows the auction week in UTC.

Loading trading hours
Cheaper than usualTypicalMore expensive than usualLimited data