Simulating Variance: Why Your Portfolio Needs a Safety Net

Variance is not your enemy — misunderstanding it is

Every sports investor who takes the craft seriously will eventually encounter a losing streak that makes them question everything. Ten losses in a row. Three weeks in the red. A month where nothing seems to land. The natural reaction is to assume something is broken — your model, your signals, your luck. But in most cases, what you are experiencing is simply variance, the unavoidable randomness inherent in any probabilistic endeavor.

Understanding variance is not just an academic exercise. It directly determines how you size your portfolio, how you react to losing streaks, and ultimately whether you survive long enough for your edge to play out. Investors who underestimate variance position too large, panic during drawdowns, and often go broke despite having a genuine edge. Investors who understand variance size appropriately, stay disciplined, and let the math work.

What variance looks like in practice

Let us put some numbers on it. Imagine an investor with a genuine 55% win rate on even-money positions (decimal returns of 2.00). This is an excellent win rate — most successful investors operate in the 52–56% range. What does a season of 500 positions look like for this investor?

Read that again: even with a strong 55% edge, there is roughly a 1% chance of being underwater after 500 positions. And the median worst losing streak is 9 positions in a row. This is not bad luck — this is normal statistical behavior.

The Monte Carlo method

Monte Carlo simulation is a technique that runs thousands of random scenarios to map out the range of possible outcomes. Instead of calculating a single expected result, it generates a distribution of results that shows you best-case, worst-case, and everything in between.

In trading terms, each simulation run represents one possible future for your portfolio. Run it 10,000 times and you get a clear picture of the probability of various outcomes: the chance of doubling your portfolio, the chance of hitting a 20% drawdown, the chance of going broke. This is far more useful than a single expected value calculation because it shows the range of variance around that expectation.

The inputs are straightforward: your estimated win rate, the average returns you invest, your allocation size as a percentage of portfolio, and the number of positions. Change any of these and the distribution shifts dramatically.

Why portfolio sizing is the critical variable

Of all the inputs to a Monte Carlo simulation, allocation size has the most dramatic effect on your probability of ruin. Here is a comparison at a 55% win rate on even-money positions over 500 positions:

• 1% of portfolio per position: Probability of ruin is essentially 0%. Drawdowns rarely exceed 10%. Growth is slow but steady.
• 2% of portfolio per position: Probability of ruin is still near 0%. Drawdowns can reach 15–20%. This is the sweet spot for most investors.
• 5% of portfolio per position: Probability of ruin rises to roughly 3–5%. Drawdowns of 30–40% are common. Emotionally very difficult to endure.
• 10% of portfolio per position: Probability of ruin exceeds 15%. Drawdowns of 50%+ happen regularly. Most investors cannot psychologically handle this, leading to tilt and even larger losses.

The conventional wisdom of risking 1–3% of your portfolio per position is not arbitrary — it is derived from exactly this kind of analysis. For a deeper dive into unit sizing, flat trading, and the Kelly Criterion, see our portfolio management guide.

Rules of thumb for portfolio sizing

Based on simulation data across various win rates and returns ranges, here are practical guidelines:

• 50–100 units as a starting portfolio. A unit is your standard position size. If you invest $20 per game, your portfolio should be $1,000 to $2,000. This gives you enough runway to absorb normal variance.
• Never risk more than 3% on a single position. Even for your highest-confidence plays, cap your exposure. Confidence is subjective; variance is mathematical.
• Reduce position size during drawdowns. If you use percentage-of-portfolio allocation, this happens automatically. If you use flat allocation, consider manually reducing your unit size if you hit a 20%+ drawdown.
• Do not increase position size to chase losses. This is the fastest path to ruin. Variance means you will have losing streaks; increasing your allocations during a downswing amplifies the damage.

Emotional preparedness matters

Even if you intellectually understand variance, experiencing a 15-position losing streak firsthand is a different matter. Preparation helps:

• Before you start, decide on a maximum drawdown threshold (e.g., 25%) at which you will pause and reassess — not panic-quit, but calmly review whether your edge is intact.
• Keep a log of your CLV alongside your results. If your closing line value is positive during a losing streak, your process is likely fine and results will revert.
• Never increase allocations to "make back" what you lost. The positions do not know you are behind.