Pistol
Knife
Machinegun
Glove

The information on the site is not a financial recommendation. It is only an analytical tool.
The price forecast of the Sticker | jmqa | London 2018 are created by our ML engineers in collaboration with the Data Science and Business Analytics teams using machine learning models trained on historical price, sales, and market data for each skin. The models incorporate features such as rarity, popularity, category, skin type, weapon, exterior, price history and more. Multiple time horizons are forecasted using a combination of pretrained and custom models, with parameters including price volatility, liquidity, and recent transaction volumes. All projections are based on historical trends and statistical patterns, and actual results may differ due to market uncertainties and unforeseen events.
*avg | Sitewide average across all skins
**Earned, ***Invested | Emulates buy and sell recommendations from addskins.gg
****Success/fail accuracy | Success — buy then sell at a profit, failure — buy then sell at a loss
Each skin’s forecast is updated approximately once a week and saved. For this skin, 16 forecasts have been generated in total. Each forecast stores key data such as predicted prices, probability of success, and recommended actions (buy, sell, or hold). Later, when real price data becomes available over time, the forecast is evaluated: the actual price movement is compared with the prediction, and the recommended actions are simulated using the real price. As a result, you can see how many buy and sell actions would have occurred, how many trades would have resulted in profit or loss, the total amount invested, and the final profit. Based on these results, the forecast accuracy for this specific skin is calculated and compared to the average accuracy of all forecasts across the site.
This in-game item is a sticker featuring the signature of the great player jmqa from Winstrike Team, a participant in the London 2018 CS2 tournament. Buying this sticker not only shows support for the player, but it also financially supports the player and his team organization.
The Sticker | jmqa | London 2018 first appeared in CS2 on August 29th, 2018, as part of the London 2018 Legends Autograph Capsule. It was released together with the "FACEIT 2018 – Tournament Items" update and swept players all over the world into its wave of excitement and anticipation.
The Sticker | jmqa | London 2018 is a rather rare sticker obtained via the opening of the container London 2018 Legends Autograph Capsule. This is something that provides special value for any CS2 player. The given sticker does not form part of the collection, being the only way it differs from the rest of the stickers available in the game.
Having reached the figure of 35%, the Sticker | jmqa | London 2018 is therefore quite above the average threshold of popularity in CS2. As it never was, really, as hype as some other items, its quite stable daily sales figure corroborates a smooth demand among gamers.
The Sticker | jmqa | London 2018 is a rather popular skin in the CS2 universe, it is one of 6,710 Sticker items, as it is. This sticker is of High Grade rarity, which corresponds to the 79.92% drop chance.
At an issue price of only $0.12, the Sticker | jmqa | London 2018 is fairly within reach for any CS2 enthusiast. Besides, this widely popular sticker is highly accessible as it can be bought from virtually any market.
The Sticker | jmqa | London 2018 has received very high feedback from the CS2 community, receiving more than 5.1K votes on addskins.gg and an average rating of 4.8 out of 5 stars. Its design and quality have resonated positively with players, making it a highly sought-after item.
According to the forecast, the price of the Sticker | jmqa | London 2018 is expected grow to $ 0.54 (5.88%) in a month. After that, in the next quarter it will rise to $ 0.7 (37.25%). Further ahead, it is pojected to fall to $ 0.475 (-6.88%) in half a year. Then, in a calendar year, it will likely drop to $ 0.474 (-7.08%). Confidence is low — it is advised to avoid.
