Systems and Methods for Analyzing a Marksman Training Exercise

Abstract

Embodiments disclosed herein are directed to systems and methods for analyzing a marksman training exercise. Embodiments disclosed herein include determining a desired instructor speed and a desired instructor accuracy for a plurality of shots in the marksman training exercise, determining a desired student speed and a desired student accuracy for the plurality of shots in the marksman training exercise, and assigning the desired instructor speed and the desired instructor accuracy a first percentage. Some embodiments are configured for assigning the desired student speed and the desired student accuracy a second percentage, receiving a marksman speed data and a marksman accuracy data for the plurality of shots by a marksman, and converting the marksman speed data and the marksman accuracy data into respective percentages based on the first percentage and the second percentage.

Description

CROSS REFERENCE

This application claims the benefit of U.S. Provisional Application Ser. No. 61/488,135, filed May 19, 2011, which is hereby incorporated by reference in its entirety.

BACKGROUND

1. Field

Embodiments provided herein generally relate to systems and methods for analyzing a marksman training exercise, and particularly to systems and methods for determining the accuracy and speed of a marksman.

2. Technical Background

During marksman training exercises (such as for firearms, knives, archery, etc.), many different criteria may be determined to assess the competency of a marksman. As an example, if a marksman is required to fire at a target of a human, the marksman may be required to fire the weapon at various distances and within a predetermined time. In some training exercises, the marksman may be required to run a distance between shots, to additionally determine the fitness of the marksman. While these tests are valuable for the marksman to practice such skills, currently, these tests often provide no empirical analysis for the marksman to improve.

SUMMARY

Embodiments disclosed herein are directed to systems and methods for analyzing a marksman training exercise. Embodiments disclosed herein include determining a desired instructor speed and a desired instructor accuracy for a plurality of shots in the marksman training exercise, determining a desired student speed and a desired student accuracy for the plurality of shots in the marksman training exercise, and assigning the desired instructor speed and the desired instructor accuracy a first percentage. Some embodiments are configured for assigning the desired student speed and the desired student accuracy a second percentage, receiving a marksman speed data and a marksman accuracy data for the plurality of shots by a marksman, and converting the marksman speed data and the marksman accuracy data into respective percentages based on the first percentage and the second percentage.

Also included are embodiments of a system. Some embodiments of a system include a memory component that stores logic that causes the system to determine a desired instructor speed and a desired instructor accuracy for a plurality of shots in the marksman training exercise, determine a desired student speed and a desired student accuracy for the plurality of shots in the marksman training exercise, assign the desired instructor speed and the desired instructor accuracy a first percentage, and assign the desired student speed and the desired student accuracy a second percentage. In some embodiments, the logic causes the system to receive a marksman speed data and a marksman accuracy data for the plurality of shots by a marksman, convert the marksman speed data and the marksman accuracy data into respective percentages based on the first percentage and the second percentage, and utilize the marksman speed data and the marksman accuracy data to determine an instruction for improvement.

Also included are embodiments of a non-transitory computer-readable medium. Some embodiments include a program that, when executed by a computing device, causes the computing device to determine a desired instructor speed and a desired instructor accuracy for a plurality of shots in the marksman training exercise, determine a desired student speed and a desired student accuracy for the plurality of shots in the marksman training exercise, and assign the desired instructor speed and the desired instructor accuracy a first percentage. In some embodiments, the program causes the computing device to assign the desired student speed and the desired student accuracy a second percentage, receive a marksman speed data and a marksman accuracy data for the plurality of shots by a marksman, and utilize the marksman speed data and the marksman accuracy data to determine an instruction for improvement.

BRIEF DESCRIPTION OF THE DRAWINGS

The embodiments set forth in the drawings are illustrative and exemplary in nature and are not intended to limit the subject matter defined by the claims. The following detailed description of the illustrative embodiments can be understood when read in conjunction with the following drawings, where like structure is indicated with like reference numerals and in which:

FIG. 1 depicts a computing environment for analyzing a marksman training exercise, according to one or more embodiments shown and described herein;

FIG. 2 depicts the computing device for analyzing a marksman training exercise, according to embodiments disclosed herein;

FIG. 3 depicts a user interface for providing data from the marksman training analysis, according to one or more embodiments shown and described herein; and

FIG. 4 depicts a flowchart for analyzing a marksman training exercise, according to embodiments disclosed herein.

DETAILED DESCRIPTION

Embodiments disclosed herein include systems and methods for analyzing a marksman training exercise. More specifically, embodiments disclosed herein are configured to measure the speed of a marksman's shot, as well as determine the accuracy of that the shot. The speed may be determined via a timing device that provides an alert to indicate the start of timing. The timing device additionally includes a noise sensor, which identifies when the marksman fired a shot. The shot that the marksman fired may be analyzed to determine the marksman's accuracy and/or speed. This data may then be compared with a predetermined instructor desired time, an instructor desired accuracy, a student desired time, and a student desired accuracy. This data may be further analyzed to identify strengths, weaknesses, and/or areas of improvement for the marksman.

Additionally, some embodiments disclosed herein are configured to compare speed and/or accuracy data among students in a class. As an example, upon analyzing two or more marksmen, a determination may be made regarding which is the fastest, slowest, most accurate, least accurate, best (as determined from a combination of speed and accuracy), and/or worst (also determined from a combination of speed and accuracy). Accordingly, in some embodiments, this data is graphically represented and sorted based on any of these criteria. Other embodiments are also considered and included within the scope of this disclosure.

Referring now to the drawings, FIG. 1 depicts a computing environment for analyzing a marksman training exercise, according to one or more embodiments shown and described herein. As illustrated, a network 100 may be coupled to a computing device 102, a target 104a, and a timing device 104b, and an image capture device 104c. The network 100 may include a wide area network and/or a local area network and thus may be wired and/or wireless. The computing device 102 may include any portable and/or non-portable computing devices, such as personal computers, laptop computers, tablet computers, personal digital assistants (PDAs), mobile phones, etc.

Also included are the target 104a, the timing device 104b, and the image capture device 104c. The target 104a may be a marksman target at which the marksman fires during the training exercise. Depending on the particular embodiment, an administrator may record the accuracy of the marksman's shots and/or the target 104a may include one or more sensors to automatically detect the accuracy of the marksman's shots. Specifically, in some embodiments, the target 104a may be configured as a paper target. Upon completion of an exercise, the administrator may measure the distance of each shot from a target point or “bulls eye.” Depending on the particular embodiment, the target 104a may include one or more target points. The administrator may then enter the accuracy results into the computing device 102.

In some embodiments, the target 104a may include and/or be part of a sensor for automatically determining the accuracy of the marksman's shots. As an example, the sensor may include a light sensor that detects when the projectile penetrates the target 104a. The light sensor can then determine the location of the marksman's shot on the target 104a and compare that location with a known position of the target point. This information may be sent to the computing device 102 for determining the accuracy of the marksman's shot.

Similarly, the timing device 104b may determine the speed for each of the marksman's shots. Specifically, the timing device 104b may be coupled to an alarm that indicates to the marksman a time to begin firing. The alarm may provide a visual indication and/or an audible indication. In response to the indication being provided, the marksman may begin firing the weapon. The timing device 104b may additionally detect when the weapon was fired. The time between the alarm being provided and the firing of the weapon may be calculated. Depending on the particular test, the alarm may activate for each round that the marksman is to fire. In some embodiments, the alarm may provide a single alarm for firing of an entire magazine of ammunition.

In some embodiments, the timing device 104b may be configured to detect a first fired shot from the marksman and calculate the time between fired shots. Thus, instead of measuring the reaction time of the marksman to external stimuli, this test may detect when each round is fired and measure the speed at which the marksman fires the shots.

The image capture device 104c, which may include a still camera and/or video camera, may be configured to capture image data of the marksman during the training exercise to determine proper technique, as well as compare the technique with speed and accuracy. As an example, the image capture device 104c may record video of the marksman during the exercise. The image capture device 104c can send the recorded content to the computing device 102, which analyzes the recorded content to identify faults in the marksman's technique. As an example, the computing device 102 may detect the position of the weapon prior to firing. The computing device 102 may additionally determine the position of the weapon during and after the marksman fires the weapon. Accordingly, the computing device 102 may determine whether the marksman moves the weapon during firing and, if so, the direction of that movement. The computing device 102 may additionally determine corrective measures to improve the marksman's speed and/or accuracy. In some embodiments, the administrator may provide at least a portion of this analysis.

Accordingly the computing device 102 may receive the data from the target 104a, the timing device 104b, the image capture device 104c, and/or an administrator and may determine various characteristics of the training session, based on predetermined criteria. In some embodiments, the computing device 102 may include analysis logic 144a and improvement logic 144b. The analysis logic 144a may cause the computing device 102 to determine the desired speed and accuracy of an instructor level marksman for various training exercises. For each of these training exercises, the computing device 102 may then assess the empirical score determined for the desired instructor and assign the desired instructor score with a first percentage of 100% (or other percentage value). Similarly, the computing device 102 can determine an empirical score for the desired student marksman for each of the training exercises and assign the desired student score with a second percentage of 80% (or other percentage value). Thus, when a marksman participates in the training exercises, his/her speed and accuracy data may be compared with the desired instructor score and the desired student score and assigned a value based on this comparison. As an example, the desired instructor percentage is 100%, which could equate to the instructor hitting 5 out of 10 targets. If the marksman hits 3 out of 10 targets, the marksman could receive an accuracy percentage of 60%.

As the computing device 102 performs this analysis on both speed and accuracy of the marksman's shot(s), the improvement logic 144b may cause the computing device 102 to compare the speed data, accuracy data, and/or the image data received from the image capture device 104c to provide the marksman with an instruction for improvement. Additionally, the computing device 102 may provide a graphical user interface that includes at least a portion of this data.

It should be understood that while the target 104a, the timing device 104b, and the image capture device 140c are depicted as non-computer based devices, this is merely an example. In some embodiments, one or more of these devices include computing components, similar to those depicted in FIG. 2 for the computing device 102. Additionally, while the computing device 102 is represented in FIG. 1 each as a single component; this is also merely an example. In some embodiments, there may be numerous different components that provide the described functionality. However, for illustration purposes, single components are shown in FIG. 1 and described herein.

FIG. 2 depicts the computing device 102 for analyzing a marksman training exercise, according to one or more embodiments shown and described herein. In the illustrated embodiment, the computing device 102 includes a processor 230, input/output hardware 232, network interface hardware 234, a data storage component 236 (which instructor data 238a, student data 238b, and/or other data), and the memory component 140. The memory component 140 may be configured as volatile and/or nonvolatile memory and as such, may include random access memory (including SRAM, DRAM, and/or other types of RAM), flash memory, secure digital (SD) memory, registers, compact discs (CD), digital versatile discs (DVD), and/or other types of non-transitory computer-readable mediums. Depending on the particular embodiment, these non-transitory computer-readable mediums may reside within the computing device 102 and/or external to the computing device 102.

Additionally, the memory component 140 may store operating logic 242, the analysis logic 144a and the improvement logic 144b. The analysis logic 144a and the improvement logic 144b may each include a plurality of different pieces of logic, each of which may be embodied as a computer program, firmware, and/or hardware, as an example. A local interface 246 is also included in FIG. 2 and may be implemented as a bus or other interface to facilitate communication among the components of the computing device 102.

The processor 230 may include any processing component operable to receive and execute instructions (such as from the data storage component 236 and/or the memory component 140). The input/output hardware 232 may include and/or be configured to interface with a monitor, positioning system, keyboard, mouse, printer, the image capture device 104, microphone, speaker, gyroscope, compass, and/or other device for receiving, sending, and/or presenting data. The network interface hardware 234 may include and/or be configured for communicating with any wired or wireless networking hardware, including an antenna, a modem, LAN port, wireless fidelity (Wi-Fi) card, WiMax card, mobile communications hardware, and/or other hardware for communicating with other networks and/or devices. From this connection, communication may be facilitated between the computing device 102 and other computing devices.

The operating logic 242 may include an operating system and/or other software for managing components of the computing device 102. Similarly, as discussed above, the analysis logic 144a may reside in the memory component 140 and may be configured to cause the processor 230 to analyze received training data from a marksman training session. The improvement logic 144b may cause the computing device 102 to utilize the received training data, as well as data determined by the analysis logic 144a to determine points for improving the marksman's performance. Other functionality is also included and described in more detail, below.

It should be understood that the components illustrated in FIG. 2 are merely exemplary and are not intended to limit the scope of this disclosure. While the components in FIG. 2 are illustrated as residing within the computing device 102, this is merely an example. In some embodiments, one or more of the components may reside external to the computing device 102. It should also be understood that, while the computing device 102 in FIG. 2 is illustrated as a single device, this is also merely an example. In some embodiments, the analysis logic 144a and the improvement logic 144b may reside on different devices.

Additionally, while the computing device 102 is illustrated with the analysis logic 144a and the improvement logic 144b as separate logical components, this is also an example. In some embodiments, a single piece of logic may cause the computing device 102 to provide the described functionality.

FIG. 3 depicts a user interface 300 for providing a marksman training exercise analysis, according to one or more embodiments shown and described herein. As illustrated, the user interface 300 may be provided by the computing device 102 and includes a plurality of windows 302a-302i for providing analysis of various marksman training exercises. While any number of training exercises may be utilized and included within the scope of this disclosure, FIG. 3 depicts pistol, carbine, and physical training exercises and/or drills. As an example, the pistol drills could include one round body drill, two round body drill, three round body drill, six round body drill, one round body reload body drill, ten reload ten drill, five reload five reload five drill, and six tactical reload six body drill, etc. Similarly, the carbine drills may include one round low ready drill, one round high ready drill, one round range left high ready drill, one round range right high ready drill, one round up range high ready drill, two body one head high ready drill, six body low ready drill, seven head high ready drill, one body one head low ready drill, one transition one drill, ten reload ten high ready drill, one reload one drill, one transition one reload one drill, and two transition two twelve meters to five meters drill, etc. The physical drills may include head five point shots drill, head four point shots drill, body five point shots drill, body four point shots drill, and body three point shots drill, etc. Other drills may also be utilized and analyzed.

More specifically, the window 302a provides pistol speed and accuracy data before training. In the window 302a, the line 303 indicates the desired student score for speed and/or accuracy. The desired student score may be provided as a percentage, which may be assigned a value of approximately 75%. Also included in the window 302a is an instructor desired score 304. The instructor desired score 304 is calculated by first determining how a marksman instructor would perform on the drill. This performance is then converted to a percentage, such as 100%, which stretches across the x-axis of the graph in the window 302a. Both lines 303 and 304 may represent the desired performances for instructors and students for both accuracy and speed. By converting the speed and accuracy to a percentage (or other common metric) both speed and accuracy may be provided in the same graphical representation.

The marksman's actual results for this particular training exercise is plotted as marksman speed data with a circle and marksman accuracy data with crosshairs to illustrate the speed (circle) and accuracy (crosshair) for each of the marksman's shots. The marksman accuracy data and the marksman speed data may each be converted into respective parentages as discussed herein to compare to the desired instructor score and/or the desired student score. As the y-axis indicates the assigned percentage that is compared to the desired scores, the x-axis indicates the shot number of the training exercise. As is also illustrated, each of the speed plots and the accuracy plots include a speed score and an accuracy score. The accuracy score may represent the total number of shots that were determined as “accurate” and/or a value of a particular shot, as based on a predetermined scoring system. Similarly, the speed score may represent the total time that has elapsed during the exercise.

In some embodiments, the time value in the window 302a is measured in seconds and the accuracy is measured according to a binary scale, where an accurate shot is rewarded with a “1” and an inaccurate shot is awarded a value of “0.” Thus, in the window 302a, the first shot missed, so the first shot accuracy 306a was assessed a 0% score. The speed of the shot (2.84 seconds), however, was assessed approximately a 58% score. As these are both below the desired student score and the desired instructor score, the first shot indicates that both speed and accuracy need improvement.

As discussed above, the percentage scored awarded to the marksman are dependent on the speed and accuracy of a desired instructor and/or student. Thus, in at least some embodiments, the percentage represented in the window 302a is not a representation of the percentage of accurate shots fired but a comparison of the marksman's accuracy with the desired instructor and/or desired student accuracy.

Also included in FIG. 3 are overall speed and accuracy for the entire training exercise. The static speed chart 310a indicates that over the course of the training exercise, the marksman achieved a 79% score, which is better than the desired student speed. Similarly, a static accuracy chart 310b indicates that the accuracy of the marksman is 69%, which is less than the desired student score.

In addition to providing the user interface 300 of FIG. 3, some embodiments may also analyze this data to determine where the marksman can improve speed and/or accuracy. As an example, if a marksman is often high on the speed assessment, but low on the accuracy assessment, the computing device 102 may indicate that marksman should slow down the speed, which should improve accuracy. Similarly, if the marksman is above expectation with regard to accuracy, but the speed of the shots is slow, the computing device 102 can determine that the marksman can increase the speed of shots, even if the marksman would sacrifice some accuracy.

Similarly, the image capture device 104c may capture one or more images of the marksman during the training exercise and perform image analysis to determine the quality of the marksman's technique. This may be used to provide improvement advice. This image data may additionally be compared with the speed and accuracy data to determine the differences between “good” shots and “bad” shots.

Further, while the examples with regard to FIG. 3 utilize a binary system for determining the accuracy of a shot, this is merely an example. Some embodiments may be configured to determine a percent error of the desired accuracy (e.g., if the marksman is firing at ten (10) yards and the desired accuracy of a shot is within one (1) inch, a percent differential from the desired accuracy may be determined for the actual shot. Additional analysis may be provided to determine the direction in which the shot missed. Such an evaluation system may provide greater information for improving the marksman's speed and/or accuracy in the future.

Similarly, the window 302b provides similar data as window 302a for a pistol speed and accuracy after training. Specifically, based on the results provided in the window 302a, the marksman may receive improvement instructions. The marksman may additionally practice those improvement instructions prior to being tested again. Similar to the window 302a, the data provided in the window 302b indicates the speed and/or accuracy of the marksman's plurality of shots, which may then be compared to an average marksman, an instructor and/or to the marksman's previous results.

The window 302c is similar to the static speed chart 310a and the static accuracy chart 310b from the windows 302a and 302b in that the pistol misses before training, the pistol time before training, the pistol misses after training, and the pistol time after training are provided. Specifically, the window 302c provides the speed and accuracy data are provided in a bar graph format to further compare the data between the windows 302a and 302b. This perspective provides a simplified view to determine the increased (or decreased) skill level after training.

The window 302d provides similar data for carbine speed and accuracy before training. Similar to the window 302a, the window 302d provides a first target accuracy level, which is depicted at a first predetermined percentage (such as 100%). A second target accuracy level may be provided at a second predetermined percentage (such as 75%). The marksman's actual results for speed and accuracy may additionally be provided against these target levels. From this data, analysis may be performed regarding improvement techniques that may be provided to the marksman.

The window 302e provides similar data for carbine speed and accuracy after training. As the marksman performance is determined both before and after training, analysis of the quality of training may be performed to improve future training exercises. As with the window 302b, the window 302e provides the after-training shot data for the marksman, as compared with desired speed and/or accuracy levels.

The window 302f provides similar data as the window 302c for the carbine before and after training. Compares the data from the window 302d with the information from the window 302e. Specifically, the static speed and static accuracy data as calculated from the window 302d is provided in a bar graph and is compared with the static speed and the static accuracy data from the window 302e. The window 302f provides the marksman and/or others with the information to determine an improvement resulting from the training.

Window 302g provides a physical assessment of the marksman for a particular training exercise. Specifically, while the windows 302a-302f provide information related to stationary shooting drills (or the stationary firing portion of a drill), the window 302g provides information related to mobile drills, where the marksman is traveling between points before firing the weapon. As an example, the marksman may start a drill 300 feet from the target 104a. The marksman may fire the weapon and then run to a point 200 feet from the target 104a. The marksman may continue running and firing, until the marksman has completed the exercise. As such, the window 302g provides an x-axis that indicates the distance of the marksman from the target 104a, while the y-axis indicates a time. Accordingly, desired instructor score is indicated with line 312a which represents a travel speed, and the desired student travel speed is indicated with line 312b. Accordingly, the computing device 102 may be configured for determining a travel speed score and/or fatigue of the marksman during the exercise, the line 312c will drop off because the marksman is slowing down and/or becoming less accurate.

The window 302h provides a graph that illustrates a first numerical score for head shots and a second numerical score for body shots. Accordingly, the graph may indicate that the marksman hit four head shots and two body shots, which equates to a total score of 26 (e.g., where a head shot is scored a “5” and the body shot is scored a “3”). Thus, the window 302h provides greater scores to the marksmen who accurately shoot a head portion of the target 104a.

The window 302i indicates a static speed and accuracy graph for each shot 1-10. The exterior web of the graph indicates the 100% desired instructor score, while the second circle indicates the desired student score. As indicated, the marksman depicted in the window 302i achieved the desired student speed, but was deficient on with his/her accuracy. From this information, the marksman can determine the areas needed for improvement.

FIG. 4 depicts a flowchart for analyzing a marksman training exercise, according to embodiments disclosed herein. As illustrated in block 430, a desired instructor speed and accuracy may be determined. At block 432, a desired student speed and accuracy may be determined. At block 434, the desired instructor speed and accuracy may be assigned a percentage. At block 436, the desired student speed and accuracy may be assigned a percentage. At block 438, the desired student speed and accuracy may be assigned a percentage. At block 438 marksman speed and accuracy may be received. At block 440, the marksman speed and accuracy data may be converted to percentages based on the desired instructor speed and accuracy percentages and the student speed and accuracy percentages. At block 442, at least a portion of the data may be provided for display.

As discussed above, embodiments disclosed herein include systems and methods for analyzing the accuracy and speed of a marksman in a training exercise. Accordingly, some embodiments are configured to compare the marksman speed and accuracy data to percentages that are based on desired student and instructor speed and accuracy data. With this analysis, the systems and methods are configured to provide useful information to improve the marksman's competence and the training exercise's effectiveness.

While particular embodiments have been illustrated and described herein, it should be understood that various other changes and modifications may be made without departing from the spirit and scope of the claimed subject matter. Moreover, although various aspects of the claimed subject matter have been described herein, such aspects need not be utilized in combination. It is therefore intended that the appended claims cover all such changes and modifications that are within the scope of the claimed subject matter.

Claims

1. A method for analyzing a marksman training exercise comprising:

determining a desired instructor speed and a desired instructor accuracy for a plurality of shots in the marksman training exercise;

determining a desired student speed and a desired student accuracy for the plurality of shots in the marksman training exercise;

assigning the desired instructor speed and the desired instructor accuracy a first percentage;

assigning the desired student speed and the desired student accuracy a second percentage;

receiving a marksman speed data and a marksman accuracy data for the plurality of shots by a marksman;

converting, by a computing device, the marksman speed data and the marksman accuracy data into respective percentages based on the first percentage and the second percentage; and

providing data related to the respective percentages for display.

2. The method of claim 1, further comprising utilizing the marksman speed data and the marksman accuracy data to determine an instruction for improvement.

3. The method of claim 1, further comprising:

receiving image data of the marksman; and

utilizing the image data to determine an instruction for improvement.

4. The method of claim 1, further comprising assigning a speed score to the marksman speed data and an accuracy score to the marksman accuracy data.

5. The method of claim 1, further comprising assigning a first numerical score to a head shot and a second numerical score to a body shot, the first numerical score and the second numerical score being combined to provide a total score for the marksman.

6. The method of claim 1, further comprising determining a travel speed of the marksman between shots and providing a travel speed score.

7. The method of claim 6, further comprising determining fatigue of the marksman, based on the travel speed.

8. A system for analyzing a marksman training exercise comprising:

a memory component that stores logic that cause the system to perform at least the following: determine a desired instructor speed and a desired instructor accuracy for a plurality of shots in the marksman training exercise; determine a desired student speed and a desired student accuracy for the plurality of shots in the marksman training exercise; assign the desired instructor speed and the desired instructor accuracy a first percentage; assign the desired student speed and the desired student accuracy a second percentage; receive a marksman speed data and a marksman accuracy data for the plurality of shots by a marksman; convert the marksman speed data and the marksman accuracy data into respective percentages based on the first percentage and the second percentage; utilize the marksman speed data and the marksman accuracy data to determine an instruction for improvement; and provide the instruction for improvement for display.

9. The system of claim 8, wherein the logic further causes the system to perform at least the following:

receiving image data of the marksman; and

utilizing the image data to determine the instruction for improvement.

10. The system of claim 8, wherein the logic further causes the system to assign a speed score to the marksman speed data and an accuracy score to the marksman accuracy data.

11. The system of claim 8, wherein the logic further causes the system to assign a first numerical score to a head shot and a second numerical score to a body shot, the first numerical score and the second numerical score being combined to provide a total score for the marksman.

12. The system of claim 8, wherein the logic further causes the system to determine a travel speed of the marksman between shots and providing a travel speed score.

13. The system of claim 12, wherein the logic further causes the system to determine fatigue of the marksman, based on the travel speed.

14. A non-transitory computer-readable medium for analyzing a marksman training exercise that stores a program that when executed by a computing device causes the computing device to perform at least the following:

determine a desired instructor speed and a desired instructor accuracy for a plurality of shots in the marksman training exercise;

determine a desired student speed and a desired student accuracy for the plurality of shots in the marksman training exercise;

assign the desired instructor speed and the desired instructor accuracy a first percentage;

assign the desired student speed and the desired student accuracy a second percentage;

receive a marksman speed data and a marksman accuracy data for the plurality of shots by a marksman;

utilize the marksman speed data and the marksman accuracy data to determine an instruction for improvement; and

provide the instruction for improvement for display.

15. The non-transitory computer-readable medium of claim 14, wherein the program further causes the system to perform at least the following:

receiving image data of the marksman; and

utilizing the image data to determine the instruction for improvement.

16. The non-transitory computer-readable medium of claim 14, wherein the program further causes the system to assign a speed score to the marksman speed data and an accuracy score to the marksman accuracy data.

17. The non-transitory computer-readable medium of claim 14, wherein the program further causes the system to assign a first numerical score to a head shot and a second numerical score to a body shot, the first numerical score and the second numerical score being combined to provide a total score for the marksman.

18. The non-transitory computer-readable medium of claim 14, wherein the program further causes the system to determine a travel speed of the marksman between shots and providing a travel speed score.

19. The non-transitory computer-readable medium of claim 18, wherein the program further causes the system to determine fatigue of the marksman, based on the travel speed.

20. The non-transitory computer-readable medium of claim 14, wherein the program further causes the computing device to convert the marksman speed data and the marksman accuracy data into respective percentages based on the first percentage and the second percentage.