"When we were considering using blockchain to develop a fishing game recently, we discovered that fishing games are actually a type of gambling game. Fishing games are a classic game genre that can be found in arcades, PC, and mobile platform. Colorful schools of fish, vast fishing nets, flashy coin effects, and enthusiastic players clicking away are all distinctive features of this type of game. Now, what is the specific principle behind this game? And what reasons lie behind its popularity? Let's start with the conclusion: Fishing games are a form of gambling, essentially similar to slot machines. Both involve using probability to bet small amounts in hopes of winning big and earning coins."
From the player's point of view, we consume gold coins, launch artillery fire, hit the target fish, hit with a certain probability, and get gold coins. This is the basic closed-loop process of the fishing game. It sounds a bit like TPS shooting games. However, it is obvious that fishing games are completely different from TPS games, and they are often classified into gambling games. So what is the essential difference between the two?
The most critical point of the game: what determines whether we hit the target?
Yes, in the fishing game, hits and misses are determined by hidden probabilities, not an explicit set of mathematical formulas. In other words, we cannot intuitively judge our fishing progress and success rate by "how much we have hit" and "how much blood is left". It can even be guessed that the fish we have worked so hard to catch probably has no blood volume at all. The probability of hitting the target is exactly the same when I hit the first time and the tenth time. As a result, the "strategy" of our hard-working fishing has been greatly reduced, and only "luck" and "probability" are left to influence the results. From the perspective of the game, the player consumes gold coins to fish, and the success rate is calculated according to a certain probability formula f(x). If it succeeds this time, the corresponding fish bonus will be output to the player. If it fails, there will be no gain.
The bet is gold coins, and the output is still gold coins. The process of calculating the fishing probability is a black box, and the final feedback is 0 or 1, that is, failure or success. In order to satisfy the player's psychology, gorgeous and exaggerated animation effects are often designed to give the player the illusion of "a lot of money". For this kind of game, it is obvious that the focus is on this "black box" f(x). What is its specific mechanism? Obviously, there are thousands of people with different faces, and the black box settings in different fishing games are different.
First of all, adjust the black box according to the basic information of the room, and the success rate of fishing in different rooms is different. The novice room often has a certain protection mechanism, and the overall feedback to the player is greater than the payment. The higher the room is, the higher the corresponding fish are, and the higher the profit will be, as well as the higher the risk will be. In other words, the more advanced the room, the lower the success rate of fishing. Also, in many theories there is the notion of room throughput. To put it simply, it means that when the room produces more gold coins than expected, the overall success rate may also be reduced. This can also be verified experimentally in the client.
Second, adjust the black box according to the player's basic information. In the same room, different players have different fishing success rates
Imagine such a scenario: players find that the novice room is profitable, so they stay in the novice room unchanged. This obviously contradicts the purpose of the developer. At the same time, as a developer, we also hope to push players to go to high-end rooms to experience high-risk, high-fun games. Therefore, it is necessary for the black box to make conditional judgments on the player's situation and make negative feedback adjustments. When the player's current amount of gold coins is higher than a certain set value of this room, even if the room is originally set relatively flat, but for this player at this time, his fishing success rate is likely to decrease accordingly. At the same time, the existence of the novice protection mechanism allows novice players to bring their own "halo", with a high success rate. And if the player reaches a certain payment point, it may be more likely to fail than usual, stimulating the player to pay.
Thirdly, adjust the black box according to the basic information of this firing. The same player in the same room, with different firing methods, has different fishing success rates.
According to the system design of each fishing game, there may be different explanations for the firepower setting of the gun. Generally speaking, the success rate of fishing is directly proportional to the firepower value of the gun. There is an important point here, that is, how many fish can be hit at one time to increase the success rate? That is a very practical question: Are there any special skills in fishing games? We start from practical experience, if a shot does not touch a fish, there must be no profit. However, if you catch 5 fish at a time, which is more cost-effective than catching one fish each 5 times? The intuitive feeling is that the former and the latter are equivalent, but what about from the perspective of research and development? Is this a game that encourages players to catch as many fish as possible? Obviously not. In terms of insurance, if you want to hit a certain fish, it may be a better strategy to keep shooting around it and not touch other small fish. As for the specific details, it is still experimentally verified by controlling variables according to specific products.
To sum up, the fishing game is a kind of game that uses small things to make big gains. Players consume gold coins, enter a specific black box, and output the probability. If they succeed, they will get the gold coins corresponding to the fish. The probability of success is determined by the black box conditions, including room conditions, player conditions, firing conditions, etc.
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