DataViz challenge for the sports analytics community - aiming to improve visual creativity and standards across the community via healthy competition #OpenToAll
@deepxg@ProformAFC That's a great suggestion... thanks
I was also hoping to identify generic 'clusters' of situations which would help with finding matching positional setups but also see frequency/style of a team
Close of the day progress...
1. Happy with how it is matching
2. Video Analyst enters time of situation he wants to find more of
3. Run script
4. Exported to XML is working into SportsCode
5. Double click the row and watch all the clips
#rstats#analytics
example below
@andrewjwant Yeah, this is the area where I would love to improve it. I simply don't know if there are better alternatives to cor(). I am very happy with the eyeball test of it after the last 20 minutes improvements
@andrewjwant Once tracking data is loaded.. It currently takes less than 60 seconds to complete everything including matrix comparisons for positions of team1 and team2 at second intervals
@PenaltyKickStat exactly... I am looking at the automation of match preparation processes to start with. So.. for opposition 'x' I have noticed something good .. pattern 'y' ... enter the time code.. hit run and then all occurrences are timecoded.
@PenaltyKickStat I am a novice! think of an idea and then magpie, google answers and eventually work it out :)
Yep, number = amount of players in that bucket.. indeed just for one team. I have it working for both teams and checking the correlation but not happy with the matching for 2 teams
A few bugs cleared..
It's matching pretty well and works as a tool... I need to work out export to xml to import to SportsCode which I have done before so shouldn't be an issue
Top left is the situation that was searched others are the matched results
Feedback?
#rstats
Updated the GitHub -> https://t.co/GDVNtHWhLm
I have the positional matrices for each second of the game.. I can enter a frame and get the closest matching second in the game - see pic.
I am using cor() in R for this... any suggestions of better ways? #rstats