[Feature Request]: UEFA-compliance / autotype compliance

[abhiamishra]

Suggest an idea or something that can be improved.

Currently, our functions are compliant to StatsBomb and Opta. UEFA-styled coordinates do exist today, new news for me, and it would be a nice thing to have that implemented.

A nicer thing would if we were able to understand the type of the dataframe automatically,,,,, food for thought!

[harshkrishna17]

auto-identify dataset type is an interesting idea, but we should probably fix the bugs for the current version and do a CRAN release so that we're free to experiment with the idea on dev

[harshkrishna17]

For now, we could just add a way to transform UEFA data to opta within the guide itself?

[abhiamishra]

Either that or we add UEFA as a data type to all functions

[abhiamishra]

Or we create a helper function that transforms datasets from UEFA to one of Opta/StatsBomb

[harshkrishna17]

Would {ggsoccer} have this functionality? It has a pitch type pitch_international for UEFA coordinates but not sure if its there for the rescale function.

[harshkrishna17]

Here's a simple internal function we could create to auto identify the dataset type. We can add in the final coordinate value specifications as well. @abhiamishra @Ryo-N7

data_type_identify <- function(data) {
  
  if (max(data$x) > 98 & max(data$x) < 102 &
      max(data$y) > 98 & max(data$y) < 102) {
    print("opta")
  } else 
  
  if (max(data$x) > 118 & max(data$x) < 122 &
      max(data$y) > 78 & max(data$y) < 82) {
    print("statsbomb")
  }
  
}

[harshkrishna17]

Updated function

data_type_identify <- function(data) {
  
  data <- data %>%
    select(x, y, finalX, finalY) %>%
    na.omit()
  
  if (max(data$x) > 98 & max(data$x) < 102 &
      max(data$y) > 98 & max(data$y) < 102 &
      max(data$finalX) > 98 & max(data$finalX) < 102 &
      max(data$finalY) > 98 & max(data$finalY) < 102) {
    data_type <- "opta"
  } 
  else 
    
    if (max(data$x) > 118 & max(data$x) < 122 &
        max(data$y) > 78 & max(data$y) < 82 &
        max(data$finalX) > 118 & max(data$finalX) < 122 &
        max(data$finalY) > 78 & max(data$finalY) < 82) {
      data_type <- "statsbomb"
    } 
  else
    
    if (max(data$x) > 103 & max(data$x) < 107 &
        max(data$y) > 66 & max(data$y) < 70 &
        max(data$finalX) > 103 & max(data$finalX) < 107 &
        max(data$finalY) > 66 & max(data$finalY) < 70) {
      data_type <- "international"
    }
  
  return(data_type)
  
}

[rithwikrajendran]

Suggest an idea or something that can be improved.

Currently, our functions are compliant to StatsBomb and Opta. UEFA-styled coordinates do exist today, new news for me, and it would be a nice thing to have that implemented.

A nicer thing would if we were able to understand the type of the dataframe automatically,,,,, food for thought!

Can't we use the uniqueness in the column names of each data frame type to find out the type of data (UEFA, Opta, SB etc) and then return the pitch accordingly?

[harshkrishna17]

Suggest an idea or something that can be improved.

Currently, our functions are compliant to StatsBomb and Opta. UEFA-styled coordinates do exist today, new news for me, and it would be a nice thing to have that implemented.
A nicer thing would if we were able to understand the type of the dataframe automatically,,,,, food for thought!

Can't we use the uniqueness in the column names of each data frame type to find out the type of data (UEFA, Opta, SB etc) and then return the pitch accordingly?

That cant work unfortunately as we already require the dataset to be inputted into the functions with specific column names

[robbiejdunne]

I don't fully understand why the passplot functions scales them fine but the pass networks don't scale properly. The prog passes one was done with the same dataset as the pass network.

[harshkrishna17]

Hey @robbiejdunne could you please be a little more specific? As in what is the problem with scaling. I would also recommend you to create a new issue for this problem, and continue the conversation there

[robbiejdunne]

This is part of the original issue with international/opta/statsbomb data. The pass network's dimensions only go as high as 68 in this dataset. But they seem to be just fine for the progressive passes. Does that make sense?

[harshkrishna17]

I dont think they're fine for the progressive passes, rather the size of the pitch in plot_pass is making it appear right when it might not be.

Try running this on your dataset before running the passnet function.

data <- data %>%
  mutate(x = x * 105/100,
         finalX = finalX * 105/100,
         y = y * 68/100,
         finalY = finalY * 68/100)

This should make it work

[abhiamishra]

I'm going to play around with the function Harsh made