Christian Saal (@saalcs) 's Twitter Profile
Christian Saal

@saalcs

ID: 2863118026

calendar_today05-11-2014 19:32:34

475 Tweet

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Jason Avedesian, PhD (@jasonavedesian) 's Twitter Profile Photo

It's likely you're looking at too many GPS metrics to quantify external demands. 96% of the variance in Total Player Load is explained by total distance! Data from ~1700 data points in WSOC.

It's likely you're looking at too many GPS metrics to quantify external demands.

96% of the variance in Total Player Load is explained by total distance!

Data from ~1700 data points in WSOC.
Christian Saal (@saalcs) 's Twitter Profile Photo

Tracking devices and physical performance analysis in team sports: a comprehensive framework for research—trends and future directions frontiersin.org/articles/10.33… no handball 🤾‍♂️?? Is it due to the combination of internal and external load?

Maarten van Smeden (@maartenvsmeden) 's Twitter Profile Photo

Do not understand why not every PI is hiring a statistician. There is a wealth of data showing that statisticians are very effective in making research slower, more difficult to understand for non-statisticians, analyses more expensive, results less impressive and more boring

Paul Glazier (@paulglazier) 's Twitter Profile Photo

Where’s the value in ‘expertise research’ (i.e., expert-novice differences)? These types of ‘on average’ findings are, on the one hand, intuitively obvious but, on the other hand, potentially misleading because they lack nuance and ignore inter-individual variability.

Where’s the value in ‘expertise research’ (i.e., expert-novice differences)? These types of ‘on average’ findings are, on the one hand, intuitively obvious but, on the other hand, potentially misleading because they lack nuance and ignore inter-individual variability.
Rob Donnelly (@robdonnelly47) 's Twitter Profile Photo

Friends don't let friends make bad charts! Chenxin Li, pulled together a lot of great advice for data visualization, with clear "do this, not that" examples for each item. Here are a few of my favorites, see the link below for more.

Friends don't let friends make bad charts!

Chenxin Li, pulled together a lot of great advice for data visualization, with clear "do this, not that" examples for each item. 

Here are a few of my favorites, see the link below for more.
The Nobel Prize (@nobelprize) 's Twitter Profile Photo

Happy International Women's Day! We're celebrating women who have changed the world. Here's all of the amazing women who have received the #NobelPrize and their remarkable achievements at the time of the award. Who are the women who inspire you the most? #IWD2024

Don Williams (@don_k_williams) 's Twitter Profile Photo

The Line The line represents respect. Respect for yourself Respect for your teammates Respect for your coaches Respect for the process

Christian Saal (@saalcs) 's Twitter Profile Photo

Physiological and Locomotor Profiling Enables to... : The Journal of Strength & Conditioning Research journals.lww.com/nsca-jscr/abst… This is obvious, but I would always be more careful with generalizations with a sample size of 11 per group.

Christian Saal (@saalcs) 's Twitter Profile Photo

Universität Leipzig: Zwei Metabolische Kammern für die Forschung Wow — das klingt nach einem coolen Messsystem und könnte eine Spiro ersetzen… uni-leipzig.de/newsdetail/art…

Christian Saal (@saalcs) 's Twitter Profile Photo

Autonomous calibration of blood pressure dependent data using second-order blood pressure variation for a future mobile diagnostic: Requirements for a calibration | IEEE Journals & Magazine | IEEE Xplore Very interesting.. ieeexplore.ieee.org/document/10595…