Tag Archives: soft tissue injuries

Predicting Soft-Tissue Injuries In Rugby / Rugby League – Free Software

Clubs have always wanted a way to maximise a teams preparation, while at the same time reducing the risk of Soft-Tissue injuries during the coming week.

Rugby players can monitor the risk of soft-tissue injury that they may be exposing themselves to during the coming week, either as a result of the squads training, or as a result of their own individualised training program.

Although this software is based on our very effective artificial intelligence software, it has been greatly simplified compared to our bespoke systems, and makes no assumptions about the availability of historical data, technical or support staff. This is an entry level solution, for those clubs or individual athletes wishing to explore this technology, but who would not have the willingness or resources to consider a more customised approach. And it is absolutely FREE of charge.

The software (called the Predictor), has been designed to analyse the predicted risk of soft-tissue injury in the coming week, for one or more athletes.

The system, which utilises an Excel spreadsheet for input and output purposes, requires a minimal amount of information such as:

Your planned training session durations and associated RPEs (Relative Perceived Exertion – 0 to 10)

Last weeks Load result, which was calculated by the spreadsheet

Several Muscle Soreness and Well-being ratings at the start of the week

Once this weeks planned session times and anticipated RPE’s, last weeks total Load, and current Muscle Soreness and Well-being ratings have been entered, the Injury Predictor based on an artificial neural network, will produce a predicted risk of injury, for each individual during the coming week.

This Entry Level Injury Predictor for Rugby / Rugby League requires a Microsoft Windows environment, together with Microsoft Excel. In the event that you are an Apple Mac owner (as I am), then you will need to run your Microsoft Windows & Excel environment on your Mac using Apple’s Bootcamp utility, or a third party virtual machine environment such as Parallels.

Canterbury Bulldogs Takes On Predictive Modeling Technology

The Belmore based Canterbury Bulldogs – 2012 Premiership runner-up, have contacted us to apply our soft-tissue Injury Prediction technology, in the 2013 NRL season.

Having been supplied with GPS and well-being training data for the 2012 pre-season and in-season, we were able to produce soft-tissue Injury Prediction models for the coming 2013 season, together with their related Optimisers. The initial test results were extremely encouraging.

While Rugby conditioning and medical staff always point out that many injuries are the result of physical contact during games, they do recognise that the effective management of soft-tissue injuries would be enormously beneficial.

Daily Soft-Tissue Injury Prediction

We have just completed development of Liverpool Football Club’s injury prediction neural network for the 2012/2013 season.

What makes this model different from ones we’ve done previously for our clients, is that this model has a time frame of one day.

Many clients operate a “one week” projected time frame for their injury analysis and predictions, but in this particular case we have developed a “one day” projected time frame.

To achieve this required a very considerable amount of pre-processing of the raw data, so that it could be used to “train” the network.

The test results were exceptional !

Injury Prediction & Management In A “Box” For Amateur Rugby Players

Amateur Rugby clubs have always wanted a way to maximise a teams preparation, while at the same time reducing the risk of Soft-Tissue injuries during the coming week.

What may be a world first, individual Rugby players of all ages and experience, who as enthusiastic amateurs, can monitor the risk of soft-tissue injury that they may be exposing themselves to during the coming week, either as a result of the squads training, or as a result of their own individualised training program.

Although this product is based on our very effective artificial intelligence software, it has been greatly simplified compared to our bespoke systems, and makes no assumptions about the availability of historical data, technical or support staff. This is a low cost of entry solution, for those amateur clubs or enthusiastic individual athletes wishing to explore this technology, but who would not have the willingness or resources to consider a more customised approach.

The software (called the Predictor), has been designed to analyse the predicted risk of soft-tissue injury one week in advance, for one or more athletes.

The system, which utilises an Excel spreadsheet for input and output purposes, requires a minimal amount of information such as:

Your planned training session durations and associated RPEs (Relative Perceived Exertion – 0 to 10)

Last weeks Load result, which was calculated by the spreadsheet

Several Muscle Soreness and Well-being ratings at the start of the week

Once this weeks planned session times and anticipated RPE’s, last weeks total Load, and current Muscle Soreness and Well-being ratings have been entered, the Injury Predictor neural network, will produce a predicted risk of injury, for each individual during the coming week.

Being aware of the risk is an important piece of information, but the question still remains as to what can be done to reduce that risk. That is a job for the Optimiser.

The Amateur Rugby Injury Optimiser (or Optimiser) product, uses a unique search algorithm to find an “optimal” training scenario so as to minimise the risk of injury to an athlete. This “optimal” scenario is subject to constraints stipulated by the user.

The Optimiser compliments the Amateur Rugby Injury Predictor (or Predictor) product, by working in partnership with it to evaluate different possible training scenarios.

Once the Predictor highlights an unacceptable risk of injury, it is possible to explore how that risk might be reduced to an acceptable level, without the use of the Optimiser by manually re-running the Predictor repeatedly, with the user changing inputs manually and re-examining the results, it may be possible to eventually reach an acceptable level of injury risk. The only disadvantage to this approach is the time it might take to do this (with hundreds or more possible scenarios), and the uncertainty of not knowing whether the risk achieved was at its lowest level possible.

If the Predictor indicates that a player is at risk, those inputs relating to that player can be copied from the Predictor into the Optimiser.

The user simply enters the upper and lower ranges for those factors which could be modified – in this case the expected session loads. The Optimiser then, in conjunction with the Predictor neural network, intelligently assesses hundreds if not thousands of possible scenarios, till the lowest possible risk of injury is determined, within the stated upper and lower load ranges.

The Optimiser displays the “adjusted loads” required to achieve this lower level of injury risk.

Both the Amateur Rugby Injury Predictor and Optimiser require Microsoft Excel and Microsoft Windows, and in the case of the Optimiser, also requires the prior installation of the Amateur Rugby Injury Predictor.

Injury Prediction & Management In A “Box” For Professional Rugby

As a rule our predictive models are custom built to match the specific requirements of a club and it’s staff. Unfortunately not every club has the resources – financial, staff or data – that will enable such an endeavor to be undertaken.

To help clubs take advantage of this technology, we have created a “boxed” version of our technology, allowing Coaching, Medical, and Strength & Conditioning staff at Rugby clubs who have always wanted a way to maximise a teams preparation, while at the same time reducing the risk of Soft-Tissue injuries during the coming week.

This product is also applicable to individual Rugby players, who as professional athletes, may wish to monitor the risk of soft-tissue injury they may be exposing themselves to, either as part of the squads training, or as a result of their own individualised training program.

Although this product is based on our very effective artificial intelligence software, it has been greatly simplified compared to our bespoke systems, and makes no assumptions about the availability of historical data, technical or support staff. This is a low cost of entry solution, for those clubs or individuals wishing to explore this technology, but who may not have the willingness or resources to consider a more customised approach.

In fact there are two parts (or perhaps I should say packages) to this story – a Predictor and an Optimiser.

The predictor software can analyse the risk of soft-tissue injury up to a week in advance, for one or more athletes.

The system, which utilises an Excel spreadsheet as a front-end for input and output purposes, requires a minimal amount of information such as your planned training session durations and associated RPEs (Relative Perceived Exertion – 0 to 10),last weeks Load, Monotony and Strain results, which were calculated by the spreadsheet,

and finally several Muscle Soreness and Well-being ratings taken at the start of the week

Once this weeks planned session times and anticipated RPE’s, last weeks total Load / Monotony / Strain, and current Muscle Soreness and Well-being ratings have been entered, the Injury Predictor neural network will, based on it’s training, produce a risk assessment for each individual for the coming week.

The second part of this story is the Optimiser.

The Rugby Injury Optimiser (or Optimiser) product, uses a unique search algorithm to find an “optimal” training scenario so as to minimise the risk of injury to an athlete. This “optimal” scenario is subject to constraints which can be stipulated by the user.

The Optimiser compliments the Rugby Injury Predictor (or Predictor) product, by working in partnership with it to evaluate different possible training scenarios.

Once the Predictor highlights an unacceptable risk of injury, it is possible to explore how that risk might be reduced to an acceptable level, by manually re-running the Predictor repeatedly, with the user changing inputs manually and re-examining the results. It may be possible to eventually reach an acceptable level of injury risk in this manner. The only disadvantage to this approach is the time it might take to do this (with hundreds or more possible scenarios), and the uncertainty of not knowing whether the risk achieved was at its lowest level. This is why we developed the Optimiser.

If the Predictor indicates that a player is at risk, those inputs relating to that player can be copied from the Injury Predictor into the Optimiser.

The Optimiser displays the “adjusted loads” required to achieve this outcome.

Both the Rugby Injury Predictor and Optimiser require Microsoft Excel and Microsoft Windows, and in the case of the Optimiser, also requires the prior installation of the Rugby Injury Predictor.

Melbourne Heart Investigates AI Technology

Today the Melbourne Heart soccer club, based at LaTrobe university in Melbourne, has signed an agreement to assist them with soft-tissue injury identification services.

In the coming year we will develop several injury prediction models, utilising neural networks, to aid the strength and conditioning staff with player preparation.

Liverpool Football Club Takes Neural Networks Seriously

The word is spreading far and wide about the power of our Injury and Performance prediction networks.

We are pleased to announce that our first football club (soccer to us Australians), is the UK based Liverpool Football Club.

Because of the highly competitive nature of the English Premier League (EPL) we can’t disclose any details other than to say that these Injury and Performance networks are probably the most sophisticated to-date, with nearly 40 factors being considered when predictions are made.

Pre-Season Neural Networks Deliver!

It’s December 2008, and pre-season preparation is already under way for our AFL clients.

The same is true for us, as we finalise the development of predictive pre-season neural networks for them, reflecting their unique playing lists and training styles.

Built using historical pre-season data, the target for these networks is the risk of soft-tissue injury and player performance in the early matches of the in-season.

By training the networks on historical data such as a players years of experience, the number of training sessions, practice matches and game time, as well as the spread of On-Legs and Off-Legs loads under various training and practice match conditions, the networks achieved a prediction accuracy greater than 80%.

Through the use of sensitivity testing we can get an indication of the ranges where some of the planned activities should fall.

Rugby League Sees The Potential For Soft-Tissue Injury Prediction

The Queensland based Brisbane Broncos have contacted us to explore our Injury Prediction technology, and its applicability to Rugby League.

Having been supplied with training data spanning 3 seasons, we were able to produce an Injury Prediction model, and related Optimiser suitable for Rugby League. The initial test results were extremely encouraging.

Carlton and Brisbane Lions AFL Clubs Sign Up for Service

It has been a hectic early 2008 with the signing up of the Carlton and Brisbane Lions AFL clubs.

Both clubs have shown great interest in the benefits that our predictive injury and performance modelling services can offer.

Neural networks will be developed for both the pre-season and in-season periods, and will initially focus on soft-tissue injury risk assessment, followed by player performance ratings.

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