Counter-Strike 2 accounted for nearly two-thirds of all esports prediction market volume on Kalshi this week, with League of Legends the clear second, and Valorant and Dota 2 both posting solid numbers.

The data pulled is from 1-7 June 2026. Kalshi’s esports markets generated a total of $36.18 million in total contract volume, across 408 matches. Six titles featured on the Kalshi platform: Counter-Strike: 2, League of Legends, Valorant, Call of Duty and Overwatch.

CS2 led comfortably with $23.7 million and 65.6% of all esports volume across 236 matches. Valve’s legendary FPS title is currently in the swing of the IEM Cologne Major, and thus it’s hardly surprising that it sits top of the charts.

I’d expect that to be an even bigger percentage come the finals on 21 June. Counter-Strike has always been open to gambling sponsors and through skin betting has more of an embedded gambling culture than others. So there’s little surprise it leads the way in interest.

League of Legends came in second with $8.7 million across 116 matches, drawing volume from the LCK (Korea), LPL (China), LEC (Europe), and regional circuits. Valorant reached $2.1 million from 13 matches, and Dota 2 generated $1.5 million from 11. Call of Duty and Overwatch were smaller but steady presences on the platform.

BIG vs. NRG in CS2 was the most-traded individual match of the week at $1.44 million in combined volume. GamerLegion vs. B8 Esports ($1.05M) and M80 vs. B8 Esports ($1.05M) rounded out the top three, both also in CS2. The first League of Legends market to appear in the top 10 was Karmine Corp vs. G2 Esports at $1.02M.

Kalshi is a prediction market platform where users trade contracts on the outcome of real-world events, including esports matches. Instead of traditional betting odds, Kalshi works like a market: you buy a “Yes” contract if you think a team will win, or a “No” contract if you think they won’t. Prices move based on supply and demand, and contracts settle at $1 if correct, $0 if not.

Therefore, the volume traded metric does not show us much beyond the “interest” in a market. It shows us how much collective money flowed into a certain match. For example, a match with $1 million in volume simply means that $1 million of contracts changed hands on that outcome. It is not, therefore, a measure of how much anyone won or lost. A person could buy a position at $0.01 and thus, they have not actually wagered $1.

High volume on a match means a lot of traders were interested in that outcome, it could reflect a high-profile fixture, two evenly matched teams, or simply that the match fell at a popular time. It does not tell us who the market thought would win, nor does it tell us how much individual traders made or lost.

Volume is the best measure we have from this data for gauging which matches captured the most attention on Kalshi each week.

However, there could also be a myriad of other factors that explain the volume on esports. Esports is known for its data latency, and there have been public examples of people coding bots to take advantage of data lag to take out positions that the typical fan, and thus market, has not reacted to. Future pieces will look to explore this phenomenon.