Overview

In a move that could reshape the landscape of sports betting, the unions representing players from the NBA, NFL, MLB, NHL, and MLS have formally called on the Commodity Futures Trading Commission (CFTC) to ban prediction markets from allowing bets on a player's underperformance or injury. These so-called 'under' bets, offered by platforms like Kalshi and Polymarket, have sparked concerns about athlete safety, harassment, and the integrity of professional sports. This tutorial breaks down the issue, the regulatory process, and what it means for athletes, bettors, and the sports industry.

Prerequisites

Before diving into the step-by-step analysis, it helps to understand a few key concepts:

• Prediction markets – platforms where users bet on the outcome of future events (e.g., political elections, sports stats).
• 'Under' bets – wagers that a player will fall short of a specified performance metric (e.g., under 20 points, under 5 rebounds) or that an injury will occur.
• CFTC – the U.S. agency that regulates futures and options markets, which has jurisdiction over certain prediction markets deemed to be derivatives.
• Sports unions – labor organizations that collectively bargain on behalf of professional athletes.

No prior legal or betting expertise is required – just a curiosity about how rules are made and why athletes are sounding the alarm.

Step-by-Step Guide: Understanding and Navigating the Debate

Step 1: Identify the Core Issue

The controversy centers on prediction markets that allow bets on whether a player will perform below a certain statistic (e.g., “LeBron James under 25 points”) or suffer an injury. Unions argue these bets encourage harassment of athletes and their families, as dissatisfied bettors may target players with abusive messages or even threats. The letter to the CFTC requests a ban specifically on “under” bets (as opposed to “over” bets) because they create perverse incentives to root against an athlete’s well-being.

Step 2: Understand the CFTC’s Role

The CFTC issued a request for comment on how to regulate prediction markets like Kalshi and Polymarket. These platforms operate under a CFTC no-action letter or similar exemptions, but their growth has raised questions about consumer protection and market manipulation. The unions’ letter is a direct response to that request. Learn more about the unions' arguments in Step 3.

Step 3: Analyze the Unions' Arguments

The key points from the unions’ letter include:

• Protection from harassment – “Under” bets create financial incentives for bettors to harass players who are underperforming or injured.
• Integrity of competition – Such bets could lead to match-fixing or players being pressured to underperform.
• Need for regulation – The CFTC should impose “appropriate regulations” to safeguard athletes and their families.

The unions also argue that allowing bets on injuries crosses a moral line, turning personal misfortune into a profit opportunity for others.

Step 4: Examine Potential Outcomes

If the CFTC agrees to ban “under” bets, prediction markets would need to remove those contracts. Alternatively, the CFTC could impose stricter oversight, such as limiting the types of events that can be wagered on, requiring transparency, or mandating cooling-off periods. A less likely outcome is a complete shutdown of prediction markets, though that would require new legislation.

Step 5: Consider Broader Implications

• For athletes – Reduced harassment risk and less stress about personal performance being monetized negatively.
• For sports leagues – Potential backlash from fans who enjoy betting; leagues may need to distance themselves from platforms.
• For bettors – Fewer betting options, but possibly a safer, more ethical market.
• For regulators – A precedent for how to handle emerging prediction market categories.

Hypothetical Code Example (for illustration)

While this guide doesn’t involve actual software, consider how a prediction market might model an “under” bet in pseudocode:

class PredictionMarket:
    def place_bet(self, player, stat, threshold, direction):
        # direction can be 'over' or 'under'
        if direction == 'under':
            # Check if player's real stat < threshold
            if get_player_stat(player) < threshold:
                payout = bet_amount * odds
        # ... validation logic omitted

This abstraction shows that banning “under” bets would simply remove the conditional payout when the player’s stat is lower than the threshold.

Common Mistakes to Avoid

Mistake 1: Confusing “Under” Bets with Traditional Sports Betting

Traditional betting (e.g., on game outcome) doesn’t target individual performance. “Under” bets on a player’s stat line or injury are more personal and directly tied to an athlete’s well-being. Review Step 1 for clarity.

Mistake 2: Assuming All Prediction Markets Are Illegal

Many operate legally under CFTC oversight or exemption. The question is not legality but the scope of permitted contracts.

Mistake 3: Overlooking the Harassment Angle

Some people see this as merely a gambling issue, but the unions’ primary concern is athlete safety. Harassment from losing bettors is well-documented in sports.

Mistake 4: Thinking Only the US Is Involved

Though the CFTC is US-based, prediction markets are global. A US ban could influence international regulators.

Summary

The push by major sports unions to ban “under” bets on athlete performance highlights a growing tension between innovation in prediction markets and the need to protect players from abuse. By engaging with the CFTC’s request for comment, the unions are using the regulatory process to demand safeguards. The outcome could redefine what is permissible in sports wagering, with lasting effects on athletes, fans, and the betting industry. This guide has walked through the key issues, the regulatory landscape, and the arguments at play – equipping you to follow and participate in the debate.