Kayode Makinde, Oluwatimileyin Onasanya, Frances Adelakun
7 min
This paper rigorously tests whether following popular Nigerian sports betting influencers on social media is a smart financial move. By tracking thousands of real bets from top tipsters, it uncovers a stark reality: these influencers lose money on their tips, and followers fare even worse. The study highlights how affiliate commissions—not winning bets—drive influencers' flashy lifestyles, raising alarms for consumer protection in Nigeria's booming, poverty-fueled gambling market.
Nigeria's sports betting scene has exploded due to mobile tech and economic hardship, with influencers on X (Twitter) and Telegram amassing millions of followers. They share 'sure wins' and luxury displays, but the paper reveals this masks poor performance and misaligned incentives.
Influencers cherry-pick winning bets ('roll-overs') for visibility, creating survivorship bias—followers see only successes, ignoring losses. To counter this, researchers tracked all 5,467 pre-match betting slips from three top tipsters (@mrbanks, @louiedi13, @bossolamilekan1) over two years (July 2023–August 2025). Using public Stake.com links, they verified outcomes, standardized currencies to USD, and cleaned data (e.g., excluding odds ≤1.00). This yielded $4.8M in bets with bookmaker payout rates (Stake.com: 93.21%, near Nigeria's 92.95% average).
Key finding: Influencers lost 25.24% on promoted slips. Followers using flat staking lost 38.27%; other strategies (Inverse, Square Root, Fixed Return) also led to heavy losses.
Influencers monetize via affiliate commissions, not tip quality. Stake.com's formula is:
The 3% platform edge ensures steady payouts regardless of wins/losses, rewarding volume and recruitment. With 4.7M collective followers, this incentivizes constant betting hype, even unprofitable tips. Luxe images (cars, homes) mislead followers into thinking wealth comes from betting skill.
Analysis broke down bets by risk (odds size) and simulated follower outcomes. Low win rates (~20%, per prior studies like Houghton & Moss 2023) deplete capital 12-20%. High-odds 'parlays' amplify variance but not profits. No strategy salvaged profitability—followers always lost more than influencers, as tips underperformed market odds.
Nigeria's National Lottery Act (2005) bans fraud/underage gambling but doesn't mandate marketing betting as entertainment, not income. Amid poverty, influencers portray it as an escape, exploiting social media's reach. Findings urge reforms: transparency on commissions, bias warnings, and volume-deterring rules to protect vulnerable bettors.
Why it matters: First large-scale, bias-free study in an emerging market, generalizable via Stake.com data. It demystifies influencer 'success,' equipping students with tools to spot biases, incentives, and risks in social media finance advice.
This study examines whether following popular Nigerian sports betting influencers on social media is a financially sound strategy. To avoid the survivorship bias that occurs when influencers only share their winning bets, we tracked 5,467 pre-match betting slips from three prominent tipsters on X (formerly Twitter) and Telegram. We verified the outcomes against official Stake.com records, resulting in a final dataset covering approximately $4.8 million in tracked bets. We analyzed raw performance, assessed risk based on odds sizes, and applied four common staking strategies (Flat, Inverse, Square Root, and Fixed Return) to simulate realistic follower outcomes. The results show a sharp contrast between the wealth these influencers display online and the actual financial results. The influencers themselves collectively lost 25.24% on their promoted bets, while a follower who staked the same amount on every tip would lose 38.27% on their investment. Across all tested strategies, following these influencers consistently led to significant financial losses. These findings raise serious consumer protection concerns in Nigeria's expanding gambling market.
Alex: So no junk skewing the picture. Did they break down the bets by risk level, like safe versus long-shot odds?
Sam: Yes—odds show the potential payoff multiplier if you win. Low under ten means safer bets with smaller wins, like picking a strong favorite team. Medium from ten to a hundred covers most tips, and over a hundred are rare high-risk shots. About half fell in medium, matching what followers chase for big returns. High-odds bets rarely hit, dragging overall results down—like betting on a video game underdog that almost never pulls off the upset.
Alex: That setup explains the follower hit harder than influencers.
Alex: You've mentioned simulations showing followers lose up to 38 percent. What do those reveal about whether the tips are just poorly picked, or if even smart money handling can't save them?
Sam: The study tests that by running the full set of bets through four common ways to decide bet sizes—called staking strategies. Think of it like portioning snacks at a party: do you grab the same handful every time, or adjust based on how tasty they look? One basic approach is flat staking: you bet the same fixed amount every time, like always risking $10 per game. It acts as a simple baseline to measure raw tip quality.
Alex: So flat staking ignores the odds and just copies the influencer's bet size equally. But if that still loses money, the tips aren't strong enough on their own?
Sam: Correct. They also tried inverse staking: bet more on safer, low-odds picks and less on risky high-odds ones—like putting $20 on a likely win but just $1 on a long shot. A milder version, square root staking, softens that. The last, fixed return staking, works backward: decide on a target profit, say $10 per win, then size the bet to hit that—like dividing $10 by the odds minus one.
Alex: Those make sense as ways to manage risk without changing the tips. So applying them—what did the numbers show?
Sam: Payouts averaged less than three-quarters back, with a win rate around 10 percent. Influencers' raw results showed a 25 percent capital loss. Even with the best staking tweaks, followers ended up around 38 percent worse, proving poor predictions drive the drain, not just sizing. A statistical tool called ANOVA confirmed clear differences among strategies, showing the choice matters for how fast money drains—but no solid difference between influencers, all around that 25 percent drop.
Alex: That pins it on the tips failing more than on how followers bet.
Alex: You've tied it to high-odds bets dragging results down. Can you break down how those odds categories performed?
Sam: Low odds lost about 10 percent of stakes on average—like safer picks that still don't quite pay off enough. Medium—the most common at half the bets—barely covered costs long-term. High odds wiped out 74 percent, showing why chasing big wins destroys bankrolls. The three main influencers varied slightly: losses of 9 percent, 21 percent, and 27 percent—adding to that overall 25 percent across 4.8 million dollars bet.
Alex: So even the safer bets lose, but the popular medium ones set false hopes—and none of the influencers profited from the bets themselves.
Sam: Exactly—platforms pay influencers a cut, often around 10 percent of what followers wager through their links, on top of the site's edge. It rewards driving more bets and sign-ups, regardless of wins, so volume trumps accuracy.
Alex: In Nigeria, with poverty pushing betting as a "career," that setup sounds risky without rules.
Sam: Yes, Nigeria's 2005 lottery law treats gambling as entertainment but doesn't require influencers to disclose affiliates or warn of risks. The paper flags this gap and calls for protections like clear warnings and disclosures.
Alex: Sam, pulling this all together—what does the full picture say about whether following these influencers actually builds wealth?
Sam: The study gives a clear no. Influencers saw a 25 percent loss on their picks, while followers using standard approaches lost up to 38 percent. No staking method or tipster turned that around—the predictions simply don't hold up. The flashy lives point to affiliate commissions as the real driver. But the study notes limits: it focuses on Stake.com, missing local sites, and tracks only three big influencers.
Alex: Solid baseline evidence, with room to expand. This really highlights how data cuts through the online hype. Thanks for diving into this with me, Sam.
Sam: A meaningful step in showing affiliate models reward volume over value, urging protections to shield vulnerable bettors. That's the core takeaway from Makinde and colleagues' work. Thanks for listening to ResearchPod.