💻 computer science

The Statistical Profitability of Social Media Sports Betting Influencers: Evidence from the Nigerian Market

This study analyzes over $4.8 million in betting data from Nigerian social media influencers and finds that following their tips results in significant financial losses for both the influencers and their followers, highlighting serious consumer protection concerns in the country's gambling market.

Original authors: Kayode Makinde, Oluwatimileyin Onasanya, Frances Adelakun

Published 2026-04-10

📖 4 min read☕ Coffee break read

CC BY 4.0

Original authors: Kayode Makinde, Oluwatimileyin Onasanya, Frances Adelakun

Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Imagine a group of people on social media who act like glamorous tour guides for a dangerous jungle called "Sports Betting." They wear expensive suits, drive luxury cars, and post photos of huge piles of cash, telling their millions of followers, "Follow my map, and you'll get rich too!"

This study is like a team of detectives who decided to stop listening to the tour guides' sales pitch and instead followed the actual path they walked. They tracked every single bet these guides made over two years, checked the real receipts, and did the math.

Here is the story of what they found, explained simply:

1. The "Highlight Reel" Trap (Survivorship Bias)

The influencers are like a magician who only shows you the tricks that work. They post the one time they won a million dollars, but they quietly delete the 99 times they lost everything.

The Study's Move: Instead of looking at the influencers' highlight reels, the researchers built a "black box" recorder. They captured 5,467 bets the moment they were posted, before the games even started. This meant they saw the losses, not just the wins.

2. The "Magic" Money Machine

The researchers followed three of Nigeria's biggest betting influencers (who have over 4.7 million followers combined). They tracked about $4.8 million in bets.

The Result: The influencers themselves lost 25% of their money.
The Follower's Reality: If an average person had blindly copied these influencers, putting the same amount of money on every tip, they would have lost 38% of their investment.

The Analogy: Imagine you hire a chef who claims to be a master. You watch them cook 100 meals. They show you the one perfect steak they made. But when you check the kitchen logs, you find out they burned 75 meals and ruined 25. The "chef" isn't rich because they are a great cook; they are rich because they get paid a commission by the restaurant every time you order a meal, regardless of whether the food is good.

3. The "Moonshot" Illusion

The study looked at what people were betting on.

Safe Bets: Betting on a team that is very likely to win (Low odds).
Moonshots: Betting on a "long shot" where the odds are 100-to-1 or even 1,000-to-1. These are like buying a lottery ticket hoping to win the jackpot.

The influencers pushed these "Moonshots" hard. The study found that chasing these huge payouts is a financial disaster. For every $100 bet on these high-risk "moonshots," followers lost an average of $74. It's like trying to cross a canyon by jumping on a trampoline that is broken; you might make it once, but eventually, you fall.

4. Does a Better Strategy Help?

The researchers asked: "What if the followers were smarter with their money? What if they used fancy math to decide how much to bet?"
They tested four different money-management strategies (like betting the same amount every time, or betting less when the odds are risky).

The Verdict: No matter how smart the money management was, everyone still lost money.
The Metaphor: It doesn't matter if you drive a Ferrari or a bicycle; if you are driving off a cliff, you are going to crash. The influencers' tips were simply bad enough that no amount of careful driving could save the passengers.

5. The Real Source of Wealth

So, why are these influencers so rich if they lose money betting?

The Secret: They aren't paid for being right; they are paid for getting you to bet.
The Deal: The betting companies pay the influencers a commission (a kickback) every time a follower signs up or places a bet. The more the followers bet, the richer the influencer gets. It doesn't matter if the followers win or lose; the influencer gets paid either way.

The Big Takeaway

This study is a giant "Stop Sign" for anyone thinking sports betting is a way to get out of poverty.

The Image: Social media shows a life of luxury and easy wins.
The Reality: The math shows that following these "gurus" is a guaranteed way to lose your savings.

The Lesson: Don't trust the tour guide who is selling you a map to gold when their real job is just selling you tickets to the ride. In Nigeria, and everywhere else, sports betting should be treated as entertainment (like buying a movie ticket you expect to lose), not as a career or an investment strategy.

1. Problem Statement

The study addresses a critical socio-economic issue in Nigeria's rapidly expanding sports betting market: the financial viability of following "betting influencers" on social media platforms (X/Twitter and Telegram).

The Core Issue: Influencers often display luxurious lifestyles, leading followers to believe their wealth stems from successful betting predictions. However, these influencers primarily monetize through affiliate marketing, earning commissions based on the volume of bets placed by followers rather than the accuracy of their tips.
Survivorship Bias: A major methodological challenge is that influencers typically only share winning tickets ("survivorship bias"), obscuring their actual loss rates.
Research Gap: While anecdotal evidence and global studies suggest betting tips are unprofitable, there was no localized, empirical data quantifying the actual financial impact of Nigerian influencers on their followers.

2. Methodology

The researchers employed a rigorous, data-driven approach to eliminate survivorship bias and simulate real-world follower outcomes.

A. Data Collection & Selection

Subjects: Three prominent Nigerian tipsters were selected based on their massive reach (combined 4.7 million followers): @mrbanks, @louiedi13, and @bossolamilekan1.
Data Extraction: Instead of relying on self-reported wins, the team built a system to scrape the entire message history of the influencers' Telegram channels and X accounts.
Verification: They extracted 5,467 pre-match betting slips shared before events started. Each slip was verified against official Stake.com records to confirm stakes, odds, and final payouts.
Dataset Scale: The final dataset covered approximately $4.8 million in tracked wagers over a two-year period (July 2023 – August 2025).

B. Platform Generalizability

Stake.com Justification: Stake.com was used because it allows public verification of bet details via URL.
Validation: The authors compared Stake.com's average payout rate (93.21%) against seven other major Nigerian bookmakers. The difference was negligible (+0.26% from the market average), confirming that findings from Stake.com are generalizable to the broader Nigerian market.

C. Data Preprocessing

Currency Standardization: All bets (USD, CAD, NGN) were converted to USD using fixed August 2025 exchange rates.
Filtering: Bets with odds $\le$ 1.00 (voided/canceled events) were excluded (<0.4% of data).
Odds Categorization: Bets were segmented into three risk categories:
- Low Odds: < 10
- Medium Odds: 10 – 100
- High Odds: > 100 ("Moonshots")

D. Simulation Models

To test if money management could salvage profitability, the study simulated four staking strategies against the raw data:

Flat Staking: Fixed amount per bet.
Inverse Staking: Stake inversely proportional to odds ( $S = C/O$ ).
Square Root Staking: Stake proportional to the square root of odds ( $S = C/\sqrt{O}$ ).
Fixed Return (Target Profit): Stake calculated to guarantee a specific profit margin ( $S = P / (O-1)$ ).

3. Key Results

A. Descriptive Statistics & Win Rates

Win Rate: The overall win rate across all 5,467 bets was a mere 10.39% (568 wins).
- @mrbanks: 6% win rate.
- @louiedi13: 10% win rate.
- @bossolamilekan1: 24% win rate (highest, but still low).
Capital Depletion: The median payout was $0.00, indicating the vast majority of bets resulted in a total loss of the stake.

B. Profitability Analysis

Influencer Performance: Even the influencers themselves lost money on their promoted bets.
- Collective Net Loss: -25.24% (Capital Loss).
- Individual losses ranged from 9.30% to 26.60%.
Follower Simulation: A follower blindly following these tips with a flat stake would suffer a 38.27% loss on their investment.
Odds Analysis:
- Low Odds (<10): ~10% loss.
- Medium Odds (10-100): Consistent losses, failing to exceed initial stakes.
- High Odds (>100): Catastrophic risk, resulting in an average 74% loss of initial stake.

C. Impact of Staking Strategies

Applying advanced money management strategies (Inverse, Square Root, Fixed Return) did not generate profit.
While strategies like "Fixed Return" slowed the rate of capital depletion, all four strategies resulted in a negative Return on Investment (ROI).
ANOVA Testing:
- Staking Strategy: Statistically significant difference in the rate of loss ( $p < 0.05$ ), but no strategy produced a profit.
- Tipster Choice: No statistically significant difference in outcomes between the three influencers ( $p = 0.1246$ ). Following any of them leads to the same systemic loss.

4. Key Contributions

Elimination of Survivorship Bias: By scraping full message histories and verifying against a third-party platform (Stake.com), the study provides the first unbiased, empirical dataset of influencer performance in the Nigerian market.
Quantification of the "Affiliate Model" Risk: The study mathematically demonstrates that the influencers' business model (volume-based commissions) creates a conflict of interest where their financial incentive is to keep followers betting, regardless of prediction accuracy.
Strategy Inefficacy Proof: The research proves that even with optimal mathematical staking strategies, the underlying predictive accuracy of these influencers is too poor to overcome the bookmaker's margin.
Risk Categorization: It quantifies the specific danger of "moonshot" bets (>100 odds), showing they destroy capital at a rate of 74%.

5. Significance and Implications

Consumer Protection: The findings challenge the narrative that sports betting is a viable career or investment path in Nigeria. The "wealth" displayed by influencers is likely derived from affiliate fees, not betting profits.
Regulatory Urgency: The study calls for the National Lottery Regulatory Commission (NLRC) to enforce strict disclosure mandates. Influencers must be legally required to disclose affiliate partnerships and market gambling strictly as entertainment, not as a trade.
Financial Literacy: There is an urgent need to educate the public on "survivorship bias" and the mathematical reality of high-odds accumulators.
Policy Recommendation: The paper suggests adopting frameworks similar to the UK Gambling Commission's LCCP to ensure transparency and protect vulnerable populations from systemic financial erosion.

Conclusion: Following Nigerian sports betting influencers is statistically guaranteed to result in significant financial loss. The disparity between the influencers' projected lifestyles and the mathematical reality of their tips suggests a systemic exploitation of followers driven by affiliate marketing incentives rather than predictive skill.