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Predicting non-contact hamstring injuries by using training load data and machine learning models
By Mladen Jovanovic on 17/12/2018Research has shown that there is an association between training load and likelihood of suffering non-contact injuries. But can we predict the injury? In this paper I have tried to predict non-contact hamstring injury by using two seasons day-to-day training load data.
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Data Preparation for Injury Prediction
By Mladen Jovanovic on 23/08/2018I have recently wrote a technical note (actually a video) for Sport Performance and Science Reports journal regarding Data Preparation for Injury Prediction. Both data and R core are available on GitHub repository.
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Three Different Aspects of Training Load Monitoring
By Mladen Jovanovic on 21/06/2018In 2014 I wrote Training Load Monitoring – Seeing the Big Picture where I have outlined a simple model for training load monitoring. In this video, I am expanding that model as well as modifying it to depict my current thought process regarding the topic.
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Fantastic Sport Analytics Papers & Resources
By Mladen Jovanovic on 03/03/2018I have recently stumbled on a few great papers that outline very useful statistical techniques, that are VERY applicable to sport and training analytics. If you are interested in analytics, this is a gold mine.
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How to Analyze Training Load and Monitoring Data?
By Mladen Jovanovic on 21/11/2017In this video I am explaining two methods to deal with missing values and why you should pay attention to the way you are aggregating data (daily, team averages, body soreness, etc).
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Latest on Load Monitoring [Video & FREE Templates]
By Sean Williams on 28/09/2017Sean Williams was kind enough to provide short review of the recent load monitoring workshop, held at the World Rugby Science Network Conference, as well as to provide full slides and Excel templates. This is tremendous resource for those interested in injury prediction analytics.
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To Turf or Not to Turf, That is the Question [Part 2]: Applications
By Mladen Jovanovic on 26/07/2017In this video I am deploying the model to make the decision between 5 variations of weekly plan. The goal is to minimize the morning soreness on the day of the game.
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To Turf or Not to Turf, That is the Question [Part 1]
By Mladen Jovanovic on 05/07/2017In this video I am presenting my “solution” to the problem and provide fake data set, as well as R code for analyzing the data. Having decent predictive model can help us run different optimization algorithms to find the “best” scheduling to minimize/maximize injury risk or performance.
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William Sands on Athlete Monitoring
By Mladen Jovanovic on 17/03/2017Athlete preparation and performance continues to increase in complexity and costs. Modern coaches are shifting from reliance on personal memory, experience, and opinion to evidence from collected training load data. Training load monitoring may hold vital information for developing systems of monitoring that follow the training process with such precision that both performance prediction and day-to-day management of training...
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Uncertainty, Heuristics and Injury Prediction
By Mladen Jovanovic on 07/03/2017I was asked by Rod Whiteley and Nicol van Dyk to contribute to the Aspetar Journal targeted topic issue that just got released off the press. I tried to combine my knowledge of predictive analytics, machine learning, philosophy of science, heuristics and practical experience as coach & sport scientist into one article. Hopefully I managed to create readable narrative.
