Tennis to Trading: ‘BlondiePredicts’ Champions Women in Prediction Markets

The former tennis pro is an influential voice in the emerging prediction market industry, paving the way for other women entering the space.

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Prediction markets have exploded in popularity, but that meteoric growth conceals the troubling truth that women remain largely on the sidelines. About 13% of commodity traders in the United States are women. During the 2024 election, Kalshi released data showing that just 10% of its users were female.

Aggie AKA “BlondiePredicts” is determined to tackle that challenge head-on. She is a former professional tennis player who got into prediction markets through one of her friends, Evie “0xgingergirl,” who is founding her own prediction market company. Aggie sees prediction markets as more than hedging or forecasting instruments, but also potential commonplace social engagement tools.

“Whether you read stuff on Reddit or X or watch TikTok videos, you’re consuming some type of social media. And I think prediction markets and conviction markets, and all the variations of [them], are going to be part of our daily life, and everyone’s going to be using [them] in a few years. There’s going to be no way around it.”

Prediction markets as social media and accountability platforms

Aggie finds value in staking real money and also putting personal reputation on the line in forecasts. In her view, prediction markets are as much an accountability tool as they are forecasting methods.

“I think it’s not the goal to be right 100% of the time, because it’s just impossible. But it just makes people maybe be a bit more serious. They can just say things [but] if there’s a bet on it or money on it, they have to maybe do a little bit more research and dig a bit deeper.”

Real money and reputation are both valid ways to aggregate information. A 2004 study compared real-money and play-money markets. The authors found similar accuracy on topics outside of sports, theorizing that “real-money markets may better motivate information discovery while play-money markets may yield more efficient information aggregation.” Whether it’s through research or improved pricing mechanisms, prediction markets do have the potential to cut through punditry and certain types of bias.

“For me, [the most interesting question about traders] is what’s your decision-making?” Aggie said. “Do you research or do you just pick a trade? Then if your trade is going down, do you exit, or do you keep holding onto your beliefs?”

Women in prediction markets

Prediction markets could be an optimal way to bring women into commodity trading as well. The social aspect of trading creates possibilities for brands to post content that customers can engage with instead of passively consume. Aggie believes markets tailored toward female customers, even those without trading backgrounds, could help onboard more women to prediction market platforms.

“So for brands, instead of paying, let’s say, $10,000 to an influencer to make a post or create some content, all of a sudden, they can maybe put that into a liquidity pool, and then people can engage with it, whether they guess what’s the next limited release color for Lululemon or flavor of the smoothie at Erewhon.”

Given the large number of men in the prediction market industry, companies must put conscious effort into marketing to and onboarding women. These efforts are uneven across platforms, though.

“All the smaller ones [platforms] are just trying to make their product and launch it and get people to talk about it. And then maybe eventually one day they’ll be like, ‘Okay, yeah, we should try to get like the other half of the population in as well.’”

Aggie has already taken early steps to create spaces for women in the prediction market industry. She’s the admin of the X group “Women in Prediction Markets,” which is a dedicated space to welcome women into the prediction market industry and provide support for those who join. So far, its posts include articles about how to bring more women onto prediction markets. It’s an early space for the industry to figure out how platforms can better appeal to female traders and women who are brand new to prediction markets.

The crypto opportunity and barrier to entry

The prediction market industry is comprised of regulated platforms like Kalshi–and soon, Polymarket–to crypto platforms like Limitless, Melee, and PNP Exchange. Younger women are generally more comfortable with speculative assets like event contracts and cryptocurrencies than older generations. Younger generations are also more familiar with navigating crypto wallets and DeFi platforms. Aggie believes both crypto and fiat-based platforms have a role to play, but she sees onboarding new audiences—especially women—as easier to achieve off-chain.

“I’ve tried to look at other apps, and they’re like, ‘You have to create this, and then that.’ They don’t accept that wallet, and [users] have to connect it and make it, and it’s like, do you transfer money? Do you just add there? So, I think for non-crypto people, it’s just an additional hurdle.”

Not all projects in crypto are equally valuable, either. Businesses that improve fractional trading or specialize in markets embedded in social media have great potential. Pepe the Frog tokens don’t solve a problem or address a market need. Aggie awaits the trimming of projects behaving more like slot machines than companies.

“I definitely think we just need a few important tokens or coins. We don’t need shit coins and meme coins…We don’t need more coins. We need something more like centralized in a decentralized world…[We need to] find some type of balance that’s not 500,000 million things, but ‘Okay, these are maybe your five choices.’”

When the prediction market industry consolidates, traders will be left with a few reputable platforms that offer a wide range of markets and features. Streamers will be able to embed prediction markets in their live chats, and either split or merge their yes/no contracts.

Some of these features may be limited to free-to-play markets. However, Aggie’s vision of ubiquitous prediction markets, and a more inclusive trading community, seems well within reach.

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