Though this information could be used as a guide, you may also just find it interesting. I love statistics. I partly majored in it, and with a server like Flood, where there are so many ways to measure things, I thought it would be fun to present to you some of my findings. My sample size (the amount of players whose measurements I took) is 111. I measure things such as damage, profit, and investment (how much you spend on your boat). The findings are as follows: The first plotting of Investment and Profits yielded interesting results. Common sense dictates that the more you spend on a boat, the better this boat is, and therefore the more money you will earn. However, from the data gathered we can see that there is little to no correlation at all between money invested into your boat and how much money you get out of it. So making cheap boats guarantees great returns then? Not so fast... See the three graphs that come together. I plotted every boat built for under $1000, under $1500, and over $1000 separately. The correlation is once again quite poor, but it appears to show a weak tendency towards demonstrating that building expensive puts you at a higher chance to lose money. This does not mean that you shouldn't build a good boat though, I will explain further down the reasoning for this. As expected, damage is strongly correlated with profit (see the third picture). On average, players spend $880 on their boat but experience an average of $1383 in profit. This may seem like it is too little money invested in a boat for a single player. The reason for that is that players who are in teams can split the cost of a boat, therefore bringing the average investment per player down... However I have also calculated standard deviation, which may give us a more accurate picture. Standard deviation tells us how dispersed our data is. It helps us picture what is consistent with the majority of players in terms of their performance. Damage On average, a player will do 1266 units of damage in a round. The standard deviation of this data set is roughly 947. This means that the damage within 1 standard deviation is 1266+947 (mean + dv). Essentially, the data suggests that: 68% of players will have caused between 0 and 2213 damage, 95% of players will have caused between 0 and 3479 damage, 99.7% of players will have caused between 0 and 4915 damage. So, if you can deal at least 2213 damage in a round, you belong to the top 32% of players. If you reach 3479 damage in a round you are at a crazy top 5% of players, and if you deal at least 4915 you belong tot he top 0.03% of players. This latest group of elites can only seemingly be achieved through the use of predator missiles in-game. Investment On average, a player will spend $880 on his or her boat, meaning a standard deviation of $974. What this tells us is that 68% of players spend between $0 and $1854, 95% of players will spend between $0 and $2828. These numbers are not very helpful in any way other than making an excellent case for teaming up with some friends. Profits On average, a player will make a profit of $1383 a round, with a standard deviation of $1717. This is huge. This means that 68% of players make less than $3100 a round, 95% make less than $4817, and 99.7% make less than $6534. In simpler terms: If you make at most $3100, you are in the top 32%. If you make at most $4817, you are part of the elite club of the top 5%. If you make at most $6534, you are part of the super elite club of the top 0.03% of Flood players. This may only be possible through the use of a predator missile. Conclusion: Spending a ton of money on a boat alone cannot guarantee returns on investment. Finding a way to make a durable boat to deal as much damage as possible is the best strategy. If you manage to deal at least 2213 damage per round (1 SD) while spending less than $1854 ( 1 SD) on your boat, you are guaranteed a profit per round between $1383 and $3100 (mean and SD). I hope this may be of use or amusement to someone. Data set in use available upon request.

If there are official stats that may confirm what this sample size tells us I would love to hear about it! I did not count people who were AFK in the lobby as they brought down the mean of the sample.