Sorry, Conway fans, this one isn’t for you. This is for everyone who grew up playing Milton Bradley’s board game The Game of Life. The game puts you in control of your own destiny as you drive your car through the decades and into retirement. On the way, your fate is forged by choices you make and the spin of a clicky wheel. While luck is clearly a big part of the game, I’ve always wondered how important those few choices really are. To answer that question, I wrote a small program to simulate the game. Armed with the ability to simulate over 50,000 games per second, I confirmed what we probably all already knew were the best choices to make when playing the game.
Strategy
Game of Life players only have a few decisions to make. I simulated the effect of each decision in 1 million simulated head-to-head matchups.
| Losing Strategy Win Percentage |
Winning Strategy Win Percentage |
Difference | |
| Buy Stock | 25.7% | 74.2% | 48.5 |
| Buy Life Insurance | 35.7% | 64.3% | 28.6 |
| Go to College | 39.8% | 60.2% | 20.4 |
| Play the Market | 46.8% | 53.2% | 6.3 |
| Play Lucky Days | 48.0% | 52.0% | 4.0 |
| Buy Fire Insurance | 49.5% | 50.5% | 1.1 |
| Buy Auto Insurance | 49.8% | 50.1% | 0.3 |
Buy Stock (74.2% wins)
This is the most important choice you can make in Life. A player who buys stock will win the game 74.2% of the time vs. a player who does not. Stock allows you to play the market (more on this later) and also reveals a number of bonus tiles along the board. Not to mention, even if you do nothing with your stock certificate, it’s worth $120,000 at the end of the game. Just buy it!
Buy Life Insurance (64.3% wins)
Does anyone really realize how important life insurance is in this game? It’s the second most important factor after buying stock. A player with Life Insurance will win head-to-head 64.3% of the time against a player who does not.
Pick the University track (60.2% wins)
We all knew this one, right? Early on, the game asks you to decide whether to go on the University track or the faster Business track. It’s pretty clear that slow-but-steady wins the race and University is the way to go. The simulator confirms it with 60.2% of University players winning in a head-to-head over Business players. I think the only surprising thing here is that the game tells us that going to college is less important than buying life insurance.
Play the Market if you Own stock (53.2% wins)
If you bought stock (and per above, you should!), you’re often given the option to play the market. Just do it! Each time, there is a 30% chance you’ll lose $60,000 and a 40% chance you’ll make $120,000. That’s an expected value of $30,000 each time. Bet on the odds and go for it. The simulator shows that those who do will win 53.2% of the time over those who don’t.
Bet on Lucky Days (52.0% wins)
When you land on a Lucky Day space you are given two $10,000 bills. You can keep them, or put each one on a different number of the wheel. If the wheel hits your number, you win $300,000. If not, you lose your original $20,000. That’s an expected value of $44,000. This comes up less frequently in the game than playing the market, so even though it’s a bigger expected value, this strategy has slightly less impact than playing the market. Those who bet on Lucky Days will win 52.0% of the time vs. those who don’t.
Buy Fire Insurance (50.5% wins)
We’re getting into diminishing returns here. Fire insurance owners will win 50.5% of the time vs. those who don’t have it.
Buy Auto Insurance (50.1% wins)
Buy auto insurance if you want to play optimally. Skip it if you want to impress your friends with your brazen strategy. Those with auto insurance will win 50.1% of the time vs. an opponent without it. It’s almost even odds.
Combined Optimal Strategies vs. Combined Losing Strategies
If you compare a player who plays optimally in each strategy defined above with a player who plays all of the opposite losing strategies, the optimal player will win the game 93.3% of the time.
Player Order
Going first in the Game of Life gets you a small but noticeable advantage. There’s ultimately still some fairness here since order is determined by spinning the wheel. Here are your odds of winning a game based on the order in which you start.
| Number of Players | Player 1 Win % |
Player 2 Win % |
Player 3 Win % |
Player 4 Win % |
Player 5 Win % |
Player 6 Win % |
Player 7 Win % |
Player 8 Win % |
| 2 | 50.8% | 49.2% | ||||||
| 3 | 34.1% | 33.3% | 32.5% | |||||
| 4 | 25.7% | 25.1% | 24.7% | 24.4% | ||||
| 5 | 20.7% | 20.3% | 19.9% | 19.7% | 19.4% | |||
| 6 | 17.3% | 16.9% | 16.7% | 16.5% | 16.4% | 16.1% | ||
| 7 | 14.7% | 14.5% | 14.5% | 14.2% | 14.1% | 14.0% | 13.8% | |
| 8 | 13.0% | 12.8% | 12.6% | 12.5% | 12.4% | 12.3% | 12.2% | 12.0% |
Career
While you can’t control your Career (aside from choosing Business vs. University), it is one of the most important factors in the game. Career determines your salary which is strongly correlated with how much money you will have at the end of the game.
| Chances of Getting this Career | Salary | Average Wealth at End of Game |
|
| Doctor | 21.4% | $50,000 | $1,985,690 |
| Lawyer | 11.4% | $50,000 | $1,972,915 |
| Physicist | 9.3% | $30,000 | $1,646,089 |
| Journalist | 21.4% | $24,000 | $1,567,040 |
| Teacher | 10.4% | $20,000 | $1,489,827 |
| University | 26.0% | $16,000 | $1,446,165 |
Most games are won by a player with the highest salary.
| Number of Players | Percent of Games Where Winner has the Highest Salary |
| 2 | 72.6% |
| 3 | 63.0% |
| 4 | 59.5% |
| 5 | 58.2% |
| 6 | 58.0% |
| 7 | 58.0% |
| 8 | 58.6% |
Methodology
All statistics were produced using a custom game simulator written in C# and available as open source on GitHub. A simulated game contains 2-8 players, each with its own “personality”. Each simulated player takes turns spinning the “wheel” and moves tile-to-tile like in a real game. Certain tiles require special actions that are coded into the simulation (e.g., stop to get married). Some tiles also allow players to make one of the decisions described above (e.g., buy stock, play the market, etc.). The simulated player’s “personality” determines which decision it will make. The statistics above were all generated using 1 million sequential games. Player order was randomized, except in the case where I was deliberately measuring the effect of player order.
For the head-to-head strategy comparisons, each strategy option (e.g., buying stock) was evaluated against a player who made the opposite decision for that strategy (e.g., not buying stock), but otherwise played “optimally”.
Future Improvements
There are a few things I didn’t account for in the simulation. The code is all available online, and contributions to improve these or other factors are welcome!
- Revenge tiles in the real game allow you to take $200,000 from any player or to send any player back 10 spaces. I didn’t simulate that perfectly or even pick a great strategy. A simulated player who lands on Revenge picks an opposing player at random and steals $200,000 or all the money that person has, whichever is less.
- Share the Wealth cards are given to players in the real game when they land in a Pay Day space by an exact count. You can then play the card later for benefits throughout the game. Growing up, we never played with these cards. I didn’t simulate them either.
- Borrowing from the Bank becomes necessary when you run out of money. In the real game, you need to do this in discrete $20,000 increments. For simplicity, I ignored that detail and allow players to go into the red by any amount. I do properly simulate 5% interest on that amount.
- Betting on the wheel is allowed in the real game, but it’s basically straight odds. It could be useful if you know you’re behind, but I ignored it in the simulation.
- At the end of a real game, a player can try to become a Millionaire Tycoon. This is a 1/10 shot of winning the game immediately. If the player fails, he or she loses everything. It’s actually not a bad option for players who know they’re far behind on wealth and have no other shot. I didn’t simulate Millionaire Tycoons. Winners are determined solely by their wealth at the end of the game.
Summary
Want to be a winner at the Game of Life? Play it exactly how your parents would have told you to play it.