CN112546635A - Game user matching method and system - Google Patents
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
- A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
- A63F13/70—Game security or game management aspects
- A63F13/79—Game security or game management aspects involving player-related data, e.g. identities, accounts, preferences or play histories
- A63F13/795—Game security or game management aspects involving player-related data, e.g. identities, accounts, preferences or play histories for finding other players; for building a team; for providing a buddy list
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Abstract
The application discloses a game user matching method, which comprises the following steps: acquiring historical data of preset game parameters of the user in a preset period, wherein the preset game parameters comprise the number of kills, the number of deaths and the number of attacks of the user in each game; calculating the average value of each field of the preset game parameters according to the historical data; calculating match matching grades of the users according to the average value of each field and a preset formula; and matching the game opponents of the corresponding grades for the users according to the match matching grades. The application also discloses a game user matching system, a server and a computer readable storage medium. Therefore, game opponents can be distributed according to the real level of the user, the operation is simple, the data acquisition way is convenient, and the game experience of the user is improved by taking the win or loss as a reference.
Description
Technical Field
The present application relates to the field of data analysis technologies, and in particular, to a method, a system, a server, and a computer-readable storage medium for matching game users.
Background
As electronic competitive games are more and more well known, it is desirable to match a flag drum equivalent opponent in a game, and therefore the matching algorithm of the game user becomes crucial.
The mainstream matching rules in the current market are as follows: distributing the segment star number according to the winning or losing result of each game, thereby carrying out ranking according to the obtained total star number (for example, "the royal glory"); the amount of money charged in the game is used as a reference of the ranking; or the score is added and deducted according to the success field and the failure field, and the score is increased and decreased according to the established rule.
However, using the mainstream matching rules, the game users who are brushed may be matched with the game users who are actually high in one battle, and when the difference between the strengths of the matched users is too large, the game experience of the game users in the high-level and the low-level is reduced, and further the users in the game are lost. In addition, if the ranking calculation is only related to the win or loss of the game, when the game user finds that the game user has a tendency of losing the game, the result of the match of the losing party can be deducted, so that the possibility of turning the game in the upwind is low, the possibility of turning the game is lost, and the game experience of the game user is influenced.
It should be noted that the above-mentioned contents are not intended to limit the scope of protection of the application.
Disclosure of Invention
The application mainly aims to provide a game user matching method, a game user matching system, a server and a computer readable storage medium, and aims to solve the problem of how to match according to the actual level of a game user.
In order to achieve the above object, an embodiment of the present application provides a game user matching method, where the method includes:
acquiring historical data of preset game parameters of the user in a preset period, wherein the preset game parameters comprise the number of kills, the number of deaths and the number of attacks of the user in each game;
calculating a historical representative value of the predetermined game parameters according to the historical data;
calculating a match matching ranking of the user according to the history representative value of the predetermined game parameter and a predetermined formula; and
and matching the game opponents of the corresponding grades for the users according to the match matching grades.
Alternatively, the history representative value is an average value per field calculated from the history data corresponding to each of the predetermined game parameters.
Optionally, the predetermined formula includes a weight corresponding to the per-field average value of each of the predetermined game parameters.
Optionally, the method further comprises, before calculating the match rating of the user based on the historical representative value and a predetermined formula:
and respectively setting the weight corresponding to the field average value of each preset game parameter in the preset formula according to the characteristics of the current game.
Optionally, the predetermined formula further includes adjusting the weight, and the method further includes, before calculating the match rating of the user according to the historical representative value and the predetermined formula: and setting the adjusting weight according to the characteristics of the current game to determine that the calculation result of the match grading is not a negative number.
Optionally, the predetermined formula is match matching ranking MMR ═ K part + D part + a part + i, where K part is a first weight corresponding to the field average killing number, and the first weight is a power operation performed on the field average killing number; the part D is a second weight corresponding to the field average death number, and the second weight is obtained by performing evolution and exponential operation on the field average death number; part A is a third weight corresponding to the field average attack number, and the third weight is an operation of dividing the field average attack number by the field average death number; i is the adjustment weight.
Optionally, the predetermined formula ranks match for a game
Wherein k is the field-average killing number, d is the field-average death number, a is the field-average attack number, and i is the adjustment weight.
Optionally, the predetermined formula ranks match for a game
Wherein k isThe number of killing is equal to the field, d is the number of death is equal to the field, and a is the number of attack is equal to the field.
Optionally, the respectively setting the weight corresponding to the per-field average value of each predetermined game parameter in the predetermined formula according to the characteristics of the current game includes:
and adjusting the power or coefficient corresponding to the field-by-field average value of each preset game parameter in the preset formula.
Optionally, the game opponents ranked according to the match of the match for the user to match the corresponding rank comprise:
sorting the calculation results of the match matching grades of all the users according to the scores;
and finding out a second user adjacent to the user according to the position relation in the sequencing to serve as a game opponent of the user.
Optionally, after finding a second user adjacent to the user according to the position relationship in the ranking, the method further includes:
and judging whether the difference value of the calculation results of the match matching grades of the user and the second user is within a preset threshold value, and if so, matching the second user as a game opponent of the user to enter a battle field.
In addition, to achieve the above object, an embodiment of the present application further provides a game user matching system, where the system includes:
the acquisition module is used for acquiring historical data of preset game parameters of the user in a preset period, wherein the preset game parameters comprise the number of kills, the number of deaths and the number of attacks of the user in each game;
the calculating module is used for calculating a historical representative value of the preset game parameters according to the historical data;
a grading module for calculating a match matching grade of the user according to the history representative value of the predetermined game parameter and a predetermined formula;
and the matching module is used for matching the game opponents in the corresponding grades for the users according to the match matching grades.
In order to achieve the above object, an embodiment of the present application further provides a server, where the server includes: the game user matching program is stored on the memory and can run on the processor, and when being executed by the processor, the game user matching program realizes the game user matching method.
In order to achieve the above object, an embodiment of the present application further provides a computer-readable storage medium, where a game user matching program is stored on the computer-readable storage medium, and when executed by a processor, the game user matching program implements the game user matching method as described above.
The game user matching method, the game user matching system, the server and the computer readable storage medium provided by the embodiment of the application can establish a set of quantitative rules for tracking the actual performance of the user in the game for a long time, and accord with the characteristics of simple operation and convenient data acquisition way, not only takes win or loss as a reference, but also distributes game opponents according to the real level of the user, embodies fair competition and improves the game experience of the user.
Drawings
FIG. 1 is a diagram of an application environment architecture in which various embodiments of the present application may be implemented;
FIG. 2 is a diagram of another application environment architecture for implementing various embodiments of the present application;
FIG. 3 is a flowchart of a method for matching game users according to a first embodiment of the present application;
FIGS. 4A-4B are a list of MMR calculations and a graphical representation of MMR curves according to the present application;
FIG. 5 is a schematic diagram of an MMR ordered list and matching results of the present application;
FIG. 6 is a flowchart of a method for matching game users according to a second embodiment of the present application;
fig. 7 is a schematic hardware architecture diagram of a server according to a third embodiment of the present application;
FIG. 8 is a block diagram of a game user matching system according to a fourth embodiment of the present application;
fig. 9 is a block diagram of a game user matching system according to a fifth embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the descriptions relating to "first", "second", etc. in the embodiments of the present application are only for descriptive purposes and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In addition, technical solutions between various embodiments may be combined with each other, but must be realized by a person skilled in the art, and when the technical solutions are contradictory or cannot be realized, such a combination should not be considered to exist, and is not within the protection scope of the present application.
Referring to fig. 1-2, fig. 1-2 are diagrams illustrating an application environment architecture for implementing various embodiments of the present application. As shown in fig. 1, the present application is applicable to an application environment including, but not limited to, a client 2, a server 4, and a network 6.
The client 2 is used for sending a game request to the server 4, receiving opponent information distributed by the server 4 and displaying the opponent information to a user, receiving game operation of the user and the like. The client 2 may be a terminal device such as a PC (Personal Computer), a mobile phone, a tablet Computer, a portable Computer, and a wearable device.
The server 4 is configured to receive a game request sent by the client 2, match a corresponding opponent for a user of the client 2, send opponent information to the client 2, and record game data and the like of the client 2. The server 4 may be a rack server, a blade server, a tower server, a cabinet server, or other computing devices, may be an independent server, or may be a server cluster formed by a plurality of servers.
The network 6 may be a wireless or wired network such as the Internet, Global System for Mobile communications (GSM), Wideband Code Division Multiple Access (WCDMA), 4G network, 5G network, Wi-Fi, etc. The server 4 and one or more clients 2 are connected through the network 6 for data transmission and interaction.
As further shown in fig. 2, in the embodiments of the present application, the server 4 may be further subdivided to include at least a data center server 40, a game matching server 42, and a game fighting server 44.
The data center server 40 is configured to collect predetermined game parameters of the users of the respective clients 2 in each game, including a kill number (kill), a death number (dead), an attack number (assist), and the like, and calculate an average value per field of the predetermined game parameters in a predetermined period of each user (for example, in the last year or in a season), including a field average kill number (denoted as k), a field average death number (denoted as d), and a field average attack number (denoted as a).
The game matching server 42 is configured to calculate Match Matching Ratings (MMR) of each user according to the average value of each field of the predetermined game parameter calculated by the data center server 40 and a predetermined formula, Match a game opponent of a corresponding Rating for the user, and introduce the user and the opponent into a game scene provided by the game fighting server 44.
The game battle server 44 is used for providing data and technical support such as game scenes according to the operation of the user and the opponent, and sending the preset game parameters to the data center server 40 for statistics after the game is finished.
It should be noted that the data center server 40, the game matching server 42, and the game combat server 44 may belong to a server cluster, be integrated into a server, or be any other feasible components.
Example one
Fig. 3 is a flowchart of a game user matching method according to a first embodiment of the present application. It is to be understood that the flow charts in the embodiments of the present method are not intended to limit the order in which the steps are performed. Some steps in the flowchart may be added or deleted as desired.
The method comprises the following steps:
s200, acquiring historical data of the preset game parameters of the user in a preset period.
When a user completes a game, the server needs to record the preset game parameters of the user and acquire historical data of the preset game parameters of the user (including the game just completed and the previous game), so as to prepare for grading each user subsequently. The level of strength of a game user should be related to the actual performance of said user in the battle field, coupled with other data and not to represent the competitive level. Thus, in the present embodiment, the predetermined game parameters include, but are not limited to, the number of kills, deaths, and attacks of the user in each game. In addition, in order to deal with the stress of a large amount of user data on the server load, only the historical data of the user in a predetermined period can be acquired during calculation. The predetermined period may be the last year, or a season, etc.
S202, calculating the average value of each field of the preset game parameters according to the historical data.
And after the historical data of the user is acquired, the server respectively calculates the average value of each field of each preset game parameter according to the historical data. That is, calculating the average killing number k according to the killing numbers of all the times of the user in the preset game period; calculating the average death number d according to the death numbers of all the game times of the users in the preset game period; and calculating the average attack number a according to the attack numbers of all the fields of the user in the preset game period.
Each time the user completes a game, the latest average value per game needs to be calculated from the historical data of the game and previous games.
In other embodiments, the per-field average value may also be replaced by another feasible historical representative value calculated according to the historical data corresponding to each of the predetermined game parameters, and will not be described herein again.
And S204, calculating the MMR of the user according to the average value of each field and a preset formula.
In this embodiment, the predetermined formula includes an average value per field and a corresponding weight for each of the predetermined game parameters. For example, the field average attack number K corresponds to a first weight (K part), the field average death number D corresponds to a second weight (D part), and the field average attack number a corresponds to a third weight (a part).
In addition, in order to ensure that the result of the MMR calculation is not negative, the predetermined formula also comprises an adjusting weight (i).
That is, the predetermined formula is:
MMR ═ K moiety + D moiety + a moiety + i. Wherein:
part K, the field-averaged killing number addition. From the disclosed data distribution, it is found that the higher the k value, the smaller the proportion of game users, and therefore, in the fitting data, the weight corresponding to k is exponentiated. I.e. K is a moiety2。
The D component, the field mean death number, adds up, usually to a negative value. Since the death number is usually amplified by the snowball effect in the later stage of the game, the field-average death number d is converged by the exponent of the natural number e in combination with the evolution, and the maximum value of the portion is reduced.
Part A, the field-averaged attack number. The attack-assisting number is important for auxiliary game users, the game users often have no killing capacity, only the output type users in the auxiliary game kill the opponents, and therefore the data of the part is also a positive number. Since the k value of the auxiliary game user is often very low, in order to balance the numerical expression of the game users, a corresponding reinforced adjustment needs to be made on the data addition of the game users, and in this embodiment, the loss caused by the low k value is made up by combining the average field death number d. The general expression is a/d.
And adjusting the weight i, which is optimization of operation, in order to prevent the MMR calculation result from being a negative number, the calculated numerical value is translated integrally without influencing the trend of the final fitting curve.
According to the above analysis, the predetermined formula (general formula expression) in the present embodiment may be:
further, the present embodiment gives an addition weight of 5a/(d +1) to the part a by fitting analysis for the simulation data, and sets the adjustment weight i to 100.
That is, the present embodiment sets the predetermined formula to:
when the server receives a new game request (mainly referring to a request for matching a game opponent in a new game) sent by the client where the user is located, the calculated field average killing number k, field average death number d and field average attack number a of the user are obtained and substituted into the formula, and the MMR score of the user can be calculated.
Fig. 4A-4B are a table of MMR calculation results and a schematic MMR variation curve, respectively. In FIG. 4A, the value of k is 0, and it can be seen that different values of d and a result in a close MMR score. These close MMR scores have a significant additive effect when there is killing data (k values). In FIG. 4B, each transition point is a set of data, where k is constant within each set and MMR is in ascending order.
S206, matching the user with the game opponent with the corresponding grade according to the MMR score.
After the MMR value of each user is calculated, the server sorts the calculation results of match grading of all users according to the scores, and then finds a second user adjacent to the user as a game opponent according to the position relation in the sorting. The adjacent means that the first name and the second name are matched, the third name and the fourth name are matched, and the like, wherein the adjacent means that the first name and the second name are matched in sequence from high to low according to the sorting. Thus, the opponent matching the second user is the first user, and the opponent matching the third user is the fourth user. For example, fig. 5 is a schematic diagram of an MMR ordered list and matching results.
In addition, in order to further ensure the accuracy of the matching result, whether the difference value of the MMR of the two matched users (the user and the second user) is within a preset threshold value can be further judged, and if yes, the two matched users enter a battle bureau. If not, matching the game opponent to the user by adopting other feasible ways, which is not described herein again.
According to the game user matching method provided by the embodiment, a set of quantitative rules for tracking the actual performance of the user in the game for a long time can be established, the characteristics of simple operation and convenient data acquisition way are met, the victory or defeat is not only taken as a reference, the game opponents are distributed according to the real level of the user, the fair competition is embodied, and the game experience of the user is improved.
Example two
Fig. 6 is a flowchart of a game user matching method according to a second embodiment of the present application. In the second embodiment, the game user matching method further includes steps S304 and S306 on the basis of the first embodiment. It is to be understood that the flow charts in the embodiments of the present method are not intended to limit the order in which the steps are performed. Some steps in the flowchart may be added or deleted as desired.
The method comprises the following steps:
s300, acquiring historical data of the preset game parameters of the user in a preset period.
When a user completes a game, the server needs to record the preset game parameters of the user and acquire historical data of the preset game parameters of the user (including the game just completed and the previous game), so as to prepare for grading each user subsequently. In this embodiment, the predetermined game parameters include, but are not limited to, the number of kills, deaths, and attacks of the user in each game. In addition, in order to deal with the stress of a large amount of user data on the server load, only the historical data of the user in a predetermined period can be acquired during calculation. The predetermined period may be the last year, or a season, etc.
S302, calculating the average value of each field of the preset game parameters according to the historical data.
And after the historical data of the user is acquired, the server respectively calculates the average value of each field of each preset game parameter according to the historical data. That is, calculating the average killing number k according to the killing numbers of all the times of the user in the preset game period; calculating the average death number d according to the death numbers of all the game times of the users in the preset game period; and calculating the average attack number a according to the attack numbers of all the fields of the user in the preset game period.
Each time the user completes a game, the latest average value per game needs to be calculated from the historical data of the game and previous games.
In other embodiments, the per-field average value may also be replaced by another feasible historical representative value calculated according to the historical data corresponding to each of the predetermined game parameters, and will not be described herein again.
S304, respectively setting the weight corresponding to the average value of each field of each preset game parameter in the MMR calculation formula according to the characteristics of the current game.
In this embodiment, the MMR calculation formula includes the average value per field and the corresponding weight of each predetermined game parameter. For example, the field average attack number K corresponds to a first weight (K part), the field average death number D corresponds to a second weight (D part), and the field average attack number a corresponds to a third weight (a part).
In addition, in order to ensure that the MMR calculation result is not a negative number, the MMR calculation formula also comprises an adjusting weight (i).
That is, the MMR calculation formula is:
MMR ═ K moiety + D moiety + a moiety + i. Wherein:
part K, the field-averaged killing number addition. From the disclosed data distribution, it is found that the higher the k value, the smaller the proportion of game users, and therefore, in the fitting data, the weight corresponding to k is exponentiated. In the predetermined formula, K is a moiety K2。
The D component, the field mean death number, adds up, usually to a negative value. Since the death number is usually amplified by the snowball effect in the later stage of the game, the field-average death number d is converged by the exponent of the natural number e in combination with the evolution, and the maximum value of the portion is reduced.
Part A, the field-averaged attack number. The attack-assisting number is important for auxiliary game users, the game users often have no killing capacity, only the output type users in the auxiliary game kill the opponents, and therefore the data of the part is also a positive number. Since the k value of the auxiliary game user is often very low, in order to balance the numerical expression of the game users, a corresponding reinforced adjustment needs to be made on the data addition of the game users, and in this embodiment, the loss caused by the low k value is made up by combining the average field death number d. The general expression is a/d.
And adjusting the weight i, which is optimization of operation, in order to prevent the MMR calculation result from being a negative number, the calculated numerical value is translated integrally without influencing the trend of the final fitting curve.
When the parameters of the MMR calculation formula are adjusted, different calculation results can be obtained. For convenience of calculation, the predetermined formula (general formula expression form) of the MMR calculation formula in this embodiment may be:
the weight of each parameter in the MMR calculation formula is correspondingly set by combining with specific game characteristics or different ranking scenes, namely, the corresponding kda addition is adjusted according to the kda judgment standard of the current scene. In this embodiment, the setting mainly includes: adjusting the power or coefficient corresponding to the field-by-field average value of each of the predetermined game parameters in the MMR calculation formula (the predetermined formula). For example, if the weight expression of the number of killing is to be increased in the current game, the number of killing can be increased by increasing or decreasing the power of k or increasing k2Is implemented by the coefficients of (a). Similarly, the D part and the A part can achieve the purpose of changing the addition effect by adjusting the coefficients. For example, for a certain ranking scene, the assistant is emphasized, and the coefficients of the part a are adjusted to make the assistant higher.
S306, setting the adjusting weight in the MMR calculation formula according to the characteristics of the current game.
For the convenience of calculation, it is necessary to ensure that the MMR calculation result is not a negative number, so all adjustments to the final value need to rely on the value of the fourth part "adjustment weight" of the formula to avoid the occurrence of a negative number.
For example, the present embodiment sets the a section to 5a/(d +1), and sets the adjustment weight i to 100. That is, the present embodiment sets the MMR calculation formula to:
and S308, calculating the MMR of the user according to the average value of each field and the set MMR calculation formula.
When the server receives a new game request (mainly referring to a request for matching a game opponent in a new game) sent by the client where the user is located, the setting is carried out according to the current game characteristics, the calculated field average killing number k, field average death number d and field average attack number a of the user are obtained, and the MMR score of the user can be calculated by substituting the calculated field average killing number k, field average death number d and field average attack number a into the set formula.
S310, matching the user with the game opponents in the corresponding grades according to the MMR score.
After the MMR value of each user is calculated, the server sorts the calculation results of match matching grading of all users according to the scores, and then matches adjacent users for the users as game opponents according to the position relation in the sorting.
In addition, in order to ensure the accuracy of the matching result, whether the MMR difference value of the two matched users is within a preset threshold value can be further judged, and if yes, the two matched users enter a battle bureau.
According to the game user matching method provided by the embodiment, a set of quantitative rules for tracking the actual performance of the user in the game for a long time can be established, the characteristics of simple operation and convenient data acquisition way are met, the victory or defeat is not only taken as a reference, the game opponents are distributed according to the real level of the user, the fair competition is embodied, and the game experience of the user is improved. And corresponding setting can be carried out by combining specific game characteristics or different ranking scenes, and the power or coefficient corresponding to the average value of each field of each preset game parameter in the formula is adjusted, so that different addition effects are realized, the matching result is more accurate, and the application range is wider.
EXAMPLE III
Fig. 7 is a schematic diagram of a hardware architecture of a server 20 according to a third embodiment of the present invention. In this embodiment, the server 20 may include, but is not limited to, a memory 21, a processor 22, and a network interface 23, which may be communicatively connected to each other through a system bus. It is noted that fig. 7 only shows the server 20 with components 21-23, but it is to be understood that not all of the shown components are required to be implemented, and that more or fewer components may be implemented instead.
The memory 21 includes at least one type of readable storage medium including a flash memory, a hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a Programmable Read Only Memory (PROM), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the storage 21 may be an internal storage unit of the server 20, such as a hard disk or a memory of the server 20. In other embodiments, the memory 21 may also be an external storage device of the server 20, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), or the like, provided on the server 20. Of course, the memory 21 may also include both an internal storage unit of the server 20 and an external storage device thereof. In this embodiment, the memory 21 is generally used for storing an operating system installed in the server 20 and various application software, such as program codes of the game user matching system 60. Further, the memory 21 may also be used to temporarily store various types of data that have been output or are to be output.
The processor 22 may be a Central Processing Unit (CPU), controller, microcontroller, microprocessor, or other data Processing chip in some embodiments. The processor 22 is typically used to control the overall operation of the server 20. In this embodiment, the processor 22 is configured to run the program codes stored in the memory 21 or process data, such as running the game user matching system 60.
The network interface 23 may comprise a wireless network interface or a wired network interface, and the network interface 23 is generally used for establishing communication connection between the server 20 and other electronic devices.
Example four
Fig. 8 is a block diagram of a game user matching system 60 according to a fourth embodiment of the present invention. The game user matching system 60 may be partitioned into one or more program modules, stored in a storage medium and executed by one or more processors to implement embodiments of the present application. The program modules referred to in the embodiments of the present application refer to a series of computer program instruction segments capable of performing specific functions, and the following description will specifically describe the functions of each program module in the embodiments.
In this embodiment, the game user matching system 60 includes:
an obtaining module 600, configured to obtain historical data of the predetermined game parameters of the user in a predetermined period.
When a user finishes every game, the preset game parameters of the user are recorded, and historical data of the preset game parameters of the user (including the game which is just finished and the game of the previous game) is acquired, so that preparation is made for grading each user in a subsequent process. In this embodiment, the predetermined game parameters include, but are not limited to, the number of kills, deaths, and attacks of the user in each game. In addition, in order to deal with the stress of a large amount of user data on the server load, only the historical data of the user in a predetermined period can be acquired during calculation. The predetermined period may be the last year, or a season, etc.
A calculating module 602, configured to calculate an average value per field of the predetermined game parameter according to the historical data.
After the historical data of the user is obtained, the calculating module 602 calculates each field average value of each predetermined game parameter according to the historical data. That is, calculating the average killing number k according to the killing numbers of all the times of the user in the preset game period; calculating the average death number d according to the death numbers of all the game times of the users in the preset game period; and calculating the average attack number a according to the attack numbers of all the fields of the user in the preset game period.
Each time the user completes a game, the latest average value per game needs to be calculated from the historical data of the game and previous games.
In other embodiments, the per-field average value may also be replaced by another feasible historical representative value calculated according to the historical data corresponding to each of the predetermined game parameters, and will not be described herein again.
A ranking module 604 for calculating the MMR of the user based on the per-field mean and a predetermined formula.
In this embodiment, the predetermined formula includes an average value per field and a corresponding weight for each of the predetermined game parameters. For example, the field average attack number K corresponds to a first weight (K part), the field average death number D corresponds to a second weight (D part), and the field average attack number a corresponds to a third weight (a part).
In addition, in order to ensure that the result of the MMR calculation is not negative, the predetermined formula also comprises an adjusting weight (i).
That is, the predetermined formula is:
MMR ═ K moiety + D moiety + a moiety + i. Wherein:
part K, the field-averaged killing number addition. From the disclosed data distribution, it is found that the higher the k value, the smaller the proportion of game users, and therefore, in the fitting data, the weight corresponding to k is exponentiated. I.e. K is a moiety2。
The D component, the field mean death number, adds up, usually to a negative value. Since the death number is usually amplified by the snowball effect in the later stage of the game, the field-average death number d is converged by the exponent of the natural number e in combination with the evolution, and the maximum value of the portion is reduced.
Part A, the field-averaged attack number. The attack-assisting number is important for auxiliary game users, the game users often have no killing capacity, only the output type users in the auxiliary game kill the opponents, and therefore the data of the part is also a positive number. Since the k value of the auxiliary game user is often very low, in order to balance the numerical expression of the game users, a corresponding reinforced adjustment needs to be made on the data addition of the game users, and in this embodiment, the loss caused by the low k value is made up by combining the average field death number d. The general expression is a/d.
And adjusting the weight i, which is optimization of operation, in order to prevent the MMR calculation result from being a negative number, the calculated numerical value is translated integrally without influencing the trend of the final fitting curve.
According to the above analysis, the predetermined formula (general formula expression) in the present embodiment may be:
further, the present embodiment gives an addition weight of 5a/(d +1) to the part a by fitting analysis for the simulation data, and sets the adjustment weight i to 100.
That is, the present embodiment sets the predetermined formula to:
when a new game request (mainly a request for matching a game opponent in a new game) sent by a client where the user is located is received, the grading module 604 obtains the calculated field average killing number k, field average death number d and field average attack number a of the user, and substitutes the calculated field average killing number k, field average death number d and field average attack number a into the formula, so that the MMR score of the user can be calculated.
And the matching module 606 is used for matching the game opponents in the corresponding grades for the users according to the MMR scores.
After the MMR value of each user is calculated, the matching module 606 sorts the calculation results of the match ranking of all users according to the score, and then matches the users with the adjacent users as game opponents according to the position relationship in the sorting.
In addition, in order to ensure the accuracy of the matching result, whether the MMR difference value of the two matched users is within a preset threshold value can be further judged, and if yes, the two matched users enter a battle bureau.
The game user matching system provided by the embodiment can establish a set of quantitative rules for tracking the actual performance of the user in the game for a long time, accords with the characteristics of simple operation and convenient data acquisition way, not only takes win or loss as a reference, distributes game opponents according to the real level of the user, embodies fair competition, and improves the game experience of the user.
EXAMPLE five
Fig. 9 is a block diagram of a game user matching system 60 according to a fifth embodiment of the present invention. In this embodiment, the game user matching system 60 further includes a setting module 608 in addition to the acquiring module 600, the calculating module 602, the grading module 604 and the matching module 606 in the fourth embodiment.
The setting module 608 is configured to set a weight corresponding to the per-field average value of each predetermined game parameter in the predetermined formula according to a characteristic of a current game.
The weight of each parameter in the predetermined formula should be correspondingly set in combination with specific game characteristics or different ranking scenes, that is, corresponding kda addition is adjusted according to the kda judgment standard of the current scene. In this embodiment, the setting mainly includes: and adjusting the power or coefficient corresponding to the field-by-field average value of each preset game parameter in the preset formula. For example, if the weight expression of the number of killing is to be increased in the current game, the number of killing can be increased by increasing or decreasing the power of k or increasing k2Is implemented by the coefficients of (a). Similarly, the D part and the A part can achieve the purpose of changing the addition effect by adjusting the coefficients. For example, for a certain ranking scene, the assistant is emphasized, and the coefficients of the part a are adjusted to make the assistant higher.
The setting module 608 is further configured to set an adjustment weight in the predetermined formula according to a characteristic of the current game.
For the convenience of calculation, it is necessary to ensure that the MMR calculation result is not a negative number, so all adjustments to the final value need to rely on the value of the fourth part "adjustment weight" of the formula to avoid the occurrence of a negative number.
After the setting module 608 sets the above weights, the grading module 604 substitutes the field average killing number k, the field average death number d, and the field average attack number a of the user calculated by the calculating module 602 into the set formula, so as to calculate the MMR score of the user.
The game user matching system provided by the embodiment can be correspondingly set by combining specific game characteristics or different ranking scenes, and the power or coefficient corresponding to each field of average value of each preset game parameter in the formula is adjusted, so that different addition effects are realized, the matching result is more accurate, and the application range is wider.
EXAMPLE six
The present application further provides another embodiment, which is to provide a computer-readable storage medium storing a game user matching program, which is executable by at least one processor to cause the at least one processor to perform the steps of the game user matching method as described above.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments.
It will be apparent to those skilled in the art that the modules or steps of the embodiments of the present application described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and alternatively, they may be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, and in some cases, the steps shown or described may be performed in an order different from that described herein, or they may be separately fabricated into individual integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, embodiments of the present application are not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present application, and not intended to limit the scope of the present application, and all modifications that can be made by the use of the equivalent structures or equivalent processes in the specification and drawings of the present application or that can be directly or indirectly applied to other related technologies are also included in the scope of the present application.
Claims (14)
1. A game user matching method, the method comprising:
acquiring historical data of preset game parameters of the user in a preset period, wherein the preset game parameters comprise the number of kills, the number of deaths and the number of attacks of the user in each game;
calculating a historical representative value of the predetermined game parameters according to the historical data;
calculating a match matching ranking of the user according to the history representative value of the predetermined game parameter and a predetermined formula; and
and matching the game opponents of the corresponding grades for the users according to the match matching grades.
2. The game user matching method according to claim 1, wherein the history representative value is an average value per field calculated from the history data corresponding to each of the predetermined game parameters.
3. The game user matching method according to claim 2, wherein the predetermined formula includes a weight corresponding to the per-field average value of each of the predetermined game parameters.
4. A game user matching method according to claim 3, wherein said method further comprises, before calculating a match rating of said user based on said history representative value and a predetermined formula:
and respectively setting the weight corresponding to the field average value of each preset game parameter in the preset formula according to the characteristics of the current game.
5. The game user matching method according to claim 4, further comprising adjusting a weight in the predetermined formula, and before calculating a match matching ranking of the user based on the history representative value and the predetermined formula, further comprising: and setting the adjusting weight according to the characteristics of the current game to determine that the calculation result of the match grading is not a negative number.
6. The game user matching method according to any one of claims 1 to 5, wherein the predetermined formula is a match score MMR ═ K part + D part + a part + i, where K part is a first weight corresponding to a field average kill number, the first weight being a exponentiation of the field average kill number; the part D is a second weight corresponding to the field average death number, and the second weight is obtained by performing evolution and exponential operation on the field average death number; part A is a third weight corresponding to the field average attack number, and the third weight is an operation of dividing the field average attack number by the field average death number; i is the adjustment weight.
7. The game user matching method according to any of claims 1 to 5, wherein the predetermined formula ranks match for a game
Wherein k is the field-average killing number, d is the field-average death number, a is the field-average attack number, and i is the adjustment weight.
8. The game user matching method according to any of claims 1 to 5, wherein the predetermined formula ranks match for a game
Whereink is the field-average killing number, d is the field-average death number, and a is the field-average attack number.
9. The game user matching method according to claim 6, wherein the setting of the weight corresponding to the per-field average value of each of the predetermined game parameters in the predetermined formula according to the characteristics of the current game comprises:
and adjusting the power or coefficient corresponding to the field-by-field average value of each preset game parameter in the preset formula.
10. The game user matching method according to claim 1, wherein said matching game opponents ranked according to the match of the match to the user in the corresponding rank comprises:
sorting the calculation results of the match matching grades of all the users according to the scores;
and finding out a second user adjacent to the user according to the position relation in the sequencing to serve as a game opponent of the user.
11. The game user matching method according to claim 10, further comprising, after finding a second user adjacent to the user in the positional relationship in the ranking:
and judging whether the difference value of the calculation results of the match matching grades of the user and the second user is within a preset threshold value, and if so, matching the second user as a game opponent of the user to enter a battle field.
12. A game user matching system, the system comprising:
the acquisition module is used for acquiring historical data of preset game parameters of the user in a preset period, wherein the preset game parameters comprise the number of kills, the number of deaths and the number of attacks of the user in each game;
the calculating module is used for calculating a historical representative value of the preset game parameters according to the historical data;
a grading module for calculating a match matching grade of the user according to the history representative value of the predetermined game parameter and a predetermined formula;
and the matching module is used for matching the game opponents in the corresponding grades for the users according to the match matching grades.
13. A server, characterized in that the server comprises: a memory, a processor and a game user matching program stored on the memory and executable on the processor, the game user matching program when executed by the processor implementing the game user matching method as claimed in any one of claims 1 to 11.
14. A computer-readable storage medium, characterized in that a game user matching program is stored on the computer-readable storage medium, and when executed by a processor, implements the game user matching method according to any one of claims 1 to 11.
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| WO2023103617A1 (en) * | 2021-12-10 | 2023-06-15 | 腾讯科技（深圳）有限公司 | User interface display method and apparatus, device, medium, and program product |
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| WO2023103617A1 (en) * | 2021-12-10 | 2023-06-15 | 腾讯科技（深圳）有限公司 | User interface display method and apparatus, device, medium, and program product |
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