Topics Trading

Winning Strategies: Lessons From Past Champions of WSOT

Intermediate
Trading
2024ćčŽ9月24æ—„

Key Takeaways:

  • Most past champion squads typically have consisted of over 1,000 members, and each team has had at least 300 teammates.

  • Our observations reveal that the top winning squads in WSOT trade an average of 197 different tokens spanning various product types.

  • Traders favor higher market-cap tokens like BTC and ETH, and show a preference for higher volatility and meme tokens.

  • The average leverage adopted by champion squads is 37.1

EN_2409-T35020_Learn_Read_to_Earn_728x90.png

What Is WSOT?

The World Series of Trading (WSOT) has earned its reputation as the largest and most exhilarating crypto trading competition in the world. Each year, it attracts traders from diverse backgrounds, all eager to showcase their skills and strategies. This year's event has generated considerable excitement, primarily due to the impressive 8 million USDT prize pool awaiting participants. This substantial sum draws not only seasoned traders, but also newcomers who are eager to learn and engage with the vibrant crypto trading community.

Participating in the WSOT is straightforward. Registration is open to all, whether you’re an experienced trader or someone who wants to benefit from the insights of accomplished crypto experts. 

WSOT's core is its squad competition, which serves as the main event. To participate in this exciting format, teams must consist of a minimum of 20 members. The competition's scoring system is based primarily on trading profits, with the top 10 squads that achieve the highest scores sharing in the total prize pool. 

In addition to the main squad competition, WSOT features a variety of side competitions that offer traders additional opportunities to test their skills and win prizes. Please refer to our detailed guide here.

This article unveils trading tips for winning WSOT based on the trading patterns of past champion teams.

What is the optimal team size?

Average number of teammates per squad from previous winning squads

1,668

There is no definitive optimal team size for the WSOT. Some teams have successfully won with smaller groups, but most past champions typically have consisted of between 300 and over 1,000 members.

Larger teams offer distinct advantages, particularly since the profits or losses of the top 20% of squad members significantly influence total scores. A larger number of participants increases the likelihood of exceptional performances from some individuals. Furthermore, having more qualified members means more points can be added to the team's overall score, enhancing competitiveness in the tournament.

What are the trading frequencies from past winning teams?

Average trading counts from previous winning squads

66,211

Average daily trading counts from previous winning squads

4,729

Average daily trading counts per team member from previous winning squads

Approximately 3

While there is no universally optimal trading count for success in WSOT, analysis of leading squads reveals some insightful trends. The top-performing teams in this two-week competition typically maintain an average trading count of 4,729 trades per day per squad.

Within these squads, trading frequency has varied significantly among members. Notably, the highest-performing individuals have tended to execute at least 30 trades per day. This pattern indicates a strong correlation between trading frequency and performance, suggesting that more active traders are often more successful.

As a result, it appears that high-frequency trading strategies are widely adopted among the most successful teams. These strategies allow traders to capitalize on short-term market movements, enhancing their profit potential.

What is the optimal trading time over the two weeks?

During WSOT 2023, the overall market exhibited notable stability, with Bitcoin consistently hovering around $29,000. However, we observed a significant increase in trading frequency in the final days. This spike in activity suggested that traders were strategically positioning themselves to take advantage of potential market shifts as the competition drew to a close.

Optimal trading times are often characterized by periods of heightened volatility, particularly in response to significant macroeconomic events. As we look ahead to WSOT 2024, the volatility landscape is expected to be heavily influenced by critical factors, including the upcoming U.S. election results and broader macroeconomic indicators. These events could increase market fluctuations, providing traders with valuable opportunities to capitalize on price movements.

Traders participating in WSOT 2024 should prepare for these anticipated shifts by developing adaptive strategies that account for this expected volatility. Understanding the timing of macro events, as well as their potential impact on market dynamics, will be crucial for optimizing trading performance. By staying informed and ready to act during these pivotal moments, participants will be able to enhance their chances of success in the competition. 

As history shows, seizing opportunities during volatile periods can make all the difference in achieving a winning edge. Please refer to this article for more information on why and how macro events could affect your trading decisions.

Which tokens should you trade?

Average number of tokens traded from previous winning squads

197 tokens

Our observations reveal that the top winning squads in WSOT have traded an average of 197 different tokens spanning various product types. This diverse trading activity includes major cryptocurrencies, such as Bitcoin (BTC) and Ethereum (ETH); lesser-known tokens, such as Siacoin (SC) and Conflux (CFX); and newly launched tokens. This broad approach underscores the strategic flexibility of leading traders, allowing them to capitalize on a wide range of market opportunities.

What are some optimal trading products?

We’ve observed that Perpetual contracts are top trading products, with support from near-term options. 

The top trading pairs ranked by trading volume from leading teams are as follows:

  • BTCUSDT

  • XRPUSDT

  • ETHUSDT

  • SOLUSDT

  • DOGEUSDT

  • YGGUSDT

  • BTCUSD 

  • 1000PEPEUSDT

  • XRPUSD

  • WLDUSDT 

Observation of the most popular trading pairs reveals a strong presence of larger market-cap tokens, with BTC, XRP, ETH and SOL leading the list.

Tellingly, meme tokens have carved out their own niche, with DOGE and PEPE Perpetuals making notable appearances. In addition, YGG and WLD have surprisingly entered the top 10, primarily due to the high volatility they experienced during this period. YGG's token surged by over 80% in just two weeks, following its partnership announcement with Polygon, while WLD exhibited significant volatility during the World Series of Trading (WSOT). This highlights many traders' preference for high volatility opportunities.

Moreover, both BTC call and put options were actively leveraged by traders during this two-week trading surge, although they were used in much smaller positions as compared to Perpetuals. This trend underscores the strategic approach traders are taking, balancing their positions across different instruments to capitalize on market movements.

Skinny_Banner-1600x400.webp

What is optimal leverage?

Average leverage weighted by trading volume

Approximately 37

In the fast-paced world of trading, the limited time frame often compels traders to adopt perpetual contracts, especially when they have a firm conviction about a particular market movement. This strategy allows them to leverage their positions significantly, maximizing potential investment returns. During the 2023 WSOT, the market exhibited a period of relative stability, which further encouraged traders to utilize higher leverage. By doing so, they aimed to enhance their returns, capitalizing on the market’s predictable behavior. The combination of a stable environment and the allure of amplified profits makes using high leverage an appealing option for traders looking to optimize their strategies in such conditions.

#LearnWithBybit