Review detailed data download

2022_08.js

let get_all_data = () => {
    
    let gws = Array.from(jQuery(".ptsshoq")).map(i => i.textContent).filter(i => i.includes('GW')).map(i => parseInt(i.split('GW')[1]))
    let first_week = Math.min(...gws)
    let last_week = Math.max(...gws)

    let jsondata= jQuery("#fplr_api").text()
    let d=JSON.parse(decodeURIComponent(escape(window.atob(jsondata))))

    let main_keys = ['name', 'pos', 'team_abbrev', 'now_cost']
    let gw_keys = ['opp', 'dmins', 'livpts', 'livxg', 'livxa', 'livcs', 'livbon']
    let text_data = "ID,Name,Pos,Team,Price"
    for (let w=first_week; w<=last_week; w++) {
        text_data += `,${w}_fix,${w}_xmins,${w}_pts,${w}_g,${w}_a,${w}_cs,${w}_bon`
    }
    let players = Object.entries(d)
    players = players.filter(i => i[1] != 0)
    players.forEach(e => {
        let pid = e[0]
        let p = e[1]
        row_data = pid + "," + main_keys.map(i => p[i]).join(",")
        for (let w=first_week; w<=last_week; w++) {
            gw_keys.forEach(k => {
                try {
                    row_data += ',' + p[w][k]
                }
                catch {
                    aa = 1
                }
                
            })
        }
        text_data += '\n'+row_data
    })

    return text_data

}

function download_csv_data(csv, filename) {
        var csvFile;
        var downloadLink;
        csvFile = new Blob([csv], {type: "text/csv"});
        downloadLink = document.createElement("a");
        downloadLink.download = filename;
        downloadLink.href = window.URL.createObjectURL(csvFile);
        downloadLink.style.display = "none";
        document.body.appendChild(downloadLink);
        downloadLink.click();
    }

text_data = get_all_data()
download_csv_data(text_data, "review_detailed.csv")

2023_01.js

let get_all_data = () => {
    
    let gws = Array.from(jQuery(".ptsshoq")).map(i => i.textContent).filter(i => i.includes('GW')).map(i => parseInt(i.split('GW')[1]))
    let first_week = Math.min(...gws)
    let last_week = Math.max(...gws)

    let jsondata= jQuery("#fplr_api").text()
    let d=JSON.parse(decodeURIComponent(escape(window.atob(jsondata))))

    let main_keys = ['name', 'pos', 'team_abbrev', 'now_cost']
    let gw_keys = ['opp', 'dmins', 'livpts', 'livxg', 'livxa', 'livcs', 'livbon']
    let text_data = "ID,Name,Pos,Team,Price"
    for (let w=first_week; w<=last_week; w++) {
        text_data += `,${w}_fix,${w}_xmins,${w}_pts,${w}_g,${w}_a,${w}_cs,${w}_bon,${w}_dmins,${w}_likelihood`
    }
    let players = Object.entries(d)
    players = players.filter(i => i[1] != 0)
    players.forEach(e => {
        let pid = e[0]
        let p = e[1]
        row_data = pid + "," + main_keys.map(i => p[i]).join(",")
        for (let w=first_week; w<=last_week; w++) {
            gw_keys.forEach(k => {
                try {
                    row_data += ',' + p[w][k]
                }
                catch {
                    aa = 1
                }
            })
            row_data += p[w].matchos ? ','+p[w].matchos.map(i => p[w][i].dmins).join(' ') : ','
            row_data += p[w].matchos ? ','+p[w].matchos.map(i => p[w][i].likelihood).join(' ') : ','
        }
        text_data += '\n'+row_data
    })

    return text_data

}

function download_csv_data(csv, filename) {
        var csvFile;
        var downloadLink;
        csvFile = new Blob([csv], {type: "text/csv"});
        downloadLink = document.createElement("a");
        downloadLink.download = filename;
        downloadLink.href = window.URL.createObjectURL(csvFile);
        downloadLink.style.display = "none";
        document.body.appendChild(downloadLink);
        downloadLink.click();
    }

text_data = get_all_data()
download_csv_data(text_data, "review_detailed.csv")

NEW.js

let get_all_data = () => {
    let gw_m = jQuery("*[data-gwid]")
    let first_week = Math.min(...Array.from(gw_m).map(i => parseInt(i.dataset.gwid)))
    let last_week = Math.max(...Array.from(gw_m).map(i => parseInt(i.dataset.gwid)))

    let d = JSON.parse(jQuery("#fplr_api").html())
    let main_keys = ['name', 'pos', 'team_abbrev', 'now_cost']
    let gw_keys = ['opp', 'dmins', 'livpts', 'livxg', 'livxa', 'livcs', 'livbon']
    let text_data = "ID,Name,Pos,Team,Price"
    for (let w=first_week; w<=last_week; w++) {
        text_data += `,${w}_fix,${w}_xmins,${w}_pts,${w}_g,${w}_a,${w}_cs,${w}_bon`
    }
    let players = Object.entries(d)
    players = players.filter(i => i[1] != 0)
    players.forEach(e => {
        let pid = e[0]
        let p = e[1]
        row_data = pid + "," + main_keys.map(i => p[i]).join(",")
        for (let w=first_week; w<=last_week; w++) {
            gw_keys.forEach(k => {
                row_data += ',' + p[w][k]
            })
        }
        text_data += '\n'+row_data
    })

    function download_csv_data(csv, filename) {
        var csvFile;
        var downloadLink;
        csvFile = new Blob([csv], {type: "text/csv"});
        downloadLink = document.createElement("a");
        downloadLink.download = filename;
        downloadLink.href = window.URL.createObjectURL(csvFile);
        downloadLink.style.display = "none";
        document.body.appendChild(downloadLink);
        downloadLink.click();
    }
    download_csv_data(text_data, "review_detailed.csv")

    console.log(text_data)

}
get_all_data()

OLD.js

function get_data() {
    let text_data = 'Name,ID,'
    let gw_names = Array.from(jQuery('#scout_table *[data-gwid]')).map(i => i.innerText)
    text_data += gw_names.map(i => [i+"_xp", i+"_fix", i+"_g", i+"_a", i+"_cs", i+"_bon"]).flat()
    let rows = jQuery("#scout_table tbody tr")
    let data = Array.from(rows).map(e => {
        
        let row = jQuery(e)
        let player = row.find(".fancyname")
        let name = player.text()
        let player_id = player.data()['id']
        let cols = row.find(".multTotal.squad")
        let row_data = name + "," + player_id
        let pdata = Array.from(cols).map((col, order) => {
            let gw_tag = gw_names[order]
            let c = col.textContent.match(/([0-9\.]*)(\([HA]\): [A-Z]{3})G: ([0-9\.]*)A: ([0-9\.]*)CS: ([0-9\.]*)Bon: ([0-9\.]*)/)
            let d = {}
            let last = 0
            last = d[gw_tag + '_xp'] = parseFloat(c[1])
            row_data += "," + last
            last = d[gw_tag + '_fix'] = c[2]
            row_data += "," + last
            last = d[gw_tag + '_g'] = parseFloat(c[3])
            row_data += "," + last
            last = d[gw_tag + '_a'] = parseFloat(c[4])
            row_data += "," + last
            last = d[gw_tag + '_cs'] = parseFloat(c[5])
            row_data += "," + last
            last = d[gw_tag + '_bon'] = parseFloat(c[6])
            row_data += "," + last
            return d
        })
        text_data += "\n" + row_data
        return {name, player_id, pdata}
    })
    console.log(data)
    console.log(text_data)
    
    function download_csv_data(csv, filename) {
        var csvFile;
        var downloadLink;
        csvFile = new Blob([csv], {type: "text/csv"});
        downloadLink = document.createElement("a");
        downloadLink.download = filename;
        downloadLink.href = window.URL.createObjectURL(csvFile);
        downloadLink.style.display = "none";
        document.body.appendChild(downloadLink);
        downloadLink.click();
    }
    download_csv_data(text_data, "review_detailed.csv")
    
    return data
    }
get_data()