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The Lab · Staking systems

Does Fibonacci staking work?

The gentler cousin of the Martingale: stake 1, 1, 2, 3, 5, 8 units on every favourite, one step deeper per loss, reset on a win. Run over 27,355 real GB races it shows +5.49%, the most interesting near-miss on the board, and the profit lives entirely in a handful of monster bets no real bankroll could place. The full story, then the honest data.

Doesn't workTested on 27,355 racesPaper ROI vs peak stake: +5.49% at 6,765 units
18+ onlyResearch output, not adviceMethodology open · losses visible

Our in-house model lost 16.8% ROI on the pre-registered Oct-Nov 2024 backtest window.

This page publishes what it predicts and tracks every result. We do this because nobody else does — the methodology is open, the losses are visible, the analysis is honest. The model output is presented as a comparison to the market, not as a recommendation to back, lay, or stake on any runner.

Read the full methodology in our in-house AI horse-racing model write-up. Track the running ledger on the Stablebet track record page.

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The verdict

No. The sequence shows +5.49% on paper, and the paper is the problem: it needed a 6,765-unit bet to climb out of a 19-race losing run. The profit belongs to a bankroll that cannot bust, which is no bankroll at all.

Updated 25 June 2026 · 26,839 races settledSee where this ranks against every system →

What this experiment settles

  • Does walking the Fibonacci sequence on every favourite come out ahead over a real, dated record of GB races?
  • What single stake did the sequence actually demand during its worst losing run, and could any real bankroll have placed it?
  • Why can a staking plan show a positive turnover-weighted ROI while still being unusable at the racecourse?

Methodology

Tested against the Stablebet betting-systems backtest, 27,355 GB races replayed in strict date order, favourites settled to industry SP. Returns measured to industry SP, flat £10 win on the model's top-rated pick per race unless stated. The underlying ledger and per-race results are public at /our-track-record/. For the detail, see how the AI model prices a race and how we settle every bet.

The story

The sequence came first, the staking plan much later. Leonardo of Pisa, the medieval mathematician better known as Fibonacci, set it out in his Liber Abaci in 1202, in a puzzle about breeding rabbits: each number is the sum of the two before it, so it runs 1, 1, 2, 3, 5, 8, 13, 21 and on forever. The sequence turned out to be one of the loveliest objects in mathematics. It hides in sunflower heads and snail shells, and the ratio between its neighbouring terms settles towards the golden ratio, the number artists and architects have chased for centuries.

Gamblers, being gamblers, saw a staking plan in it. The betting version works like the Martingale's more reasonable sibling: stake one unit, and after every losing bet step one place further along the sequence, so the stakes climb 1, 1, 2, 3, 5, 8. After a win, go back to the start. The climb is gentler than doubling, the recovery arithmetic still works on paper, and the whole thing carries that faint glow of natural mathematics, as if the same pattern that arranges a pine cone might arrange your betting bank.

Pascal brought it to the Lab with some confidence, and here is the honest twist that makes this the most interesting page on the board: when we replayed the plan over 27,355 real GB races, the headline number came back positive. And that positive number is precisely the mirage this page exists to take apart, because the profit sits in a handful of bets so large that no real bankroll could ever have placed them. The sequence that grows rabbits, it turns out, grows stakes exactly as fast.

Why everyone swears by it

The Fibonacci plan sells itself on one comparison: it is not the Martingale. Doubling after every loss is obviously reckless, everyone has heard how that ends, and the sequence looks like the grown-up alternative. Each step up multiplies the stake by roughly 1.6 rather than 2, so after five straight losses a Martingale wants 32 units where Fibonacci asks for a modest 8. Written out side by side, one column looks like a panic and the other looks like a plan.

Then there is the rhythm of it in practice, and this is the part that genuinely does feel good. The plan here backs the favourite, and the favourite obliges often, winning 34.8% of races in our record. So most sequences are short. You lose one, lose another, the favourite comes in, you reset to a single unit and bank a small recovery. Weeks can pass like that: little runs, little resets, the cumulative line ticking gently upward. The plan is doing exactly what its brochure promised, and every reset reads as proof that the mathematics is working.

And the mathematics itself is a quiet part of the sales pitch. A staking plan named after a casino feels like a hustle; one named after the pattern in a sunflower feels like wisdom. Punters who would never touch a doubling system will happily walk a sequence that Leonardo of Pisa wrote down eight centuries ago, because it carries a borrowed authority that plain arithmetic never gets.

The appeal, in short, is that Fibonacci softens everything: softer climbs, frequent resets, a respectable pedigree. What it does not soften, as the next section shows, is the one thing that decides the outcome. The climb is slower, but it is still exponential, and an exponential climb with a losing run underneath it always reaches the same place. It just arrives politely.

The catch

The catch has two layers, and the first is the losing run. Favourites win about a third of races, which means they lose about two thirds, and over 27,355 real races the bad stretches are not a theoretical risk, they are on the record. The worst of them ran 19 races without a single favourite winning. Walk the sequence through that run and the stakes go 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1,597, 2,584, 4,181, and then the plan asks for 6,765 units on one race. At a £10 base unit, that is a single bet of £67,650, placed by someone whose original idea of a bet was a tenner, with nineteen straight losers immediately behind it. No bookmaker would take it, and no sane person would place it. This is the same cliff the Martingale walks off; Fibonacci simply takes a few more steps to reach the edge.

The second layer is subtler, and it is what makes the headline figure a mirage rather than a lie. The +5.49% is turnover-weighted: total profit divided by total money staked. In a progression, the late-sequence bets are hundreds or thousands of times larger than the base stake, so those few monster bets dominate the average. The "profit" is not a gentle skim off 27,355 races. It is the outcome of a handful of enormous recovery bets that happened, in this particular replay of history, to land. The tens of thousands of ordinary one-unit and two-unit bets underneath are just the favourite's usual slow leak. The plan's result belongs almost entirely to bets that only a bankroll with no upper limit could have placed, and a bankroll with no upper limit is the one thing no punter has.

Professor Furlong with a losing betting slip at the Stablebet AI Lab
The Professor has run this one through the numbers before. It still loses.

How we tested it

The test is a full chronological replay, because a staking plan only means anything in the order history actually happened. Progressions live and die by the sequence of results, so unlike the flat-stake systems on the board, this one cannot be measured as a simple average over races. We lined up every qualifying GB race in our record, 27,355 of them, sorted strictly by date and then by off time, and walked the plan through them one bet at a time, exactly as a punter following it would have.

The rules were the plan's own. Back the favourite in every race. Stake in units along the Fibonacci sequence, starting at 1: after any race the favourite loses, step one place further along; after any race a favourite wins, reset to the start. Joint favourites split the stake between them, exactly as the board's other favourite systems handle them.

Settlement follows the Lab's standard honest conventions, the same ones behind the 24 systems on the leaderboard as of 25 June 2026: returns to industry Starting Price, non-runners voided and refunded, fallers and pulled-up horses counted as the losing bets they are, and every race required to have a recorded winner. Nothing about the settlement is softened for the staking plan; the only thing that changes from the flat-stake favourite system is how much goes on each bet. See how we settle every bet for the full conventions.

Two measurement notes, both of which matter for reading the result. The ROI is turnover-weighted: total net profit divided by total money staked, which is the only honest way to score a plan whose stakes vary enormously. And there is deliberately no confidence interval, because a single ordered staking path through history has no exchangeable resamples to bootstrap; you cannot shuffle a story and keep it the same story. What the path gives us instead is its shape, and the shape is the finding.

What the data showed

The numbers below are pulled live from the study file, so they update whenever the record is recomputed.

+5.49%
ROI, turnover-weighted
27,355 races
GB races, in date order
34.8%
favourite strike rate
6,765 units
peak stake demanded
19 races
longest losing run

Needs an unlimited bankroll — see why below.

Read the grid left to right and it tells the whole story in miniature. The turnover-weighted return is +5.49%, and on any other page of this Lab a plus sign would be the headline of the year. The favourite won 34.8% of the 27,355 races, which is why the plan spent most of its life resetting comfortably after short sequences. And then the last two tiles quietly explain where the plus sign came from: a longest losing run of 19 races, and a peak demanded stake of 6,765 units.

Hold those two figures together. A punter staking £10 units needed to put down £67,650 on a single race, having just watched nineteen favourites in a row get beaten, to stay on the path that produces the +5.49%. Miss that bet, or any of the monster bets on the other deep runs, and the paper profit is gone, because turnover-weighting means those few bets are where nearly all the money, and therefore nearly all the result, actually sits. The plan's fate was decided in a handful of moments of maximum absurdity, and history happened, this time, to be kind in those moments.

Strip the progression away and the underlying bet is one we have already measured. Backing every favourite flat to SP over this record returns -8.6%, a leak of −8.6p from every pound staked, and that page shows the loss is structural, built out of the bookmaker's margin. Fibonacci staking does not repair that leak; it wallpapers over it with escalating stakes until, in this replay, a few colossal winning bets happened to land on top. A different shuffle of the same results, one where a deep run arrives when the sequence is already stretched, ends in ruin instead. The favourite's margin is certain; the rescue is luck.

The verdict

So does Fibonacci staking work? No, and this page earns its place on the board precisely because the raw number says otherwise. The +5.49% is real arithmetic over real races, and it is the most interesting near-miss we have tested, a genuine curiosity worth understanding rather than a claim worth acting on. It exists only for an imaginary punter with a bottomless bankroll, a bookmaker willing to take a 6,765-unit bet from a losing account, and the iron nerve to place it after nineteen straight beaten favourites. Remove any one of those three fictions and the plan collapses into what it always was underneath: the favourite's steady leak of −8.6p per pound, dressed in a more elegant sequence than the Martingale wears.

The general lesson is the one every staking-plan page in this Lab keeps arriving at, from a different direction each time. Staking plans change the shape of your results, not their direction. A progression takes the favourite's small, certain disadvantage and repackages it: long comfortable stretches of small recoveries, paid for by rare moments where everything depends on a bet you cannot afford. Sometimes the repackaging even produces a positive paper number, as it did here, and the number is honest about the history and silent about the ruin required to collect it.

If Fibonacci tempted you because it felt more measured than doubling, the instinct behind that feeling is sound; the sequence is gentler. It is just not gentle enough, because nothing exponential is. The honest tools remain the dull ones: a flat stake you can afford, or a fractional Kelly if you genuinely hold a measured edge. And whether anything we test holds such an edge is a question we publish either way, losses included, in the track record, with the Martingale's fate sitting one page away as this plan's blunter twin.

Frequently asked questions

Does Fibonacci staking work in horse racing?
No, not in any way you could use. Replayed over 27,355 real GB races, staking the Fibonacci sequence on every favourite shows +5.49% turnover-weighted, and that figure only exists because the sequence was allowed to keep climbing to a 6,765-unit bet during a 19-race losing run. At £10 a unit that is a single £67,650 bet. Any real bankroll, and any real bookmaker limit, stops the system long before the bet that produces the recovery. The number is honest arithmetic and unusable advice.
How is Fibonacci staking different from the Martingale?
Martingale doubles after every loss; Fibonacci climbs the sequence 1, 1, 2, 3, 5, 8, 13, one step per loss, and resets on a win. The climb is slower, roughly 1.6 times per step instead of 2, so the stakes take longer to become absurd. That slower climb is exactly why it looks safer and why it fails the same way: the growth is still exponential, so a long losing run still demands a stake no one can place. It reaches the cliff edge later, and the cliff is the same height.
If the backtest shows +5.49%, why is the verdict that it doesn't work?
Because the ROI is turnover-weighted, which means the enormous late-sequence bets dominate the average. The profit is not spread across 27,355 races; it is concentrated in a handful of monster stakes placed at the bottom of long losing runs, including one of 6,765 units. Those are precisely the bets a real punter can never make, because the bankroll is gone or the bookmaker's maximum has long since been passed. Remove the unplaceable bets and you are left holding flat-ish stakes on the favourite, which loses -8.6% over the same record.
What bankroll would you have needed to survive the worst run?
During the longest losing run the sequence demanded stakes all the way up to 6,765 units on a single race. At a £10 base unit that is £67,650 for one bet, on top of everything already lost climbing to it. Start from £1 units and it is still a £6,765 bet to protect a system whose base bet is a pound. There is no sensible answer to the question, which is the finding: the plan's survival requirement grows without limit, and every real bankroll is a limit.
Doesn't the reset-on-a-win protect you? Favourites win about a third of the time.
It protects you often, and that is the trap. The favourite obliged on roughly 34.8% of races in this record, so most sequences reset within a few steps and the plan feels comfortable for months. But the plan's whole design concentrates its risk into the rare long run of losing favourites, and over 27,355 real races the long run duly arrived: 19 races without a favourite winning. A system that behaves beautifully until one bad fortnight is not protection, it is a delay.
Is there any staking plan that turns the favourite into a winner?
No. Staking plans reshuffle when you lose; they cannot change what the bets return. The favourite leaks −8.6p of every pound staked at SP, and no ordering of stake sizes alters that expectation. What a progression can do, as this page and the Martingale page show, is convert a steady small leak into a rare catastrophic one, and occasionally, as here, produce a paper ROI that only a bankroll with no ceiling could ever have collected.

What this experiment doesn't cover — and what we're testing next

  • Does the D'Alembert system, add one unit after a loss rather than climbing the sequence, survive any longer?
  • Does a capped Fibonacci, stopping after six steps and taking the loss, keep any of the paper profit?
  • Does the reverse ladder, climbing after wins instead of losses, fare any better?

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