Markets
|13 min ReadHow Polymarket’s Sports God Blew Four Million
Maya Chen
Senior Analyst
Published
Jan 16, 2026
Alpha Briefing: A Polymarket sports trader known as “Mayuravarma” turned roughly 5,000 dollars into nearly 4 million on sports and esports markets, then vaporized almost everything in about a week after an 11-trade losing streak. His rise and collapse show how “sure thing” end-of-market strategies, oversized bets on favorites, and the illusion of safety in prediction markets can turn paper riches into ruin in record time.
On Polymarket, prediction markets look like a game for the many. In reality, they are a feast for the very few. Most people provide liquidity and emotion. A handful of whales harvest the edge. And in sports markets, where upsets are built into the DNA of the game, even the “gods” can die overnight.
This is the story of “Mayuravarma,” a trader who was briefly worshiped as Polymarket’s “sports prediction god.” In about a month, he turned roughly 5,000 dollars into around 3.8 million dollars, a 760x run that put him near the top of the site’s profit rankings for sports. Then, in about a week, an 11-trade skid and a series of all-in bets nearly erased it all.
His arc is a brutal reminder: on Polymarket, the “sweep the final odds” strategy is not free yield. In sports, the last-minute “certainty” is often an illusion. What you are really putting on the line is not a few easy percentage points. It is your entire stack.
From LOL Side Action To “Sports Prediction God”
Mayuravarma’s public trail starts in esports. He began his prediction-market journey on the League of Legends World Championship. According to his Polymarket profile, he placed nine bets across the S15 Worlds, winning six and losing three for a win rate around two-thirds.
The raw results are staggering. Across those LOL markets, he reportedly ended down about 20,000 dollars on some legs but still cleared close to 790,000 dollars in overall profit. Two trades stand out.
In the AL vs T1 match, he put 150,000 dollars on the line and walked away with 162,500 dollars. In the KT vs T1 final, he bet 1.1 million dollars and booked nearly 600,000 dollars profit. These are not degen scratch tickets. These are whale-sized convictions.
After that taste of blood, he expanded fast. From LOL, he moved into the big American sports circuits: college football (CFB), the NHL, the NBA, the NFL and more. Early on, the run looked unstoppable. In five college football games and two NHL matchups, multiple entries on the same markets produced returns between roughly 30 and 82 percent, with his best single profit around 360,000 dollars.
The style was clear. He preferred pre-game positions. Size ranged from a few thousand dollars to hundreds of thousands. He almost never sold mid-game. That discipline made it possible to “ladder up” from small capital into huge size. It also set up the catastrophe that came later, when he started firing million-dollar bullets with the same mentality.
Two NHL trades show how thin the line was.
In an early Wild vs Rangers game, he backed the Rangers at roughly 57–43 odds and lost 275,000 dollars. Later, in another NHL market, he bet on the Devils, again fading the Wild, and made about 86,000 dollars on less than 120,000 dollars risk. Same league. Same kind of matchup. Completely different outcomes.
Then came the big one. In a Wild vs Penguins game, he fired 1 million dollars on the Penguins, the pre-game favorite. The Wild blew them out 5–0. The entire million was gone.
He also dipped into the NBA. In two early games, he correctly backed the Warriors over the Lakers, making nearly 100,000 dollars on one of them. On paper, his win rate in basketball sat at 50 percent, but the size of his winners kept him ahead.
Across LOL, NHL, NBA and college football, the pattern was consistent. He favored favorites. He bet on the stronger teams, not Cinderella upsets. That implied he followed the sports closely and trusted the market’s implied probabilities. It also meant his entire strategy depended on a world where favorites mostly behave like favorites.
But sports are sports. The ball is round. A single own goal, a rogue penalty, a freak bounce off the post, a star injury, a referee error, and the “safe” side goes to zero. In a prediction market designed for binary outcomes, every surprise is a total wipeout for someone.
When Money Turns Into Numbers On A Screen
As his streak developed, his position sizes exploded. The early bets were two thousand dollars here, five thousand there. Soon it was thirty to fifty thousand per game. Then 100,000 dollars became a normal unit of risk.
In less than a month, the “newbie” became a certified whale. Other Polymarket players tracked his moves, studied his entries, and gave him the “sports prediction god” label.
Across one key stretch of 24 events, his stats looked almost textbook.
He went 12–12 on individual markets, a 50 percent hit rate. On the losing side, he staked about 840,000 dollars across those 12 losses and lost it all. On the winning side, he booked roughly 1.64 million dollars. Profit was about 1.95 times losses. The biggest two single-game losses were NBA bets, each costing just over 100,000 dollars. The biggest win came from an NHL game between the Bruins and the Senators, where he put 992,000 dollars at risk and walked away with more than 607,000 dollars profit.
Overall, that phase was “lose small, win big.” Even better, there were flashes of genuine risk control. In an NBA game between the Jazz and the Blazers, he cut a 20,000-dollar position quickly, losing less than 300 dollars. For a full-send whale, that was a rare example of professional-grade stop-loss discipline.
Then he found the groove again. Over the next 12 matches, he lost only three. Nine went his way.
That is when he hit his individual peak: a college football game between Houston and UCF. He put 745,000 dollars behind his view and earned about 687,000 dollars on the trade, a 92 percent return. Out of 108 recorded bets, that was his single largest profit.
Then, like a high-flying altcoin after a new all-time high, gravity hit.
In the next cluster of 10 games (11 including the one before), his luck snapped. He racked up 10 straight losses. Total damage: around 2.05 million dollars.
Most of the damage came from the NHL. Eight of those 11 losing bets were hockey. That matters, because NHL upset rates hover somewhere around 30 percent, the highest of the major U.S. leagues and notably higher than the NBA, MLB, or NFL. Betting large on favorites in a league built on volatility is asking for trouble. For him, it was the beginning of the end.
From Cautious Favorite-Backer To All-In Gambler
After that ugly streak, LOL returned as his lucky charm. Backing T1 to win the S15 Worlds title netted him another 600,000 dollars. The account stabilized. Results turned into a mix of wins and losses again.
But something had changed. Once you get used to seeing six and seven-figure swings in your PnL, money stops feeling like money. It becomes numbers. Units. Chips.
His size crept even higher. Instead of “just” six figures, he started flinging 300,000 to 500,000 dollars at markets. He even put 1 million dollars into bets with only about 30 percent upside. The trader who once prided himself on being conservative and backing only the strongest sides was now breaking his own rules.
When a player moves from “carefully betting on favorites” to “I want to win and I want to win big, now,” the market usually responds with one answer: punishment.
One Month To Glory, One Week To Oblivion
At his peak, around mid-month, his profit curve was beautiful. In roughly four weeks of activity, his account PnL went from about 7,000 dollars in gains to nearly 3.9 million dollars. For a moment, he was the king of sports markets.
Then the hammer fell.
In a college football matchup between Texas State and Southern Miss, he staked 1.2 million dollars on Southern Miss to win. They lost. The entire 1.2 million was wiped out.
In an NHL game between the Capitals and the Canadiens, he went all in again. Another 1.2 million went on the “safer” Canadiens at attractive pre-game odds. He never stopped out. The bet went to zero. In about a week, his total PnL flipped from up nearly 3.8 million dollars to down around that same number.
After that roller coaster, he deleted his X account in frustration. The screenshots of his disappearance made the rounds in the Polymarket community.
He was not done yet, though. Not willing to be remembered as just a cautionary meme, he wired in another 1 million dollars and returned to the arena. The new chapter looked exactly like the old one. More sports bets. More losses than wins.
By the time this episode was documented, his Polymarket profile showed cumulative losses around 885,000 dollars and open positions worth roughly 278,500 dollars. That means he not only gave back every dollar of his prior profit. He was also down hundreds of thousands on original capital.
In sports prediction markets, just like in leveraged futures, there are only two binary outcomes on each ticket. One side wins. One side loses. With limited choices and no partial payout at settlement, prediction markets can be even more ruthless than margin trading. Many people cannot bring themselves to cut a bet early. They wait for the final whistle or hope for the late upset. By the time reality hits, the entire stake is gone.
With automated resolution and winner-takes-all payouts, the cruelty is very clean.
IDs, Myths And The Fate Of A “Peacock King”
Prediction markets always attract a layer of mysticism. Even a trader’s handle starts to feel like a spell.
We saw that before with “fengdubiying,” the Chinese Polymarket legend whose ID basically reads “always win when betting.” Mayuravarma’s name carries its own mythology.
In Sanskrit, “Mayura” comes from “मयूर,” meaning “peacock,” a symbol of beauty and divinity in Indian culture. “Varma” or “Varman” stems from “वर्मन्,” meaning “protector” or “armor,” often associated with noble or warrior castes. The suffix appears in southern Indian noble families, linked to the idea of a protector role.
On his Polymarket profile he even referenced the Kadamba dynasty, an ancient Indian kingdom whose founder, Mayurasharma, is tied to peacock symbolism. The name loosely translates to “protector of the peacock,” combining warrior class identity with nature worship.
It is a tremendous story. A “peacock king” stepping into prediction markets, guarding his growing fortune with sharp reads on games across continents. But like the old dynasty he echoes, his reign did not last.
In the roaring, always-on world of Polymarket, he will be remembered as one sharp, volatile datapoint. A man who built a fortune in a month and lost it in a week.
Other “instant legends” are already grinding away, hoping to be the next name that turns a few thousand dollars into millions on Polymarket’s sports and political markets. Many more will follow the same arc he did, rising fast, going all in, and blowing up. Just like the heavily memed contract trader “Machi Big Brother” on centralized futures platforms, Mayuravarma will not be the first or the last to fall.
Disclaimer: This document is intended for informational and entertainment purposes only. The views expressed in this document are not, and should not be taken as, investment advice or recommendations. Recipients should do their own due diligence, taking into account their specific financial circumstances, investment objectives and risk tolerance, which are not considered here, before investing. This document is not an offer, or the solicitation of an offer, to buy or sell any of the assets mentioned.