How to Use Football Statistics to Find Winning Bets: The Complete Guide for Nigerian Punters

Why Do 85% of Nigerian Bettors Lose Money Consistently?

Before learning what works, understanding what doesn’t work is equally important. The betting industry thrives because most punters make predictable, avoidable mistakes. Bookmakers like Bet9ja, 1xBet, BetKing, and others aren’t charities — they’re businesses designed to profit from these errors. Recognising the traps helps you avoid them.

Betting on team names instead of current performance

Manchester United, Arsenal, AC Milan, Barcelona — these names carry weight. They evoke memories of past glories, legendary players, and trophy cabinets. But historical reputation has nothing to do with next Saturday’s match. A casual bettor sees “Man United vs Brentford” and instinctively backs United because of the name. A statistical bettor asks: what do the underlying numbers say about both teams’ current form?

Bookmakers know this bias exists. They shade their odds accordingly, making big teams worse value propositions than their actual probability of winning would suggest. The money flows predictably toward famous names, and bookmakers adjust to capture that flow. This is why consistently backing “big” teams against “small” teams is a losing strategy long-term.

Chasing losses with bigger stakes

You lose ₦5,000 on the early kickoff. Frustrated, you place ₦10,000 on the 4pm match to “recover.” That loses too. Now you’re down ₦15,000 and desperate, so you put ₦20,000 on the evening game. This emotional spiral has destroyed more bankrolls than any bad tip ever could.

The mathematics of chasing losses are brutal. You’re not making rational decisions based on value — you’re making emotional decisions based on a desire to return to breakeven. These are completely different things. The match you chase rarely offers genuine value; you’re betting because you need to bet, not because the opportunity is good.

Over-reliance on accumulator bets

The dream of turning ₦1,000 into ₦500,000 with a 20-match accumulator bet is incredibly seductive. Social media is full of screenshots showing massive wins from small stakes. What you don’t see are the thousands of failed accumulators for every one that lands.

Each selection in an accumulator multiplies the bookmaker’s edge. A single bet might face a 5% margin. A five-fold accumulator faces roughly 25%. A ten-fold faces 50% or more. The odds look attractive, but they’re mathematically stacked against you far more heavily than single bets. Occasional accumulators for entertainment are fine, but they shouldn’t be your primary betting strategy.

Misunderstanding what “value” actually means

Many punters think “value” means backing an underdog at high odds. That’s not it. Value exists when the true probability of an outcome is higher than the implied probability of the odds offered. A 1.30 favourite can offer value if they should really be 1.20. A 5.00 underdog offers no value if their true odds should be 8.00.

Finding value requires estimating probabilities more accurately than the bookmaker’s odds suggest. This is where statistics become essential — they provide an objective basis for probability estimation beyond “I think” or “I feel.”

What Is Expected Goals (xG) and How Does It Transform Your Betting?

Expected Goals, universally abbreviated as xG, has revolutionised football analysis over the past decade. It’s now the single most important statistical tool for serious bettors worldwide, and Nigerian punters who understand it gain a genuine edge over those who only look at scorelines and league tables.

The concept is straightforward: xG measures the quality of goal-scoring chances rather than simply counting goals. Every shot in every football match is assigned a value between 0 and 1 based on historical data from hundreds of thousands of similar shots. This value represents the probability of that shot resulting in a goal.

How xG values are calculated

Factors affecting a shot’s xG value include: distance from goal, angle to goal, body part used (foot, head, other), type of assist (through ball, cross, cutback), whether it’s a one-on-one situation, defensive pressure, and whether it’s a rebound or set piece.

Typical xG values for common situations:

• Penalty kick: 0.76 xG (scored roughly 76% of the time)
• One-on-one with goalkeeper: 0.35-0.45 xG
• Header from 6-yard box: 0.40-0.50 xG
• Shot from edge of box, central: 0.08-0.12 xG
• Long-range effort (25+ yards): 0.02-0.04 xG
• Tight-angle shot near byline: 0.02-0.05 xG

When you sum all xG values from a team’s shots in a match, you get their total match xG — essentially how many goals they “deserved” to score based on chance quality. A team with 2.5 xG created chances that, on average across thousands of similar situations, would produce 2.5 goals.

Why xG is more reliable than actual goals for betting

Actual goals involve significant luck. A striker might be having an off day with finishing. A goalkeeper might produce a career-best performance. Deflections happen. Woodwork gets hit. Over a single match or even five matches, actual goals can diverge wildly from underlying performance.

Consider this real-world example: In early-season Premier League matches, Team A creates chances worth 2.3 xG per game but only scores 0.9 goals per game. Team B creates chances worth 1.1 xG per game but scores 1.8 goals per game. Looking only at actual goals, Team B appears the better attacking side. Looking at xG, Team A is clearly creating more and better chances.

What happens over time? Regression to the mean. Team A’s finishing will likely improve toward their xG level. Team B’s unsustainable overperformance will likely correct. The smart bettor backs Team A’s improvement before the market adjusts; the casual bettor keeps backing Team B based on misleading goal tallies.

Platforms offering predictions for today’s football matches increasingly incorporate xG analysis, making this data accessible without requiring you to calculate everything yourself. The key is understanding what the numbers mean and how to apply them.

How to apply xG analysis to your betting

For any match you’re considering betting on, ask these questions:

1. What is each team’s average xG created over recent matches (last 6-10 games)?
2. What is each team’s average xG conceded over the same period?
3. How do their actual goals compare to their xG? (Overperforming or underperforming?)
4. Are there significant home/away splits in their xG numbers?
5. Do recent squad changes (injuries, suspensions) affect these numbers?

Teams significantly underperforming their xG (creating good chances but not scoring) are candidates for backing. Teams significantly overperforming (scoring more than their chances suggest) are candidates for opposing or avoiding. This simple framework, applied consistently, improves your hit rate substantially.

Beyond xG: Which Other Statistics Actually Predict Results?

While xG is the foundation, several other metrics provide valuable insights for betting. Understanding which statistics matter — and which are just noise — helps focus your analysis on genuinely predictive information.

Expected Goals Against (xGA): Measuring defensive quality

xGA measures the quality of chances a team concedes. A team with low xGA is genuinely defensively solid — they’re not just getting lucky with opponents missing chances. This metric is crucial for Both Teams to Score (BTTS) markets and under/over goals betting.

Watch for teams keeping clean sheets despite high xGA — they’re living dangerously and will likely start conceding. Conversely, teams conceding goals despite low xGA are suffering bad luck that will probably reverse.

Expected Points (xPts): The table that doesn’t lie

Expected Points simulates thousands of match outcomes based on xG data to calculate how many points a team “should” have. Comparing actual points to xPts reveals which teams have been lucky or unlucky.

A mid-table team with xPts suggesting they should be in the top six is being undervalued by the market. A team near the top with xPts suggesting mid-table quality is vulnerable. This metric is especially useful for Asian Handicap betting and match winner markets.

PPDA (Passes Per Defensive Action): Understanding pressing intensity

PPDA measures how many passes a team allows opponents before making a defensive action (tackle, interception, foul). Low PPDA means aggressive pressing; high PPDA indicates a team that sits deep and absorbs pressure.

Why does this matter for betting? High-pressing teams (low PPDA) tend to create chaotic, open games with more goals and more variance. Deep-defending teams (high PPDA) tend to be involved in tighter, lower-scoring matches. This directly informs over/under selections.

Shot volume vs. shot quality

Some teams take many shots of average quality; others take fewer shots but from better positions. Neither approach is inherently superior, but understanding a team’s style helps predict match outcomes.

High-volume shooting teams often leave themselves exposed to counter-attacks, producing end-to-end games. Patient, possession-based teams that wait for high-quality chances tend to be involved in lower-scoring, controlled matches. Matching these tendencies to over/under lines creates betting opportunities.

How Do You Convert Statistics Into Profitable Betting Decisions?

Statistics alone don’t make money. The key is converting analytical insights into probability estimates, then comparing those estimates to bookmaker odds to identify value bets. This process is the core skill of profitable betting.

Understanding implied probability

Every betting odd implies a probability. Converting odds to probability is essential for identifying value. The formula for decimal odds (standard in Nigeria) is simple:

Implied Probability = (1 ÷ Decimal Odds) × 100

Examples:

• Odds of 1.50 = 66.7% implied probability
• Odds of 2.00 = 50.0% implied probability
• Odds of 2.50 = 40.0% implied probability
• Odds of 3.00 = 33.3% implied probability
• Odds of 4.00 = 25.0% implied probability
• Odds of 5.00 = 20.0% implied probability

Calculating value: A practical example

Let’s walk through a realistic scenario. Liverpool plays at home against Wolves. Based on your xG analysis of recent matches, home/away splits, and current form, you estimate:

• Liverpool win probability: 62%
• Draw probability: 22%
• Wolves win probability: 16%

The bookmaker offers:

• Liverpool: 1.55 (implied probability: 64.5%)
• Draw: 4.20 (implied probability: 23.8%)
• Wolves: 6.00 (implied probability: 16.7%)

Comparing your estimates to implied probabilities: Liverpool’s odds imply 64.5% but you estimate 62% — no value (odds are actually worse than your probability suggests). The Draw implies 23.8% but you estimate 22% — no value. Wolves imply 16.7% but you estimate 16% — no value.

In this example, no bet offers value. The disciplined response is to skip this match entirely, regardless of how much you “feel” Liverpool will win. The undisciplined response is to bet anyway because you want action. The former builds bankrolls; the latter destroys them.

Now imagine your analysis suggested Liverpool’s true win probability was 70% instead of 62%. Suddenly the 1.55 odds (64.5% implied) offer value — you’re getting better odds than the true probability suggests. This is when you bet.

Which Betting Markets Respond Best to Statistical Analysis?

Different betting markets have different levels of efficiency. Some are priced very accurately by bookmakers; others offer more opportunities for informed bettors. Understanding which markets suit statistical analysis helps you focus efforts where edge is most likely.

Over/Under Goals: The statistician’s favourite

Over/Under markets respond extremely well to xG-based analysis. By comparing both teams’ xG created and xG conceded, you can estimate expected total goals for a match. When this estimate differs significantly from the bookmaker’s line, value exists.

For example: Team A averages 1.8 xG created and 1.3 xG conceded at home. Team B averages 1.2 xG created and 1.6 xG conceded away. A simple estimate suggests roughly 3.0 expected total goals (Team A scores ~1.5, Team B scores ~1.5). If the bookmaker offers Over 2.5 at 1.95, that’s likely value since your analysis suggests more than 2.5 goals is probable over 50% of the time.

The key insight is looking beyond recent actual goals. A team involved in three consecutive 0-0 draws might still have strong xG numbers, suggesting goals are coming. Similarly, a team in high-scoring games might have low xG, suggesting regression to fewer goals ahead.

Both Teams to Score (BTTS): Balancing attack and defence

BTTS markets require analysing both offensive capability and defensive vulnerability for both teams. For BTTS-Yes to hit, each team needs sufficient attacking quality to score while also having defensive weaknesses the opponent can exploit.

Ideal BTTS-Yes candidates: Both teams averaging 1.0+ xG created AND both teams averaging 1.0+ xG conceded. The match features two sides capable of scoring but also prone to conceding.

Ideal BTTS-No candidates: At least one team with very low xG created (under 0.8) or very low xG conceded (under 0.8). Either a team can’t score regardless of opponent, or a team rarely concedes regardless of opponent.

Asian Handicap: Capturing xG differentials

Asian Handicap markets let you back teams with a virtual advantage or disadvantage. This is powerful when statistical analysis reveals a team is better (or worse) than their results suggest.

If Team A has been creating 2.2 xG per home game but only scoring 1.0 goals due to poor finishing, while Team B has been conceding 1.9 xG per away game but only allowing 0.8 goals due to fortunate goalkeeping, the match odds might not reflect Team A’s true superiority. Taking Team A -1 on the Asian Handicap captures this statistical edge.

The handicap essentially asks: “Will Team A win by more than 1 goal?” Your xG analysis suggests they’re creating enough chances to score 2+ goals while Team B’s defence is more vulnerable than results indicate. The handicap exploits this hidden edge.

Markets to approach with caution

Correct Score, First Goalscorer, and other high-odds markets are difficult to beat with statistics because they require precise predictions rather than directional assessments. The variance is enormous — you can be “right” about a match (correct winner, expected goal range) but still lose these bets.

Similarly, long-odds accumulators — while exciting — face compounding bookmaker margins that statistical edges struggle to overcome. Stick to markets where being “approximately right” generates consistent returns over time.

How Should Nigerian Punters Manage Their Betting Bankroll?

Perfect statistical analysis fails without proper bankroll management. This is where analytical bettors separate themselves from gamblers — treating betting as a long-term investment rather than a series of independent gambles.

Establishing your bankroll

Your bankroll is money set aside exclusively for betting — funds you can lose entirely without affecting rent, food, transport, or family obligations. This isn’t pessimism; it’s essential risk management. Even skilled bettors experience losing streaks lasting weeks. If you can’t survive those streaks, you’ll never reach the profitable long-term.

For most Nigerian punters, a starting bankroll of ₦20,000 to ₦100,000 is reasonable. The specific amount matters less than the discipline applied to managing it. A ₦50,000 bankroll managed correctly outperforms a ₦500,000 bankroll managed recklessly.

Keep your betting funds separate from everyday money — ideally in a dedicated account or clearly tracked spreadsheet. This separation creates psychological distance that helps prevent emotional decisions. For guidance on finding the right betting site for your bankroll management needs, consider factors like withdrawal speed and deposit options.

Stake sizing: The 1-3% rule

Never bet more than 1-3% of your total bankroll on any single selection. With a ₦50,000 bankroll, that means individual bets of ₦500 to ₦1,500 maximum. This seems conservative — and that’s the point.

Consider the mathematics: With 2% stakes, you need to lose 50 consecutive bets to wipe out your bankroll. Even the worst losing streaks rarely reach such extremes. With 10% stakes, just 10 consecutive losses eliminates you — a streak that occurs with alarming frequency even for skilled bettors.

Scale your stakes based on edge size:

• Small edge (2-4% value): 1% bankroll stake
• Medium edge (5-8% value): 1.5-2% bankroll stake
• Large edge (8%+ value): 2-3% bankroll stake (maximum)

Recording every bet: Non-negotiable discipline

Maintain a detailed record of every bet placed: date, match, league, selection, odds, stake, and result. Use a spreadsheet or dedicated app. After 100+ bets, analyse your performance by market type, league, and bet category.

This analysis reveals crucial patterns. You might discover your Premier League bets are profitable but Serie A selections consistently lose. Your Over/Under picks might excel while BTTS selections underperform. Without data, you’re guessing about your own strengths and weaknesses. With data, you can optimise your strategy based on evidence.

Be honest in your recording. Including only wins or “forgetting” to log losses defeats the purpose entirely. The goal is truth, not ego protection.

What Critical Mistakes Must You Avoid When Using Statistics?

Statistical analysis improves betting decisions significantly, but it’s not foolproof. Certain mistakes can undermine even solid analytical approaches. Recognising these pitfalls helps you avoid them.

Overreacting to small sample sizes

Three matches is not a meaningful sample. Even ten matches can be heavily influenced by variance. Reliable patterns require 20+ games minimum for team-level statistics. This creates particular challenges early in seasons when current-season data is limited.

Early-season betting is treacherous because you’re forced to rely on last season’s data despite summer transfers, managerial changes, and evolving tactics. Exercise extra caution during August and September. By October, enough current-season data exists to trust statistical analysis more confidently.

Ignoring contextual factors

Statistics capture what happened in past matches, not what will happen in the next one. Key player injuries, suspensions, fixture congestion, travel fatigue, and match importance all affect outcomes in ways pure numbers miss.

A team’s strong xG numbers become less relevant if their primary creator is injured. A side fighting relegation brings desperation that statistics can’t quantify. European matches midweek affect weekend league performance. Layer contextual analysis on top of statistical foundations for complete pictures.

Always check team news before finalising any bet. Statistics tell you what teams did with their best players available; context tells you whether those players will be present for the upcoming match.

Falling victim to confirmation bias

It’s easy to find statistics supporting what you already believe. If you think Arsenal will win, you’ll notice their strong home xG and ignore their weak record against top-six sides. This selective interpretation defeats the purpose of statistical analysis.

Combat confirmation bias by actively seeking contradictory evidence. Before backing any selection, deliberately look for reasons it might lose. Only proceed when your thesis survives scrutiny. This discipline is uncomfortable but essential for objective analysis.

Betting on too many matches

With hundreds of matches available weekly, the temptation to bet constantly is overwhelming. Resist it. More bets doesn’t mean more profit — it means more exposure to bookmaker margins and more opportunities for undisciplined decisions.

Professional bettors are remarkably selective. They might analyse 50 matches to find 5 worth betting. They let entire weekends pass without placing a single wager if value isn’t present. This selectivity concentrates capital on highest-confidence opportunities rather than diluting it across marginal edges.

Quality over quantity is the consistent theme of profitable betting. Five well-researched bets per week outperform fifty rushed selections placed out of boredom or action-seeking.

How Do You Build a Sustainable Betting Process?

Profitable betting isn’t about one magical statistic or secret system. It’s about building a repeatable process that identifies small edges consistently over hundreds of bets. Here’s a practical framework Nigerian punters can implement immediately.

Step 1: Select your focus leagues

You cannot analyse every league deeply. Choose 2-4 competitions you can follow regularly: watch matches, read team news, understand tactical approaches, and track statistical trends. For most Nigerian punters, the English Premier League is a natural starting point given its TV coverage and cultural familiarity.

Consider adding La Liga, Bundesliga, or Serie A as secondary focus areas. Alternatively, explore less popular leagues (Eredivisie, Portuguese Liga, Belgian Pro League) where bookmaker pricing may be less efficient due to lower betting volumes. Specialisation builds genuine expertise; spreading thin creates superficial knowledge that doesn’t generate edge.

Step 2: Gather data for upcoming matches

For each potential bet in your focus leagues, collect: recent xG created and conceded (with home/away splits), actual goals versus xG (over/underperformance), current form and momentum, head-to-head history, team news (injuries, suspensions, fitness concerns), and contextual factors (fixture congestion, match importance).

Use reliable statistical sources that provide xG data. Free options exist, though paid services often offer more detail. The football predictions page here provides daily analysis incorporating these factors, giving you a starting point for further research.

Step 3: Form probability estimates

Based on your data, estimate probabilities for relevant outcomes. For match winner markets, estimate home win, draw, and away win percentages. For Over/Under, estimate the probability of each side of the line. Be honest about uncertainty — if you’re unsure, your probability estimates should reflect that spread.

This is the hardest step and improves with experience. Initially, your estimates may be rough. Over time, reviewing your estimates against actual outcomes helps calibrate accuracy. The goal isn’t perfection — it’s being more accurate than the bookmaker’s odds imply.

Step 4: Compare to odds and identify value

Convert bookmaker odds to implied probabilities. Compare these to your estimates. Where your probability exceeds implied probability by 5% or more, potential value exists. Below that threshold, edges are too small to overcome variance and margins reliably.

If no value exists in any market for a match, skip it entirely. This discipline separates professionals from recreational bettors. You’re not obligated to bet on every match; you’re obligated to only bet when edge exists.

Step 5: Stake, record, and review

Apply appropriate stake sizing based on edge size, place the bet, and record all details immediately. After outcomes are known, update your records and periodically review aggregate performance.

Regular reviews (monthly or quarterly) reveal patterns: which leagues you’re profitable in, which markets suit your analysis, whether your probability estimates are well-calibrated. Use this information to refine your process continuously.

Frequently Asked Questions

Can statistics really help me win at betting?

Statistics cannot predict specific match outcomes with certainty — football has too much inherent randomness for that. However, statistics significantly improve probability estimates compared to intuition alone. Over hundreds of bets, even small improvements in accuracy compound into meaningful profit. Think of it as improving your success rate from 48% to 54% — not huge per bet, but transformative over time.

Where can Nigerian punters find reliable xG data?

Several free and paid platforms provide xG statistics for major European leagues. FBref, Understat, and FotMob offer free xG data. Paid services like StatsBomb, Opta, and various betting-focused platforms provide more detailed analysis. For Nigerian-focused insights, local platforms like ours combine international statistical data with understanding of what Nigerian bettors need. Start with free resources and consider paid options as your betting becomes more serious.

How much money do I need to start statistical betting?

You can start with any amount you’re genuinely comfortable losing completely — typically ₦10,000 to ₦50,000 for most Nigerian punters. The amount matters less than the discipline applied. With proper 1-2% stake sizing, even a ₦20,000 bankroll allows 50+ bets before potential depletion, giving your edge time to manifest. Never bet money needed for essentials regardless of how confident you feel.

How long before I know if my statistical approach works?

Statistical approaches require large sample sizes for meaningful evaluation. Expect to place 200-500 bets before drawing firm conclusions about long-term profitability. Results from 20-50 bets are dominated by variance and reveal little about genuine edge. This is why bankroll management matters so much — you need to survive long enough for your edge to show. Patience isn’t optional; it’s essential.

Should I bet on the Nigeria Professional Football League (NPFL)?

Local leagues can offer value because bookmakers devote fewer resources to pricing them accurately compared to Premier League or La Liga. However, reliable xG and advanced statistics are harder to find for NPFL. If you have genuine knowledge advantage — attending matches, following local news, understanding team dynamics beyond public information — this edge can be profitable. Otherwise, stick to leagues with abundant statistical data until you develop analytical skills that transfer to data-sparse environments.

Why do I keep losing even when backing favourites?

Backing favourites isn’t automatically profitable because bookmakers price them efficiently — often too efficiently, as public money flows toward big names. A team might deserve to be favourite without their odds offering value. If Arsenal “should” win 65% of the time but their odds imply 70% probability, backing them loses money long-term despite Arsenal winning most matches. Value matters more than prediction accuracy. You can correctly predict 6 of 10 winners but still lose money if none offered value.

Is it better to specialise in one market or bet across many?

Specialisation generally outperforms diversification for statistical bettors. Mastering Over/Under markets using xG analysis is more profitable than mediocre analysis across five different market types. Once you’ve proven edge in one area, consider expanding. But depth beats breadth, especially when starting out. Find what works, refine it, and only branch out once your core approach is reliably profitable.

How do I handle losing streaks without chasing losses?

Losing streaks are mathematically inevitable even with genuine edge. A 55% win rate means losing 45% of bets — streaks of 5-10 losses happen regularly. The key is recognising this before it happens and committing to your staking plan regardless of short-term results. Never increase stakes to “recover” losses. If anything, reduce stakes during losing runs to preserve bankroll. Review your process for errors, but don’t panic-adjust a sound strategy because of normal variance. Trust the mathematics.

Can I make a living from football betting in Nigeria?

Theoretically possible, but practically extremely difficult. Professional bettors exist but represent a tiny fraction of all punters. They typically have large bankrolls (₦5M+), sophisticated analytical models, access to sharp odds before they move, and years of experience. For most Nigerians, betting should remain entertainment with profit as a welcome bonus rather than a primary income source. If you develop genuine skill, treat it as supplemental income while maintaining stable employment.

What’s the single most important thing for betting success?

Discipline. Not statistics, not tips, not luck — discipline. The discipline to only bet when value exists. The discipline to stake appropriately regardless of confidence. The discipline to record every bet honestly. The discipline to skip matches without edge. The discipline to accept losing streaks without chasing. Every other skill builds on this foundation. Without discipline, the best analytical mind still loses money. With discipline, even modest analytical ability can generate profit.

Conclusion: Data Is Your Edge in Nigeria’s Competitive Betting Market

The Nigerian betting market grows more competitive every year. Bookmakers have sophisticated models, real-time data feeds, and teams of analysts working to price markets efficiently. The casual bettor betting on names, feelings, and tips from friends stands little chance against this machinery.

But bookmakers aren’t infallible. They make errors, especially in markets with less liquidity or when public perception diverges from statistical reality. Your edge comes from exploiting these gaps — finding value where xG suggests different probabilities than odds imply, identifying teams due for regression before the market adjusts, and maintaining discipline while others chase losses and bet emotionally.

Statistics won’t make you invincible. Variance ensures even optimal strategies experience losing periods. But over hundreds of bets, a systematic, data-driven approach compounds small edges into meaningful profit. You’ll make better decisions, avoid costly emotional mistakes, and identify opportunities that casual punters miss entirely.

The path forward is clear: learn to interpret xG and related metrics, understand how to convert analysis into probability estimates, find markets where your insights create genuine value, and manage your bankroll with military discipline. None of this is easy or instant. It requires patience measured in months, not days. It demands honesty about your own results, including losses.

Start small. Focus on one league. Build your analytical process step by step. Track everything. Learn from both wins and losses. The bettors who succeed long-term aren’t the luckiest — they’re the most disciplined, patient, and analytical.

The data exists. The methods are proven. The bookmakers can be beaten by those willing to put in the work. The only remaining question is whether you’ll join the 15% who profit or remain with the 85% who fund them.

Your next bet can be the start of a new approach. Make it count.