Hi David (and FoT), Seen this only on Saturday so did a (very) brief evaluation of Trent Alexander-Arnold and the types of goals he contributes to using the tools and data you provided. Out of all 19 goals you provided, 8 were assists by Trent and 90% of these were across the floor (from watching them all). Turns out the type of play he was involved with was very similar across your sample. In these few slides (and two tiny videos) I briefly evaluate these types of goals using tracking data to validate what opposition players may notice on the pitch, using techniques showed on this RUclips channel. And as a result what defenders on opposition sides could do to increase their chance of not conceding. Link to PDF slides: drive.google.com/open?id=1Dx_8I3FuKT_23sOzywOPSI6Dk3Jqjc7t [Video links are on associated slides] Thank you for this incredible resource and I look forward to learning more in time, Adam Ruby
Here is my contribution to the challenge : medium.com/@gabs.rol43/analysing-liverpool-attack-e6d32c6c9a57#6461. Analysing Liverpool attack was a real pleasure for me as I'm a Liverpool fan. I would very much appreciate hearing your views on this study. Thanks a lot for the opportunity and all your tutorials.
In case my tweet goes unseen, here is my submission to the challenge: medium.com/@hugoriosneto/would-better-goalkeeper-positioning-have-prevented-liverpool-from-scoring-caab43e23972
![I.N "HALLUCINATION" | [Stray Kids : SKZ-PLAYER]](http://i.ytimg.com/vi/n5B5q1Hwt_U/mqdefault.jpg)
Thanks to all involved in Friends of Tracking!
Hi David (and FoT),
Seen this only on Saturday so did a (very) brief evaluation of Trent Alexander-Arnold and the types of goals he contributes to using the tools and data you provided.
Out of all 19 goals you provided, 8 were assists by Trent and 90% of these were across the floor (from watching them all). Turns out the type of play he was involved with was very similar across your sample.
In these few slides (and two tiny videos) I briefly evaluate these types of goals using tracking data to validate what opposition players may notice on the pitch, using techniques showed on this RUclips channel. And as a result what defenders on opposition sides could do to increase their chance of not conceding.
Link to PDF slides: drive.google.com/open?id=1Dx_8I3FuKT_23sOzywOPSI6Dk3Jqjc7t
[Video links are on associated slides]
Thank you for this incredible resource and I look forward to learning more in time,
Adam Ruby
just saw it ..
Great work!
Keep it up & continue to learn.
Here is my contribution to the challenge : medium.com/@gabs.rol43/analysing-liverpool-attack-e6d32c6c9a57#6461.
Analysing Liverpool attack was a real pleasure for me as I'm a Liverpool fan.
I would very much appreciate hearing your views on this study.
Thanks a lot for the opportunity and all your tutorials.
In case my tweet goes unseen, here is my submission to the challenge:
medium.com/@hugoriosneto/would-better-goalkeeper-positioning-have-prevented-liverpool-from-scoring-caab43e23972
hey can you post links to the datasets you use?