Athlete Monitoring Program

Abstract

A system, method, and computer program product for athlete monitoring through a user interface is provided. The method includes receiving a first and second user input defining a current status of a user associated with a first and second readiness characteristic, respectively, prior to a training session or a match. From the first and second user input a readiness level for the user is determined. The method further includes receiving a third user input defining an exertion level of the user during a previous training session or a previous match, wherein the exertion level is associated with the perceived exertion level of the user during the training session or the previous match. Using the exertion level and duration of the session, a training load level of the previous training session or previous match is determined. The method further includes causing display of the readiness level for the user and the training load.

Description

TECHNOLOGICAL FIELD

Example embodiments of the present invention relate generally to computer technology and, more particularly, relate to methods, apparatuses, and computer program products for monitoring readiness and training loads for athletes.

BACKGROUND

Training and body preparedness have a direct effect on how an athlete performs and how susceptible they are to injury. Creating an appropriate and tailored training program based on athlete data can lead to better preparedness for the athlete and, ultimately, better success during a match or training session.

BRIEF SUMMARY

Understanding an athlete's training load and readiness for a training session or match can be beneficial for the athlete and coaches. For example, knowing the degree of training load an athlete underwent or is about to undergo can be useful for preventing injury and planning upcoming training sessions or strategy for matches. Additionally, knowing the readiness of the athlete, based on certain factors such as the amount and degree of sleep the athlete recently had, the athlete's mood, fatigue level, stress level, and soreness level, provides further insight that can aid in preventing injury and planning upcoming training sessions or strategy for matches. Moreover, knowing which muscles feel sore and the degree of soreness can also provide useful information and help to prevent overuse injuries.

Embodiments of the present invention provide various example methods, apparatuses, and computer program products for monitoring the training load, readiness level, and soreness of an athlete. In particular, in some embodiments, a user-friendly interface is provided that prompts an athlete to enter information related to different readiness characteristics prior to a training session or match. That information is used to create an overall readiness level for the athlete. Additionally, the athlete can be prompted to provide information concerning a recent training session, such as a training load (e.g., a degree of how hard the training session was). Further, the athlete can be prompted to provide information detailing specific muscles and the relative soreness level associated with the specific muscle. The resulting training load, readiness level, and soreness information can be presented in a user-friendly interface for use by the athlete or coaches. Such information can be combined with other related athlete's training load, readiness level, and/or soreness level, such as to provide information concerning an entire team. In this way, in various embodiments, the information is gathered in a passive (non-active) manner and is subjective to the athlete.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

Having described embodiments of the invention in general terms, reference will now be made to the accompanying drawings, which are not necessarily drawn to scale, and wherein:

FIG. 1 illustrates a system for athlete monitoring according to some example embodiments described herein;

FIG. 2 illustrates a block diagram of an athlete monitoring apparatus in accordance with some example embodiments described herein;

FIG. 3 illustrates an example display for enabling an athlete to begin entry of various information, according to some example embodiments described herein;

FIG. 4 is a flowchart illustrating an example readiness level calculation based on information provided by the athlete, according to some example embodiments described herein;

FIGS. 4A-E illustrate example displays of prompts for an athlete to enter a current status for example readiness characteristics, according to some example embodiments described herein;

FIG. 5 illustrates an example display of a user interface presenting a profile for an athlete that details various information for the athlete including a readiness level and a training load, according to some example embodiments described herein;

FIG. 6 illustrates an example display of a user interface presenting a profile for a team of athletes that detail various information for the team and athletes that form the team, including a team readiness level and a team training load, according to some example embodiments described herein;

FIG. 7 illustrates an example display of the user interface shown in FIG. 6, wherein the readiness level of each athlete on the team is broken down for ease of use, according to some example embodiments described herein;

FIG. 8 illustrates an example display of the user interface shown in FIG. 6, wherein the history of the team readiness level is illustrated in a user-friendly graph, according to some example embodiments described herein;

FIGS. 9-9A illustrate example displays of the user interface shown in FIG. 6, broken down into a specific subset of athletes on a team (e.g., the midfielders), according to some example embodiments described herein;

FIG. 10 illustrates an example display of the user interface that enables an athlete to input information concerning their training status as it corresponds with their health and ability to train at full capacity, according to some example embodiments described herein;

FIG. 11 illustrate example displays that enable an athlete to input information concerning their perceived training load, according to some example embodiments described herein;

FIG. 12 illustrates an example display that enables an athlete to input information concerning their heart rate zones during a previous training session in combination with their perceived training load, according to some example embodiments described herein;

FIG. 13 illustrates an example display that enables an athlete to input information concerning their level of hydration, accordingly to some example embodiments described herein;

FIG. 14 illustrate example displays that enable an athlete to select specific muscles and input associated soreness level of the muscles, according to some example embodiments described herein;

FIG. 14A illustrates an example display of the user interface shown in FIG. 5, wherein specific muscles and their soreness are presented for the athlete and/or coach, athletic trainer, strength & conditioning coach, medical staff, etc. to view historical soreness, according to some example embodiments described herein;

FIG. 15 illustrates an example display that enables an athlete to send a note to another user, such as another athlete or their coach, according to some example embodiments described herein;

FIG. 16 illustrates an example display that enables an athlete to report an injury to another user, such as their coach, athletic trainer, strength & conditioning coach, or medical staff, according to some example embodiments described herein;

FIG. 17 illustrates an example display that enables an athlete to provide recovery information, according to some example embodiments described herein; and

FIG. 18 is a flowchart illustrating an overview of various features related to athlete monitoring, according to some example embodiments described herein.

DETAILED DESCRIPTION

Some embodiments of the present invention will now be described more fully hereinafter with reference to the accompanying drawings, in which some, but not all embodiments of the invention are shown. Indeed, various embodiments of the invention may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will satisfy applicable legal requirements. Like reference numerals refer to like elements throughout.

As used herein, the terms “data,” “content,” “information” and similar terms may be used interchangeably to refer to singular or plural data capable of being transmitted, received, displayed and/or stored in accordance with various example embodiments. Thus, use of any such terms should not be taken to limit the spirit and scope of the disclosure.

The term “computer-readable medium” as used herein refers to any medium configured to participate in providing information to a processor, including instructions for execution. Such a medium may take many forms, including, but not limited to a non-transitory computer-readable storage medium (e.g., non-volatile media, volatile media), and transmission media. Transmission media include, for example, coaxial cables, copper wire, fiber optic cables, and carrier waves that travel through space without wires or cables, such as acoustic waves and electromagnetic waves, including radio, optical and infrared waves. Signals include man-made transient variations in amplitude, frequency, phase, polarization or other physical properties transmitted through the transmission media. Examples of non-transitory computer-readable storage media include a magnetic computer readable medium (e.g., a floppy disk, hard disk, magnetic tape, any other magnetic medium), an optical computer readable medium (e.g., a compact disc read only memory (CD-ROM), a digital versatile disc (DVD), a Blu-Ray disc, or the like), a random access memory (RAM), a programmable read only memory (PROM), an erasable programmable read only memory (EPROM), a FLASH-EPROM, or any other non-transitory medium from which a computer can read.

Additionally, as used herein, the term ‘circuitry’ refers to (a) hardware-only circuit implementations (e.g., implementations in analog circuitry and/or digital circuitry); (b) combinations of circuits and computer program product(s) comprising software and/or firmware instructions stored on one or more computer readable memories that work together to cause an apparatus to perform one or more functions described herein; and (c) circuits, such as, for example, a microprocessor(s) or a portion of a microprocessor(s), that require software or firmware for operation even if the software or firmware is not physically present. This definition of ‘circuitry’ applies to all uses of this term herein, including in any claims. As a further example, as used herein, the term ‘circuitry’ also includes an implementation comprising one or more processors and/or portion(s) thereof and accompanying software and/or firmware. As another example, the term ‘circuitry’ as used herein also includes, for example, a baseband integrated circuit or applications processor integrated circuit for a mobile phone or a similar integrated circuit in a server, a cellular network device, other network device, and/or other computing device.

Additionally, as used herein, although the figures and examples may refer to users such as athletes, players, coaches, athletic trainers, strength & conditioning coaches, nutritionists, athletic administrators, and medical staff, other types of users are contemplated (e.g., coordinators, executives, club directors, insurance coordinators, etc.). Indeed, example embodiments of the present invention may be used with any type of user.

FIG. 1 illustrates a system 101 for athlete monitoring according to some example embodiments. It will be appreciated that the system 101 as well as the illustrations in other figures are each provided as an example of an embodiment(s) and should not be construed to narrow the scope or spirit of the disclosure in any way. In this regard, the scope of the disclosure encompasses many potential embodiments in addition to those illustrated and described herein. As such, while FIG. 1 illustrates one example of a configuration of a system for athlete monitoring, numerous other configurations may also be used to implement embodiments of the present invention.

The system 101 may include an athlete monitoring apparatus 102 that may be configured to provide athlete monitoring functionality to any number of user terminals (e.g., athlete user terminal 110 and/or coach user terminal 120), which may, for example, be embodied as a laptop computer, tablet computer, mobile phone, desktop computer, workstation, or other like computing device. In some embodiments, a user terminal (e.g., athlete user terminal 110 and/or coach user terminal 120) may be remote from the athlete monitoring apparatus 102, in which case the user terminal (e.g., athlete user terminal 110 and/or coach user terminal 120) may communicate with the athlete monitoring apparatus 102 remotely, such as via network 100. Additionally or alternatively, the user terminal (e.g., athlete user terminal 110 and/or coach user terminal 120) may be implemented on the athlete monitoring apparatus 102 or may be directly connected to the athlete monitoring apparatus 102.

The athlete monitoring apparatus 102 may be configured to communicate with user terminal (e.g., athlete user terminal 110 and/or coach user terminal 120) via any of a variety of methods dependent upon the configuration of the system 101. For example, in embodiments in which an athlete monitoring apparatus 102 is disposed remotely from the user terminal (e.g., athlete user terminal 110 and/or coach user terminal 120), communication via the network 100 may occur by a variety of connections. The network 100 may be embodied in a local area network, the Internet, any other form of a network, or in any combination thereof, including proprietary private and semi-private networks and public networks. The network 100 may comprise a wireline network, wireless network (e.g., a cellular network, wireless local area network, a wireless wide area network, some combination thereof, or the like), or a combination thereof, and in some example embodiments comprises at least a portion of the Internet.

In some example embodiments, the athlete monitoring apparatus 102 may be embodied as or comprise one or more computing devices, such as, by way of non-limiting example, one or more servers configured to access the network 100. In some example embodiments, the athlete monitoring apparatus 102 may be implemented as a distributed system or a cloud-based entity that may be implemented within the network 100. In this regard, the athlete monitoring apparatus 102 may comprise one or more servers, a server cluster, one or more network nodes, a cloud computing infrastructure, some combination thereof, or the like.

FIG. 2 illustrates an athlete monitoring apparatus 102 in further detail, in accordance with some example embodiments. However, it should be noted that the components, devices, and elements illustrated in and described with respect to FIG. 2 may not be mandatory and, thus, on or more of the components, devices, or elements illustrated may be omitted in certain embodiments. Additionally, some embodiments may include further or different components, devices, or elements beyond those illustrated in and described with respect to FIG. 2.

Continuing with FIG. 2, processing circuitry 210 may be provided that is configured to perform actions in accordance with one or more example embodiments disclosed herein. In this regard, the processing circuitry 210 may be configured to perform and/or control performance of one or more functionalities of the athlete monitoring apparatus 102 in accordance with various example embodiments. The processing circuitry 210 may be configured to perform data processing, application execution, and/or other processing and management services according to one or more example embodiments. In some embodiments, the athlete monitoring apparatus 102 or a portion(s) or component(s) thereof, such as the processing circuitry 210, may be embodied as or comprise a circuit chip. The circuit chip may be configured to perform one or more operations for providing the functionalities described herein.

In some example embodiments, the processing circuitry 210 may include a processor 212 and, in some embodiments such as that illustrated in FIG. 2, may further include memory 214. The processing circuitry 210 may be in communication with or otherwise control any number of components or controllers configured to perform various operations consistent with some embodiments of the present invention. For example, with reference to FIG. 2, the processing circuitry 210 may be in communication with or otherwise control (e.g., via the processor 212) a user interface 216, a readiness level module 220, a training load module 230, a soreness module 240, an active monitoring module 250, and/or a communication interface 218. In some embodiments, the processing circuitry 210 may be embodied as a circuit chip (e.g., an integrated circuit chip) configured (e.g., with hardware, software, or a combination of hardware and software) to perform operations described herein. Along these lines, though the illustrated example embodiment of FIG. 2 details a number of different controllers and/or components in communication with or otherwise controlled by the processing circuitry 210, in some embodiments the processing circuitry 210 may be configured to directly control any operation described herein.

The processor 212 may be embodied in a number of different ways. For example, the processor 212 may be embodied as various processing means such as one or more of a microprocessor or other processing element, a coprocessor, a controller, or various other computing or processing devices including integrated circuits such as, for example, an ASIC (application specific integrated circuit), an FPGA (field programmable gate array), or the like. Although illustrated as a single processor, it will be appreciated that the processor 212 may comprise a plurality of processors. The plurality of processors may be in operative communication with each other and may be collectively configured to perform one or more functionalities of the athlete monitoring apparatus 102 as described herein. The plurality of processors may be embodied on a single computing device or distributed across a plurality of computing devices collectively configured to function as the athlete monitoring apparatus 102. In some example embodiments, the processor 212 may be configured to execute instructions stored in the memory 214 or otherwise accessible to the processor 212. As such, whether configured by hardware or by a combination of hardware and software, the processor 212 may represent an entity (e.g., physically embodied in circuitry in the form of processing circuitry 210) capable of performing operations according to embodiments of the present invention while configured accordingly. Thus, for example, when the processor 212 is embodied as an ASIC, FPGA, or the like, the processor 212 may comprise hardware for conducting the operations described herein. Alternatively, as another example, when the processor 212 is embodied as an executor of software instructions, the instructions may specifically configure the processor 212 to perform one or more operations described herein.

In some example embodiments, the memory 214 may include one or more non-transitory memory devices such as, for example, volatile and/or non-volatile memory that may be either fixed or removable. In this regard, the memory 214 may comprise a non-transitory computer-readable storage medium. It will be appreciated that while the memory 214 is illustrated as a single memory, the memory 214 may comprise a plurality of memories. The plurality of memories may be embodied on a single computing device or may be distributed across a plurality of computing devices collectively configured to function as the athlete monitoring apparatus 102. The memory 214 may be configured to store information, data, applications, instructions and/or the like for enabling the athlete monitoring apparatus 102 to carry out various functions in accordance with one or more example embodiments. For example, the memory 214 may be configured to buffer input data for processing by the processor 212. Additionally or alternatively, the memory 214 may be configured to store instructions for execution by the processor 212. As yet another alternative, the memory 214 may include one or more databases that may store a variety of files, contents, or data sets. Among the contents of the memory 214, applications may be stored for execution by the processor 212 to carry out the functionality associated with each respective application. In some cases, the memory 214 may be in communication with one or more of the processor 212, user interface 216, communication interface 218, readiness level module 220, training load module 230, soreness module 240, and active monitoring module 250 for passing information among components of the athlete monitoring apparatus 102.

The user interface 216 may be in communication with the processing circuitry 210 to receive an indication of a user input at the user interface 216 and/or to provide an audible, visual, mechanical, or other output to the user. As such, the user interface 216 may include, for example, a keyboard, a mouse, a joystick, a display, a touch screen display, a microphone, a speaker, and/or other input/output mechanisms. As such, the user interface 216 may, in some example embodiments, provide means for user control of athlete monitoring operations and/or the like. In some example embodiments in which the athlete monitoring apparatus 102 is embodied as a server, cloud computing system, or the like, aspects of the user interface 216 may be limited or the user interface 216 may not be present. In some example embodiments, one or more aspects of the user interface 216 may be implemented on the athlete user terminal 110 and/or the coach user terminal 120. Accordingly, regardless of implementation, the user interface 216 may provide input and output means to facilitate functions of the athlete monitoring apparatus 102 in accordance with one or more example embodiments.

The communication interface 218 may include one or more interface mechanisms for enabling communication with other devices and/or networks. In some cases, the communication interface 218 may be any means such as a device or circuitry embodied in either hardware or a combination of hardware and software that is configured to receive and/or transmit data from/to a network and/or any other device or module in communication with the processing circuitry 210. By way of example, the communication interface 218 may be configured to enable the athlete monitoring apparatus 102 to communicate with the athlete user terminal 110 and/or the coach user terminal 120 via the network 100. Accordingly, the communication interface 218 may, for example, include supporting hardware and/or software for enabling communications via cable, digital subscriber line (DSL), universal serial bus (USB), Ethernet, or other methods.

In some example embodiments, the processor 212 (or the processing circuitry 210) may be embodied as, include, or otherwise control a readiness level module 220, a training load module 230, a soreness module 240, and/or an active monitoring module 250. As such, the readiness level module 220, training load module 230, soreness module 240, and/or active monitoring module 250 may be embodied as various means, such as circuitry, hardware, a computer program product comprising computer readable program instructions stored on a computer readable medium (for example, the memory 214) and executed by a processing device (for example, the processor 212), or some combination thereof. The readiness level module 220, training load module 230, soreness module 240, and/or active monitoring module 250 may be implemented on separate apparatuses, the same apparatus, or any combination of apparatuses. The readiness level module 220, training load module 230, soreness module 240, and/or active monitoring module 250 may be capable of communication with one or more of the processor 212, memory 214, user interface 216, and communication interface 218 to access, receive, and/or send data as may be needed to perform one or more of the functionalities described herein.

In some embodiments, the athlete monitoring apparatus 102 may be configured to receive user input to enable a user (e.g., an athlete) to enter data to perform passive, subjective monitoring of conditions regarding the athlete. Some examples of such conditions include the training load of a recent training session, the current readiness level of the athlete, and soreness level of specific muscles for the athlete. Understanding an athlete's training load, readiness for a training session or match, and soreness level of specific muscles can be beneficial for the athlete and coaches. The monitored information could enable tailoring of the use of the athlete in upcoming training sessions and matches, ultimately reducing injury and increasing performance, among other things.

FIG. 3 shows an example user interface 290 that may be implemented by the athlete monitoring apparatus 102. The user interface 290 enables a user (e.g., an athlete) to enter data for monitoring of conditions regarding the athlete. The user interface 290 includes options for a user to select to begin entering data.

Selecting Readiness 300 enables a user to provide data regarding their current status for various readiness characteristics, as will be described in greater detail herein.

Selecting Status: Full Training 310 enables a user to toggle between various options for designating their training status in a training status user interface 800 shown in FIG. 10. For example, a user, Mike Gell, can select between Full Training 804, Modified Training 806, and Rehabilitative 808. In some embodiments, additional or alternative options for training status for a user are also available.

Selecting Training Load 320 enables a user to enter data regarding their perceived training load for prior training sessions or matches, as will be described in greater detail herein.

Selecting Hydration (USG) 330 enables a user to enter their current hydration level, such as seen in the hydration user interface 830 shown in FIG. 13.

Selecting Site Soreness 340 enables a user to enter data specifying muscles and their associated soreness level, as will be described in greater detail herein.

Selecting Send Note 350 enables a user to enter a note sending to another user, such as another athlete or a coach. An example note user interface 860 is shown in FIG. 15.

Selecting Report Illness/Injury 360 enables a user to report an illness or injury to another user, such as a coach, athletic trainer, strength & conditioning coach, doctor, or medical staff. An example report injury/illness user interface 870 is shown in FIG. 16. The report injury/illness user interface 870 enables a user to toggle between reporting an injury or an illness at 872 and also enables a user to specify the issue with text at 874.

Selecting Recovery Points 370 enables a user to enter data regarding current tasks associated with recovery. An example recovery user interface 880 is shown in FIG. 17. The example recovery user interface 880 includes the following categories: Nutrition/Hydration 882; Recover 884; and Rest 886. Each category includes selectable activity associated with each category. The user can select any activity performed by the user and save it. In this regard, the user can track planned activities to confirm that their recovery is on track.

In some embodiments, the user interface 290 can be embodied as an application on a user's smartphone or other device (e.g., the athlete monitoring apparatus 102). Additionally, in some embodiments, the user interface 290 may be tailored to the specific user. For example, user interface 290 in FIG. 3 shows the user as Mike Gell, the date as 9/24, and the ability to sign out.

In some embodiments, the athlete monitoring apparatus 102, such as through the readiness level module 220, may be configured to receive input from the user associated with readiness characteristics and determine a readiness level for the user. A flowchart illustrating calculation of the readiness level of the user is shown in FIG. 4.

In some embodiments, the athlete monitoring apparatus 102 may be configured to receive one or more user inputs defining a current status of a user associated with one or more readiness characteristics prior to a training session or a match. With reference to FIG. 4, at operation 402, the user starts the readiness questionnaire, such as by selecting Readiness 300 from the user interface 290 (shown in FIG. 3).

In some embodiments, when completing the readiness questionnaire, the user may input data regarding their current status for a readiness characteristic prior to a training session or match. A readiness characteristic may be any characteristic associated with the user that relates to (or affects) the readiness of the user for the upcoming training session or match. Such readiness characteristics may, in some cases, have an effect on how the user performs, how recovered a user is from a prior training session or match, how susceptible a user is to suffering injury, among other things. Some example readiness characteristics include the fatigue level of the user, the mood of the user, the stress level of the user, the soreness level of the user, the quality of sleep the user had the night before, and the number of hours of sleep the user had the night before, though other readiness characteristics may be used with embodiments of the present invention.

At operation 404, the user selects their current status for fatigue level, such as through the readiness user interface 490 for the fatigue level 491 shown in FIG. 4A. Examples of possible fatigue levels include: very fresh, fresh, fairly fresh, neutral, fairly tired, tired, and very tired, though other options may be used. At operation 406, the user selects their current status for mood level, such as through the readiness user interface 490 for the mood level 492 shown in FIG. 4B. Examples of possible mood levels include: very pleasant, pleasant, fairly pleasant, neutral, fairly unpleasant, unpleasant, and very unpleasant. At operation 408, the user selects their current status for stress level, such as through the readiness user interface 490 for the stress level 493 shown in FIG. 4C. Examples of possible stress levels include: very calm, calm, fairly calm, neutral, fairly anxious, anxious, and very anxious. At operation 410, the user selects their current status for soreness level, such as through the readiness user interface 490 for the soreness level 494 shown in FIG. 4D. Examples of possible soreness levels include: very good, good, fairly good, neutral, fairly tight/sore, tight/sore, and very tight/sore. At operation 412, the user selects their current status for sleep quality level, such as through the readiness user interface 490 for the sleep quality level 495 shown in FIG. 4E. Examples of possible sleep quality levels include: very restful, restful, fairly restful, neutral, fairly restless, restless, and very restless. Additionally, at operation 414, the user inputs the number of hours of sleep they received the night before. Finally, the user submits the data for consideration by the athlete monitoring apparatus 102 at operation 420.

Additionally, the athlete monitoring apparatus 102 may be configured to determine a readiness level for the user prior to the training session or the match based at least on the one or more current status of the user associated with the one or more readiness characteristics. The readiness level may be determined from one or more of the readiness characteristics (e.g., two, three, four, five, etc.). For example, at operation 424, a value is assigned for each readiness characteristic based on the current status selected by the user (e.g., a neutral selection is inputted as 0, a positive selection is inputted as one of +1, +2, or +3 depending on the selection, and a negative selection is inputted as one of −1, −2, or −3 depending on the selection). In some embodiments, the inputted values associated with the readiness characteristics can be used to determine an overall readiness level for the user.

Additionally, in some embodiments, the athlete monitoring apparatus 102 may be configured to apply weights to one or more of the readiness characteristics for determination of the overall readiness level of the user prior to a training session or a match. For example, a first weighted factor may be applied to a first readiness characteristics (e.g., fatigue level) and a second weighted factor may be applied to a second readiness characteristic (e.g., mood level). In such a case, the first weighted factor may be different than the second weighted factor. For example, the first weighted factor could be greater than the second weighted factor, such that the current status of the user for their fatigue level has a greater effect on the overall readiness level of the user than the current status of the user for their mood level.

With reference to FIG. 4, at operation 428, the inputted values (weighted or not) may be subtracted from an optimum readiness level (e.g., 100) per readiness characteristic. In some embodiments, the weights to each readiness characteristic may be pre-set into the optimum readiness level such that inputted values are applied to only the specific pre-set optimum readiness level value for that readiness characteristic. Then, the readiness level is calculated at operation 430 based on the subtracted values from the optimum readiness level.

In some embodiment, the athlete monitoring apparatus 102 may be configured to check the calculated readiness level for theoretical accuracy. For example, each readiness characteristic has a threshold value associated with certain inputted values that are negative to ensure the overall readiness score for a user will not be too high as the negative value for characteristic should signal to the coach, trainer, medical staff, etc. that there is a potential issue. For example, fatigue level may be assigned only 15 points of the overall readiness level. However, applying the inputted value of −3 to the threshold for fatigue would necessitate that the overall readiness score not be higher than 75 for example and therefore the impact of the inputted value of −3 for fatigue would be greater than the allotted value of 15 points in the standard calculation method.

Thus, at operation 440, the values for each category are checked to determine if there is a negative threshold. If there are no negative threshold values, then, at operation 450, the final readiness is generated based on the standard calculation method (e.g., operation 430). However, if there are negative threshold values, then, at operation 442, a maximum value for the readiness score is determined based on the lowest threshold value for all of the readiness categories. Then, at operation 444, the adjusted weighted values for each category instead of the standard weighted values are subtracted from the maximum readiness score value to determine the threshold readiness score calculation method value. At operation 446, the resulting readiness level from the threshold method is compared to the readiness level calculated using the standard calculation method. If the resulting readiness level from the threshold method is less than the readiness level calculated using the standard method, then the readiness level calculated using the threshold method is used. However, if the resulting readiness level from the threshold method is greater than or equal to the readiness level calculated using the standard method, then the readiness level from the standard method is used at operation 455.

In some embodiments, the athlete monitoring apparatus 102 may be configured to determine the readiness level of a user based on at least one of an historic readiness level for the user or an historic status of the user associated with one or more of the readiness characteristics. In this regard, in some embodiments, the determination of the readiness level may be tailored for each specific user's habits or tendencies. For example, some users may require less sleep than others. Additionally, a prior day's readiness level may be used to calculate the current readiness level (e.g., a threshold amount of change may be applied such that a drastic change in readiness level is difficult or, in some cases, not possible). Along these lines, using historic data, the athlete monitoring apparatus 102 can dynamically learn and tailor the readiness level calculation to the specific user for greater accuracy.

The above described method for determining the readiness level provides one example method for determining the readiness level of a user for an upcoming training session or match. Embodiments of the present invention are not meant to be limited to the above described method, as other methods are contemplated (e.g., percentages, layered levels, etc.).

In some embodiments, the athlete monitoring apparatus 102 may be configured to cause display of the readiness level for the user, such as in a graphical user interface. Additionally, in some embodiments, the specific results for the current status of each readiness characteristic may also be displayed. Such information could be kept in memory and historic data could be displayed in the graphical user interface, allowing for a user-friendly interface that may include usable information, including graphs, trends, etc. An example user interface 500 is shown in FIG. 5.

With reference to FIG. 5, each user (e.g., athlete) may have a dedicated user page 502 with a user profile that may include specific information regarding the user (e.g., name, position, team name, location, etc.). The overview 504 of the user in the user interface 500 may include information created or used by the athlete monitoring apparatus 102, such as for creating a graphical user interface useful for managing activities and readiness of the user. In this regard, the readiness level 512 of the user may be displayed in the readiness breakdown 510. The readiness level 512 may be displayed as a number (e.g., 52) out of 100 (e.g., the optimum readiness level) as shown, or, in some cases, could be displayed as another identifier (e.g., percentage, relative term (e.g., low, medium, high), among other things.

Additionally, in some embodiments, the readiness level 512 may be displayed in a color (e.g., red) that may provide additional information regarding the relative readiness level. For example, a good (or high) readiness level may be displayed in green, a neutral (or medium) readiness level may be displayed in yellow, and a poor (or low) readiness level may be displayed in red. Though the above example displays the readiness level in a color, other identifier may be used (e.g., arrows, fill bar, etc.). For example, a fill bar is shown around the readiness level “52” that fills 52% of the circle.

Additionally, in some embodiments, the selected current status of the user for each readiness characteristic is also displayed (at 514) to provide additional information. Further, additional information, such as percentage of completion of the readiness questionnaire and percentage decrease from a prior readiness level may also be presented (at 516).

In some embodiments, a further breakdown 506 of information related to the readiness level of the user may be displayed in the user interface 500. For example, a graph showing historic readiness levels is presented at 520 and graphs showing historic status of each readiness characteristic is presented at 521. In some embodiments, each readiness characteristic may be further broken down at 524 with more useful information, including a designation of if the status of the user is at critical levels (e.g., critical 526 and mod-high 527).

In some embodiments, the athlete monitoring apparatus 102 may be configured to determine an instance in which at least one of the current status of the user associated with one or more readiness characteristics or the readiness level of the user is less than a critical threshold and, in response, cause an alert to be presented to the user (or another user, such as a coach of the user). Such an alert may provide information associated with the readiness characteristic and/or readiness level. In some embodiments, the alert may include a recommendation associated with readiness characteristic and/or readiness level, such as a proposed strategy or training load for the user in an upcoming training session or match and/or specific recovery methods or exercises.

The above described embodiments of the present invention of the athlete monitoring apparatus 102 are configured to calculate the readiness level based on passive, subjective data that is entered by the user prior to a training session or match. Some additional information that may be useful with some embodiments of the present invention includes active monitoring information. Active monitoring information may be any type of data that is collected in real-time, such as during the training session or match. Such active monitoring information may be obtained in many different ways, including for example, using sensors associated with the user during the training session or match, such as a heart rate monitor, a GPS positioning sensor, a position sensor, an accelerometer, etc. In such a manner, the active monitoring information may be objective, as opposed to the subjective data entered by the user into the athlete monitoring apparatus 102 through, for example, the readiness level module 220, the soreness module 240, and the training load module 230. In some embodiments, the active monitoring information may be provided to the athlete monitoring apparatus 102 through the active monitoring module 250.

In some embodiments, the athlete monitoring apparatus 102, such as through the active monitoring module 250, may be configured to receive active monitoring data. The active monitoring data may include at least one of GPS data associated with the user during a training session or a match or heart rate data associated with the user during a training session or a match.

In some embodiments, the athlete monitoring apparatus 102 is configured to compare the active monitoring data associated with the user with the readiness level of the user. Then, in some embodiments, the athlete monitoring apparatus 102 may be configured to provide an alert based on at least the comparison of the active monitoring data with the readiness level. For example, the athlete monitoring apparatus 102 may be configured to provide an alert in an instance in which the active monitoring data senses a condition of the user that may be critical, particularly based on readiness characteristics and/or readiness level of the user. As an example, a certain heart rate variation or heart rate level may be considered critical in an instance in which the user has a low readiness level.

In some embodiments, the athlete monitoring apparatus 102 is configured to provide a user interface for an entire team. For example, with reference to FIG. 6, the user interface 600 can include an overall team view 602 and present an overview 604. In the overview, a readiness breakdown 610 can be presented. The readiness breakdown 610 can include an overall team readiness score 612, along with other valuable overall team numbers, such as different readiness characteristics 614, percentage of completion of the readiness questionnaire, and percentage decrease from a prior readiness level may also be presented (at 616).

A further detailed overview 606 can be also presented with sortable columns: players 660, readiness 662 (which includes pertinent readiness details and graphs), sleep 664, hydration 666, training load 668, and soreness 670. Additionally, the detailed overview 606 can include easy identifiers, such as colors associated with various readiness scores for each player (see 672). FIG. 7 shows a further breakdown based on readiness of the players on the team (see 680). This view is also sortable and provides further detailed information including the following columns: player 682, position 684, readiness score 686, percentage decrease or increase from prior scores 688, and detailed scores for each readiness characteristic 689. Like the other views, this view may also provide an easy to spot color coding 683 based on the readiness score (for example).

Similar to the individual readiness level, the athlete monitoring apparatus 102 may be configured to provide a user interface view 700 that displays a historical graph 710 of overall team readiness score 712 over time (e.g. days 714). In some embodiments, other groups or subgroups could be used (players, position based, etc.) with the ability to compare players or groups to each other and the team. Likewise, other gathered information can be displayed (specific readiness characteristic scores, soreness levels, training loads, etc.).

FIGS. 9 and 9A show an additional view 720 that is focused on players for a specific position (e.g., midfielders) 721. Similar to detailed herein, the view 720 can include a position readiness breakdown 722 (e.g., an average of each player's corresponding score for the players at that position), a training load 724 (as will be described herein), and an overview tab 726. FIG. 9A shows the ability of a user to view more specific details regarding the readiness 728 of the players at the selected position.

Returning to FIG. 3, in some embodiments, the athlete monitoring apparatus 102 may be configured to enable input regarding a user's status for an upcoming or prior training session or match 310. After selection by a user, the user may be presented with an interface 800 for inputting their status for the training session—see FIG. 10. In the depicted example, a user 802 can select between full training capacity 804, modified training status 806, and rehabilitative status 810—though other athlete status could be inputted in various embodiments (e.g., injured, etc.). Such information is useful for understanding and tracking the players status and determining which players are available for training and to what degree.

As noted herein, in some embodiments, the athlete monitoring apparatus 102 may be configured to determine a training load level for a user (such as through the training load module 230) associated with a previous training session or previous match. FIG. 3 shows an example user interface that enables the user to select the training load 320 option to begin inputting information to determine the training load.

FIG. 11 shows an example training load interface 810. Each user may input the category of training 812 (e.g., different types of training sessions, such as those shown and described with respect to FIG. 10). The user may also provide a training intensity 814 that it associates with the training session or match that was just played. FIG. 11 depicts a slide bar option for selecting different training intensities (though other selecting options are contemplated). Example training intensities (i.e., exertion levels) include: Rest, Easy, Mild, Moderate, Hard, Very Hard, and Exhausting (though other levels are contemplated). A user may also input the duration of the prior training session or match. The coach also has the option to input target training loads for each upcoming training session. The option for the coach to input the training load information provides information that enables a coach to see the difference between the intended training intensity (as perceived by the coach) and the perceived training intensity by the player (inputted through the user interface of FIG. 11). This information can be used in calculating the training load of a player and/or team.

FIG. 12 shows a similar user interface 820 that is used in tandem with the training load to allow the player to provide similar inputs with the addition of heart rate zone data (day of the training session or match 821, training category 822, perceived training intensity level 824, duration 826, and heart rate zones associated with the training 828 (as manual inputs derived from heart rate hardware device)).

In this regard, the athlete monitoring apparatus 102, such as through the training load module 230, may be configured to determine a training load level of a previous training session or previous match for a user based at least on the exertion level (e.g., training intensity) and a length of time of the previous training session or the previous match. In some embodiments, as may be described herein, when determining the training load, data can be displayed to coaches based on the differences between the coaches perceived training intensity and the players perceived training intensity with respect to that training session or match to allow the coach to more accurately assess the intensity of their training sessions over time.

In some embodiments, the athlete monitoring apparatus 102 may be configured to display the training load in a user interface. For example, FIG. 5 provides an example display of a training load overview 530. This overview 530 can include a training load score 532 for the most previous training session or match. Additionally, historical training load scores 534 can be displayed (e.g., for the second most recent training session or match). Additional information can also be displayed, such as duration, comparison to overall team training loads, comparison to coach perceived training load, etc.). Additionally, graphs can be used to show historical training loads (e.g., selection capabilities near 506). FIG. 6 shows a team user interface that include training load information for the overall team 630. This includes the most recent training load 632 and historical training loads 634, along with other related information. Like a readiness score, the training load (or training intensity 712) can be displayed in a sortable historical graph—shown in FIG. 8. Further, position breakdowns can be used—see e.g., the training load 724 shown in FIGS. 9 and 9A.

In some embodiments, the athlete monitoring apparatus 102 may be configured to cause display of the readiness level for the user and the training load of the previous training session or the previous match by providing a graphical user interface with the readiness level of the user and the training load of the previous training session or the previous match displayed in an associated form so as to enable comparison of the readiness level of the user and the training load of the previous training session or the previous match. For example, FIG. 5 shows the readiness score breakdown 510 proximate the training load overview 530 for easy comparison. Likewise, team (FIG. 6) and position views (FIGS. 9, 9A) can be displayed.

In some embodiments, the athlete monitoring apparatus 102 may be configured to compare the readiness level for the user and the training load of the previous training session or the previous match. Such comparison could be based on underlying comparison characteristics or algorithms that take into account the association between the prior training loads and the current readiness score. This comparison could be displayed for ease of use by the coach in determining what training session to implement or which players to use or rest. In some embodiments, a recommendation could be provided regarding the user based at least on the comparison of the readiness level for the user and the training load of the previous training session or the previous match. Such recommendations could include a suggested training load for an upcoming training session or an upcoming game, how to utilize a player (how long, what level of intensity, etc.), or specific recovery protocols (foam roller, ice bath, pool sessions, corrective exercises, sleep habits, etc.)

In some embodiments, an alert could be presented when a training load meets a certain critical threshold. Similarly, the alert could be based on the resulting comparison of the training load and readiness score. The alert could provide a recommendation associated with the at least one of the current status of the user associated with the first readiness characteristic, the current status of the user associated with the second readiness characteristic, or the training load for the previous training session or the previous match that was greater than the critical threshold.

In some embodiments, an overall readiness score could be determined. The overall readiness score could be based on at least the readiness level of the user and the training load of the previous training session or the previous match. Additional information could be used (e.g., the comparison of the readiness level to the training load, a soreness level (as described more herein), or other information). Weights could be assigned to the factors to help determine the overall readiness score.

The above examples could be applied to the team as a whole, position groups, or individual players, which could help tailor specific upcoming training sessions or match strategies for the coach.

Returning to FIG. 3, the athlete monitoring apparatus 102 may be configured to provide a hydration level of a user. In this regard a use can select the hydration option 330 and then input the estimated hydration level using the user interface 830 shown in FIG. 13.

In some embodiments, the athlete monitoring apparatus 102 may be configured to determine a soreness level and/or track soreness levels for players, such as through the soreness module 240. FIG. 3 shows a soreness option 340 for selection by a user.

FIG. 14 provides an illustration (e.g., 841, 842, 843) of an example process that a user can go through to identify soreness levels. For example, an image of a user's muscle system 844 in the form of the body can be presented to the user. The user can provide an input selecting a muscle. Additionally, the user can select a soreness level for the selected one or more muscles (see 846). Example soreness levels include: a little soreness; sore, can move ok; limits movement; struggling to move; and painful to move. Additionally, colors may be associated with the different soreness levels. In the depicted embodiment, the color may be presented over or on the muscle (e.g., highlight the muscle) to indicate the association that the user makes. The user, using the flip option 848 can flip the image of the body to select additional muscles located on the back of the user. By repeating this process, the user can build up a color coded image representing the soreness level of various muscles in their body.

In some embodiments, the athlete monitoring apparatus 102 may be configured to cause display of the historical soreness level for the user over time. For example, FIG. 14A shows a soreness overview 852 with a table 852 that identifies muscles and/or muscles groups and the associated soreness level for each corresponding with the date. This can be displayed on a player-by-player basis or in various groups (e.g., teams, position groups, etc.).

As is consistent with described embodiments herein, different soreness levels can be associated with critical thresholds (pre-set or set by the coach). Falling below the thresholds can result in alerts and/or recommendations. Such recommendation may include resting the player, focusing on certain rehabilitative techniques, corrective exercises, changing training load or playing status plans, etc.

Returning to FIG. 3, a user can also send a note 350, report and illness/injury 360, and/or enter recovery points 370. FIG. 15 illustrates an example note taking interface 860 that enables notes to be saved. These notes can be private or can be sent to appropriate users (e.g., coach, strength coach, position coach, etc.). FIG. 16 illustrates an example reporting interface 870. The user can report an injury or illness with the drop down menu (e.g., 872)—though other input means are contemplated. Additionally, the user can specify the issue associated with the injury or illness (at 874). Finally, FIG. 17 illustrates an example recovery interface 880. In the recovery interface 880, the user can enter information about recent nutrition/hydration events at 882. For example, if the user ate breakfast, they would click the breakfast box accordingly. Other options include: lunch; dinner; snacks; training hydration; protein; and shakes. Additionally, a user can enter recovery information at 884. Example of recovery events include: jogging, stretching, massage, biking, ice bath, shower, etc. Finally, the user can enter rest information at 886. Example rest information includes nap and sleep over a certain hour mark (e.g., 7 hours). This information can be used to provide a recovery profile for a user and can aid in tracking a link between events and recovery time (e.g., over time). The recovery system can include points associated with completing each activity throughout the day that can be enabled, disabled, or customized. This will help the coaches tailor a future recovery program for the player.

FIG. 18 illustrates an example flowchart 900 detailing creation of an example user interface (such as described herein in various embodiments). At operation 902, a user logs in.

At operation 910, a user completes the readiness questionnaire (such as described herein). Then, at operation 912, the readiness score is calculated, such as using the readiness level module 220. Then, at operation 914 alerts based on the readiness scores may be provided to the user or coaches. In some embodiments, the alerts may be provided based on thresholds that are relative to day-to-day change allowance and standard deviation.

At operation 920, the user decides whether a training is performed today. If not, then a user submits that it was an Off day at 921. If training did occur, then the user submits training load information (such as described herein) at operation 922. Then, such as through the training load module 230, the training load is calculated at operation 924.

At operation 930 a user decides whether there is soreness in their muscles. If there is not, then the user skips the soreness entry or submits that there is no soreness at operation 931. At operation 932, the user submits soreness site (e.g., the muscle) and the associated soreness level (such as described herein). Then, such as through the soreness module 240, a cumulative soreness level is calculated (e.g., for a muscle, muscle groups, the user overall, etc.). Then, at operation 936 alerts based on the soreness scores may be provided to the user or coaches. In some embodiments, the alerts may be provided based on thresholds that are relative to day-to-day change allowance and standard deviation.

At operation 940, the user interface is populated, showing overview averages and tables according to embodiments described herein. The user interface may include readiness and training load breakdowns, alerts, charting, player drill downs views, etc. In this regard, the example embodiments of the present invention provide a useful user interface for athlete monitoring.

FIGS. 4 and 18 each illustrate a flowchart of a system, method, and computer program product according to some example embodiments. It will be understood that each block of the flowcharts, and combinations of blocks in the flowcharts, may be implemented by various means, such as hardware and/or a computer program product comprising one or more computer-readable mediums having computer readable program instructions stored thereon. For example, one or more of the procedures described herein may be embodied by computer program instructions of a computer program product. In this regard, the computer program product(s) which embody the procedures described herein may comprise one or more memory devices of a computing device (for example, the memory 214) storing instructions executable by a processor in the computing device (for example, by the processor 212). In some example embodiments, the computer program instructions of the computer program product(s) which embody the procedures described above may be stored by memory devices of a plurality of computing devices. As will be appreciated, any such computer program product may be loaded onto a computer or other programmable apparatus (for example, an athlete monitoring apparatus 102 and/or other apparatus) to produce a machine, such that the computer program product including the instructions which execute on the computer or other programmable apparatus creates means for implementing the functions specified in the flowchart block(s). Further, the computer program product may comprise one or more computer-readable memories on which the computer program instructions may be stored such that the one or more computer-readable memories can direct a computer or other programmable apparatus to function in a particular manner, such that the computer program product may comprise an article of manufacture which implements the function specified in the flowchart block(s). The computer program instructions of one or more computer program products may also be loaded onto a computer or other programmable apparatus (for example, an athlete monitoring apparatus 102 and/or other apparatus) to cause a series of operations to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus implement the functions specified in the flowchart block(s).

Accordingly, blocks of the flowcharts support combinations of means for performing the specified functions and combinations of operations for performing the specified functions. It will also be understood that one or more blocks of the flowcharts, and combinations of blocks in the flowcharts, can be implemented by special purpose hardware-based computer systems which perform the specified functions, or combinations of special purpose hardware and computer instructions.

Many modifications and other embodiments of the inventions set forth herein will come to mind to one skilled in the art to which these inventions pertain having the benefit of the teachings presented in the foregoing descriptions and the associated drawings. Therefore, it is to be understood that the inventions are not to be limited to the specific embodiments disclosed and that modifications and other embodiments are intended to be included within the scope of the appended claims. Moreover, although the foregoing descriptions and the associated drawings describe example embodiments in the context of certain example combinations of elements and/or functions, it should be appreciated that different combinations of elements and/or functions may be provided by alternative embodiments without departing from the scope of the appended claims. In this regard, for example, different combinations of elements and/or functions than those explicitly described above are also contemplated as may be set forth in some of the appended claims. Although specific terms are employed herein, they are used in a generic and descriptive sense only and not for purposes of limitation.

Claims

1. A method comprising:

receiving a first user input defining a current status of a user associated with a first readiness characteristic prior to a training session or a match;

receiving a second user input defining a current status of the user associated with a second readiness characteristic prior to the training session or the match;

determining, by a processor, a readiness level for the user prior to the training session or the match based at least on the current status of the user associated with the first readiness characteristic and the current status of the user associated with the second readiness characteristic;

receiving a third user input defining an exertion level of the user during a previous training session or a previous match, wherein the exertion level is associated with the perceived exertion level of the user during the training session or the previous match;

determining a training load level of the previous training session or previous match for the user based at least on the exertion level and a length of time of the previous training session or the previous match; and

causing display of the readiness level for the user and the training load of the previous training session or previous match.

2. The method of claim 1, wherein causing display of the readiness level for the user and the training load of the previous training session or the previous match comprises providing a graphical user interface with the readiness level of the user and the training load of the previous training session or the previous match displayed in an associated form so as to enable comparison of the readiness level of the user and the training load of the previous training session or the previous match.

3. The method of claim 1 further comprising:

comparing the readiness level for the user and the training load of the previous training session or the previous match; and

causing display of the comparison of the readiness level for the user and the training load of the previous training session or the previous match.

4. The method of claim 1 further comprising:

comparing the readiness level for the user and the training load of the previous training session or the previous match; and

providing a recommendation regarding the user based at least on the comparison of the readiness level for the user and the training load of the previous training session or the previous match.

5. The method of claim 4, wherein the recommendation comprises a suggested training load for an upcoming training session or an upcoming match.

6. The method of claim 1 further comprising:

comparing the readiness level for the user and a proposed training load for an upcoming training session or an upcoming match; and

providing a recommendation regarding the user based at least on the comparison of the readiness level for the user and the proposed training load of the upcoming training session or the upcoming match.

7. The method of claim 1, wherein determining the readiness level of the user comprises applying a first weighted factor to the current status of the user associated with the first readiness characteristic and a second weighted factor to the current status of the user associated with the second readiness characteristic, wherein the first weighted factor is different than the second weighted factor.

8. The method of claim 1 further comprising:

determining an instance in which at least one of the current status of the user associated with the first readiness characteristic, the current status of the user associated with the second readiness characteristic, or the training load for the previous training session or the previous match is less than a critical threshold; and

causing an alert to be presented, wherein the alert provides information associated with the at least one of the current status of the user associated with the first readiness characteristic, the current status of the user associated with the second readiness characteristic, or the training load for the previous training session or the previous match that was less than the critical threshold.

9. The method of claim 8, wherein the alert further provides a recommendation associated with the at least one of the current status of the user associated with the first readiness characteristic, the current status of the user associated with the second readiness characteristic, or the training load for the previous training session or the previous match that was less than the critical threshold.

10. The method of claim 1 further comprising:

determining an overall readiness score for the user based on at least the readiness level of the user and the training load of the previous training session or the previous match; and

causing display of the overall readiness score.

11. The method of claim 1 further comprising:

receiving a fourth user input defining at least one muscle;

receiving a fifth user input defining a soreness level for the at least one muscle; and

causing display of the soreness level for the muscle.

12. The method of claim 11 further comprising:

determining an overall readiness score for the user based on at least the readiness level of the user, the training load of the previous training session or the previous match, and the soreness level for the at least one muscle; and

causing display of the overall readiness score.

13. The method of claim 11 further comprising:

providing a graphical user interface with the readiness level of the user, the training load of the previous training session or the previous match, and the soreness level for the at least one muscle displayed so as to be associated with the user.

14. The method of claim 1, wherein the training load for the previous training session or the previous match defines a training load for the user, wherein the user comprises a first player on a team such that the readiness level of the user and the training loading for the user corresponds to the readiness level for the first player and the training load for the first player, wherein the team comprises a plurality of players including the first player, the method further comprising:

determining a team readiness level for the team based at least on the readiness level for the first player and a second readiness level for a second player;

determining a team training load for the team for the previous training session or the previous match based at least on the training load for the first player and a second training load for the second player; and

causing display of the team readiness level and the team training load.

15. The method of claim 14, wherein the method further comprises:

providing a graphical user interface configured to display:

a listing of the plurality of players;

a corresponding readiness level and training load for each of the plurality of players;

the team readiness level for the team; and

the team training load for the team for the previous training session or the previous match, wherein the team readiness level and the team training load for the previous training session or the previous match are displayed in an associated form so as to enable comparison of the team readiness level and the team training load of the previous training session or the previous match.

16. The method of claim 15, wherein the team readiness level and the team training load are sortable based at least on a position of each of the plurality of players for the team.

17. The method of claim 14 further comprising:

comparing the team training load to an intended training load; and

causing display of the comparison of the team training load to the intended training load.

18. The method of claim 1, wherein determining the readiness level further comprises determining the readiness level based on at least one of an historic readiness level for the user or an historic status of the user associated with the first readiness characteristic.

19. The method of claim 1 further comprising:

receiving active monitoring data, wherein the active monitoring data includes at least one of GPS data associated with the user during a training session or a match or heart rate data associated with the user during a training session or a match;

comparing the active monitoring data with the readiness level; and

providing an alert based on at least the comparison of the active monitoring date with the readiness level.

20. Computer program product comprising a non-transitory computer readable medium having program code portions stored thereon, the program code portions being configured, when said program product is run on a computer or network device, to:

receive a first user input defining a current status of a user associated with a first readiness characteristic prior to a training session or a match;

receive a second user input defining a current status of the user associated with a second readiness characteristic prior to the training session or the match;

determine a readiness level for the user prior to the training session or the match based at least on the current status of the user associated with the first readiness characteristic and the current status of the user associated with the second readiness characteristic;

receive a third user input defining an exertion level of the user during a previous training session or a previous match, wherein the exertion level is associated with the perceived exertion level of the user during the training session or the previous match;

determine a training load level of the previous training session or previous match for the user based at least on the exertion level and a length of time of the previous training session or the previous match; and

cause display of the readiness level for the user and the training load of the previous training session or previous match.

21. The computer program product of claim 20, wherein the program code portions are further configured when said program product is run on a computer or network device to cause display of the readiness level for the user and the training load of the previous training session or the previous match by providing a graphical user interface with the readiness level of the user and the training load of the previous training session or the previous match displayed in an associated form so as to enable comparison of the readiness level of the user and the training load of the previous training session or the previous match.

22. The computer program product of claim 20, wherein the program code portions are further configured when said program product is run on a computer or network device to:

compare the readiness level for the user and the training load of the previous training session or the previous match; and

cause display of the comparison of the readiness level for the user and the training load of the previous training session or the previous match.

23. The computer program product of claim 20, wherein the program code portions are further configured when said program product is run on a computer or network device to:

compare the readiness level for the user and a proposed training load for an upcoming training session or an upcoming match; and

provide a recommendation regarding the user based at least on the comparison of the readiness level for the user and the proposed training load of the upcoming training session or the upcoming match.

24. The computer program product of claim 20, wherein the program code portions are further configured when said program product is run on a computer or network device to:

determine an instance in which at least one of the current status of the user associated with the first readiness characteristic, the current status of the user associated with the second readiness characteristic, or the training load for the previous training session or the previous match is less than a critical threshold; and

cause an alert to be presented, wherein the alert provides information associated with the at least one of the current status of the user associated with the first readiness characteristic, the current status of the user associated with the second readiness characteristic, or the training load for the previous training session or the previous match that was less than the critical threshold.

25. The computer program product of claim 20, wherein the program code portions are further configured when said program product is run on a computer or network device to:

receive a fourth user input defining at least one muscle;

receive a fifth user input defining a soreness level for the at least one muscle; and

cause display of the soreness level for the muscle.

26. The computer program product of claim 20, wherein the training load for the previous training session or the previous match defines a training load for the user, wherein the user comprises a first player on a team such that the readiness level of the user and the training loading for the user corresponds to the readiness level for the first player and the training load for the first player, wherein the team comprises a plurality of players including the first player, wherein the program code portions are further configured when said program product is run on a computer or network device to:

determine a team readiness level for the team based at least on the readiness level for the first player and a second readiness level for a second player;

determine a team training load for the team for the previous training session or the previous match based at least on the training load for the first player and a second training load for the second player; and

cause display of the team readiness level and the team training load.

27. The computer program product of claim 26, wherein the program code portions are further configured when said program product is run on a computer or network device to:

provide a graphical user interface configured to display:

a listing of the plurality of players;

a corresponding readiness level and training load for each of the plurality of players;

the team readiness level for the team; and

the team training load for the team for the previous training session or the previous match, wherein the team readiness level and the team training load for the previous training session or the previous match are displayed in an associated form so as to enable comparison of the team readiness level and the team training load of the previous training session or the previous match.

28. The computer program product of claim 20, wherein the program code portions are further configured when said program product is run on a computer or network device to:

receive active monitoring data, wherein the active monitoring data includes at least one of GPS data associated with the user during a training session or a match or heart rate data associated with the user during a training session or a match;

compare the active monitoring data with the readiness level; and

provide an alert based on at least the comparison of the active monitoring date with the readiness level.