Sports betting has its ups and downs, so it’s important to understand the concept of variance and how it affects results. Variance refers to the degree of uncertainty or risk attached to a particular bet or series of bets, and is a major factor behind winning and losing runs.
High variance bets have a wider range of possible outcomes and carry more risk, while low variance bets have narrower outcomes and are less risky.
Understanding variance is crucial for analysing the risk-reward ratio of a bet or value betting strategy. In this article, I explore the key differences between high and low variance bets and how they impact results, helping you take a more effective, predictable approach.
Article Contents
Variance Explained
In statistics, variance measures how spread out a dataset is — the average distance of each data point from the mean. High variance means results are widely dispersed; low variance means they cluster closer to the average.
In betting terms: variance reflects the uncertainty of your results. A high-risk betting strategy will produce erratic swings in profit (high variance). A low-risk strategy tends to produce steadier results with smaller fluctuations (low variance).
This is often confused with volatility, which describes how those swings feel to the bettor. Two strategies might have the same variance mathematically, but the one with sharper short-term swings will feel more volatile. Recognising this distinction helps keep decision-making objective.
High Variance
High variance bets carry greater risk and a wide range of potential outcomes, making them less predictable. They usually come with high odds — offering big payouts if successful but a greater likelihood of losing.
For example, backing an underdog in a football match is a high variance bet. So is betting on a specific player to score the first goal, since many players could do so and the outcome is hard to predict.
Variance also increases when you raise your stakes, since each outcome carries more weight against your bankroll.
Low Variance
Low variance bets carry less risk and narrower outcomes, making results more predictable. These bets usually have lower odds, with smaller payouts but a reduced chance of losing.
For example, backing a strong favourite in a football match is a low variance bet. Another is betting on the total points scored in a basketball game, which tends to align with averages and statistics.
Variance can also be reduced by lowering your stakes, since smaller bet sizes create gentler swings in your bankroll.
What Approach Is Most Profitable?
Neither high nor low variance is inherently more profitable. Both can be part of a successful strategy, and both can fail. The difference lies in how they behave:
- High variance strategies deviate further from the expected value, with bigger wins and losses.
- Low variance strategies stay closer to the expected value, with steadier but less dramatic swings.
Ultimately, profitability depends on finding value in the odds — not on variance itself. Some high variance approaches can be lucrative but risky, while some low variance approaches protect the bankroll but fail to generate profit.
The Psychological Impact of Variance
Variance doesn’t just test your bankroll — it tests your mindset. Even sound strategies experience losing runs, and how you react is critical.
- Chasing losses: A natural response is to raise stakes to recover quickly, but this usually compounds losses.
- Overconfidence: A hot streak can create false belief in a system’s edge, tempting you to bet recklessly.
- Patience under pressure: Variance often tempts bettors to abandon solid strategies too soon. Recognising that swings are normal is key to sticking with a process long enough for value to show.
By being aware of these psychological traps, bettors can keep variance in perspective and avoid letting short-term results dictate poor decisions.
An Example of Variance in Betting
It’s easy to get carried away during winning streaks or disheartened by losing ones, but variance is a normal part of betting. Swings happen in all forms of gambling.
To demonstrate, I’ll use my Mug Betting Experiment as an example — I placed a bet on every Premier League fixture based purely on opinion and tracked the results each week.
Initially, profits rose to +£180. Soon after, a run of losses cut them back to +£100. This kind of fluctuation is common and highlights variance.
From +£180 down to +£100…
Over the course of 270 bets, the experiment eventually settled at 0.00% ROI.
Crucially, I never changed my stakes because there was no rational reason to think the experiment had an edge. Had I increased bet sizes after the winning run, the losses that followed would have been disastrous. The test showed the strategy wasn’t profitable — and that variance alone can create deceptive swings.
As I’ve said elsewhere: successful betting isn’t about past wins or the number of winners you’ve picked. It’s about consistently finding value.
How to Control Variance in Betting
You can’t eliminate variance, but you can manage its impact with disciplined practices:
- Bankroll management: Set aside a dedicated bankroll and risk only a small percentage per bet. This cushions losing streaks and ensures longevity.
- Capping the odds: Stick to lower-odds bets (e.g. under 3.0) to limit swings. Returns are smaller, but losses are less severe in the short term.
- Lower bet sizes: Smaller stakes mean smaller fluctuations, reducing the impact of bad runs.
- Hedging: Backing both sides of an outcome can cut variance, though it reduces potential profit and may sacrifice value.
- Using multiple strategies: Mix high and low variance strategies to balance risk and avoid overexposure to one approach.
- Data analysis: Research teams, players, and trends. Informed bets reduce randomness and help variance converge toward expected value.
The Importance of a Large Data Set
A large dataset is vital for reducing variance and improving accuracy. By analysing enough team, player, and betting data, you can spot patterns and trends more reliably.
The same applies to your own betting records. For example, 80 bets over six months may seem meaningful, but variance makes it too small a sample for solid conclusions.
Without enough data, variance can exaggerate wins or losses. With enough data, you can better gauge whether a strategy is truly profitable.
Over time, the ROI of any approach converges toward its true level. Think of a casino’s fixed edge on roulette: they don’t win every spin, but across thousands, their advantage always shows. Betting works the same way — variance fades, value endures.
Variance will always play a role in betting, but discipline, data, and a focus on value are what ultimately decide long-term success. Manage the swings, stick to your process, and let the numbers reveal the truth over time.
I also recommend reading my post on betting strike rates, which ties in closely with variance.
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