I am building a web application that handles live analytics by fetching data arrays from an external sports pipeline. To establish my parsing logic, I am modeling my system arrays based on the nested data structures outlined in this statistical documentation resource at https://matchstat.com/predictions-tips/the-best-tennis-data-api-for-stats/

The logic works perfectly during initial testing, but my pipeline encounters runtime exceptions when dealing with variable array layouts returned under certain network parameters.

Here is the block of code I am using to parse the incoming response data:

async function processSportsData() { const targetUri = "https://tennis-api-host.p.rapidapi.com/rankings"; const configuration = { method: "GET", headers: { "X-RapidAPI-Key": "MY_AUTHENTICATION_KEY_STRING", "Accept": "application/json" } };

try { const rawData = await fetch(targetUri, configuration); const complexPayload = await rawData.json();

complexPayload.data.results.forEach(record => {
  console.log("Processing records for ID: " + record.profile.id);
  console.log("Current standing metric: " + record.profile.metrics.current_ranking);
});

} catch (executionError) { console.error("Engine failed during execution: ", executionError.message); } }

The problem occurs when the endpoint switches contexts. If the nested metrics block is completely absent or if the results array maps back completely empty, the execution loop immediately throws an uncaught TypeError: Cannot read properties of undefined reading current_ranking, which completely breaks my downstream execution thread.

What is the standard engineering practice for handling these kinds of fluid structural payload variations inside JavaScript loops? Should I run explicit defensive conditional checks on every single nested node layer, or is there a way to safely define fallback object states natively to keep the data mapping smooth?