The win exchange rate

All wins are not created equal. When we say Kevin Love is worth $45 million and Kobe Bryant is “only” worth $20 million, we leave out the fact that wins are worth more in Los Angeles than Minnesota. This didn’t sit well with Arturo, our Director of Analytics. He decided to break down the difference in the value of a win for each market. It turns out that not all markets are created equal. For example here’s LeBron James’ value across markets.


[js]
google.load(‘visualization’, ‘1’, {packages: \[‘table’\]});
[/js]
[js]
var data = new google.visualization.DataTable();
data.addColumn(‘string’, ‘City’);
data.addColumn(‘number’, ‘Value’);
data.addRows(5);
data.setCell(0, 0, ‘Los Angeles Lakers’);
data.setCell(1, 0, ‘Miami                 Heat’);
data.setCell(2, 0, ‘Cleveland Cavaliers’);
data.setCell(3, 0, ‘Golden State Warriors’);
data.setCell(4, 0, ‘Indiana Pacers’);
data.setCell(0, 1, 72.4, ‘$72,404,609’);
data.setCell(1, 1, 67.8, ‘$60,543,003’);
data.setCell(2, 1, 45.7, ‘$45,743,660’);
data.setCell(3, 1, 44.2, ‘$44,155,338’);
data.setCell(4, 1, 35.4, ‘$35,444,569’);
var chartDiv = document.getElementById(‘lebron_chart’);
var options = {title: ‘LeBron James\’ Value by City’};
chart = new PilesOfMoney(chartDiv);
chart.draw(data, options);
[/js]

What’s the value of a win?

Arturo did an estimate of each team’s net operating income. This is basically how much money the team brings in (from ticket sales, TV deals and main revenue streams) minus the cost of the players salaries. Using this number as a baseline Arturo estimated how much a win was in each market and there were some pretty big differences.


[js]
var win_data = new google.visualization.DataTable();
win_data.addColumn(‘string’, ‘Team’);
win_data.addColumn(‘number’, ‘NOI’);
win_data.addColumn(‘number’, ‘Salaries’);
win_data.addColumn(‘number’, ‘Win Value’);
win_data.addColumn(‘number’, ‘Wins Purchased’);
win_data.addColumn(‘number’, ‘Wins Produced’);
win_data.addRows(\[
\[‘Los Angeles Lakers’, 234.8, 90.4, 3.37, 26.8, 57.5\],
\[‘New York Knicks’, 216, 67.1, 3.1, 21.6, 42.8\],
\[‘Miami Heat’, 186.7, 66.7, 2.68, 24.9, 61.1\],
\[‘Boston Celtics’, 178.2, 76.2, 2.56, 29.8, 55\],
\[‘Chicago Bulls’, 170.5, 55.6, 2.45, 22.8, 60.5\],
\[‘Toronto Raptors’, 151.4, 69.1, 2.17, 31.8, 23.8\],
\[‘Dallas Mavericks’, 137.6, 86.6, 1.97, 43.9, 51.9\],
\[‘Phoenix Suns’, 135.4, 66.2, 1.94, 34.1, 38.9\],
\[‘San Antonio Spurs’, 134.8, 69.7, 1.93, 36.1, 56.2\],
\[‘Los Angeles Clippers’, 133.7, 52.7, 1.92, 27.5, 32.6\],
\[‘Portland Trailblazers’, 130.4, 73.7, 1.87, 39.4, 44.9\],
\[‘Houston Rockets’, 128.7, 70.9, 1.85, 38.4, 46.9\],
\[‘Cleveland Cavaliers’, 126.7, 55.1, 1.82, 30.3, 16.9\],
\[‘Orlando Magic’, 124.4, 89.9, 1.78, 50.4, 55.7\],
\[‘Golden State Warriors’, 120.2, 68.3, 1.72, 39.6, 34.1\],
\[‘Oklahoma City Thunder’, 115.4, 58.1, 1.65, 35.1, 51.8\],
\[‘Denver Nuggets’, 112.2, 67.1, 1.61, 41.7, 53.8\],
\[‘Philadelphia 76ers’, 107.9, 68.5, 1.55, 44.3, 44.9\],
\[‘Atlanta Hawks’, 106.2, 70.2, 1.52, 46.1, 38.4\],
\[‘Sacramento Kings’, 105.5, 44.9, 1.51, 29.7, 26.6\],
\[‘Washington Wizards’, 104.5, 57.2, 1.5, 38.2, 21.6\],
\[‘Utah Jazz’, 103.7, 75.3, 1.49, 50.6, 35.9\],
\[‘Milwaukee Bucks’, 102, 68.9, 1.46, 47.1, 38.5\],
\[‘Memphis Grizzlies’, 98.1, 69.7, 1.41, 49.6, 47.3\],
\[‘Detroit Pistons’, 97.7, 65, 1.4, 46.4, 31.3\],
\[‘Charlotte Bobcats’, 96, 65.6, 1.38, 47.7, 30.2\],
\[‘New Orleans Hornets’, 94.3, 68.3, 1.35, 50.5, 43.3\],
\[‘New Jersey Nets’, 91.6, 58.9, 1.31, 44.9, 24.4\],
\[‘Minnesota Timberwolves’, 87.7, 54.2, 1.26, 43.1, 22.8\],
\[‘Indiana Pacers’, 84.9, 65.1, 1.22, 53.5, 37.8\]
\]);
var win_table = new google.visualization.Table(document.getElementById(‘win_value_table’));
// Bar Format of Wins Purchased column to green/red bar
var wp_purchased_formatter = new google.visualization.NumberFormat({fractionDigits:1});
wp_purchased_formatter.format(win_data,4);

// Bar Format of Wins Produced Column to green/red bar
var wp_formatter = new google.visualization.NumberFormat({fractionDigits:1});
wp_purchased_formatter.format(win_data,5);

// Currency Formatter for NOI and Salaries
var currency_formatter = new google.visualization.NumberFormat({prefix: ‘$’, fractionDigits: 1});
currency_formatter.format(win_data, 1);
currency_formatter.format(win_data,2);

// Currency Formatter for Value of Win
var value_converter = new google.visualization.NumberFormat({prefix: ‘$’, fractionDigits: 2});
value_converter.format(win_data, 3);

// And draw the table, the allowHTML is huge as the barFormatter generated HTML
win_table.draw(win_data, {allowHtml: true});
[/js]

Summing up

The most interesting thing to me is that the large market teams are getting a huge discount. Even up against the hard cap, the Lakers are essentially paying half price for their wins. At the same time various small market teams (sorry New Orleans, Charlotte and Indiana) are in major trouble unless they are a contender every year. The big market teams have a major advantage against the small market teams. It’s not that they can buy more wins; in fact, the numbers show spending is a very poor predictor of winning. No, the major advantage that the big market teams have is that they can afford to lose. Small market teams don’t have the same luxury.

If we ask who the salary cap helps it turns out it is the big market teams. The fact that any big market can only spend around $90 million means that as long as they produce pedestrian basketball (see New York) they’ll be fine. The “competitive balance” myth we keep hearing about and the “need for salary control” might just be rhetoric by big market teams that want to get an even bigger discount. This will come at the cost of the small market teams and the players, who may very well go along with it, believing that it’s for the best.

-Dre

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