PC Benchmark Analysis Guide: Measure Gaming Performance

For serious PC gamers and hardware enthusiasts, understanding your system’s true performance capabilities is essential. While running a game and getting a general sense of how it performs is helpful, systematic benchmarking provides concrete data that reveals exactly how your components are performing, and more importantly, where bottlenecks might be limiting your gaming experience. Excel offers a powerful, accessible tool for logging, analyzing, and visualizing this performance data, transforming raw numbers into actionable insights that can guide your upgrade decisions and optimization efforts.

Why Benchmark Your Gaming PC?

Benchmarking serves multiple critical purposes for PC gamers. First, it establishes a performance baseline that you can reference after making changes to your system, whether that’s installing new drivers, upgrading components, or adjusting settings. Second, systematic benchmarking helps identify performance bottlenecks, those frustrating situations where one component limits the performance of others. Third, tracking performance over time can reveal gradual degradation due to thermal paste aging, dust accumulation, or other factors that might otherwise go unnoticed until they become severe problems.

Many gamers rely solely on in-game FPS counters or occasional benchmark runs, but this approach provides only snapshots of performance without revealing trends, patterns, or the relationships between different metrics.

Essential Metrics to Track

Frames Per Second (FPS): The most obvious metric, but track both average FPS and 1% low FPS (the lowest 1% of frame times), as this reveals stuttering and inconsistent performance that average FPS might hide.

GPU Utilization: Measured as a percentage, this shows how hard your graphics card is working. Sustained utilization near 100% suggests your GPU is the bottleneck, while lower utilization might indicate a CPU bottleneck or other limitation.

CPU Utilization: Track both overall CPU usage and per-core usage when possible. Many games don’t utilize all cores equally, and single-thread performance often matters more than multi-threaded benchmarks suggest.

GPU Temperature: Overheating can cause thermal throttling, reducing performance. Track temperatures under load to ensure adequate cooling.

CPU Temperature: Similar to GPU temps, CPU thermal throttling can significantly impact gaming performance.

GPU Clock Speed: Monitoring actual clock speeds versus advertised boost clocks reveals whether thermal or power limitations are preventing your GPU from reaching its potential.

CPU Clock Speed: Track whether your CPU maintains its boost clocks during gaming or throttles down due to thermal or power constraints.

RAM Usage: Understanding memory consumption helps determine whether you need more RAM or if background applications are consuming resources unnecessarily.

Power Consumption: If you have the tools to measure it, power draw can reveal whether your PSU is adequate and whether components are operating within expected parameters.

Game Settings: Don’t forget to log which graphics settings you’re testing, resolution, quality presets, ray tracing status, DLSS/FSR usage, etc.

Tools for Collecting Performance Data

Several free tools make collecting this data straightforward. MSI Afterburner with RivaTuner Statistics Server (RTSS) is perhaps the most popular choice, offering comprehensive monitoring and the ability to log data to CSV files. HWiNFO64 provides even more detailed sensor readings and also supports logging. For AMD users, Radeon Software includes performance monitoring features, while NVIDIA users can leverage GeForce Experience and third-party tools.

The key is configuring your monitoring software to log data at regular intervals, typically every second, during your benchmark runs. Most tools can export this data as CSV (comma-separated values) files, which Excel can easily import and analyze.

Creating an organized Excel workbook for performance tracking ensures consistent data collection and makes analysis much easier. Start by creating a workbook with multiple worksheets for different purposes:

System Configuration Sheet: Document your PC specifications, CPU model, GPU model, RAM amount and speed, storage configuration, motherboard, PSU, and cooling solution. Include a version history tracking when you change components or update drivers. This context is crucial when comparing performance across time.

Benchmark Log Sheet: This is where you’ll paste or import raw data from your monitoring tools. Create columns for timestamp, FPS, GPU utilization, CPU utilization, GPU temperature, CPU temperature, GPU clock speed, CPU clock speed, RAM usage, and any other metrics you’re tracking. Include columns for game name, graphics settings preset, resolution, and any notes about the test conditions.

Summary Statistics Sheet: Here you’ll calculate key metrics for each benchmark run, average FPS, minimum FPS, maximum FPS, 1% low FPS, average temperatures, peak temperatures, average utilization rates, and more. This condensed view makes it easy to compare different benchmark sessions.

Comparison Sheet: Create a dedicated space for side-by-side comparisons of different configurations, settings, or time periods. This might compare performance before and after a driver update, or contrast different graphics quality presets.

Charts and Visualizations Sheet: Dedicate one or more sheets to graphs that visualize your performance data, FPS over time, temperature curves, utilization patterns, and performance comparisons across different scenarios.

Importing and Organizing Data

Once you’ve run benchmarks and generated CSV log files from your monitoring software, clean up the data by removing any unnecessary columns, ensuring timestamps are formatted correctly, and adding identifying information like the date, game tested, and settings used. If you’re tracking multiple benchmark runs, consider adding a “Run ID” column that uniquely identifies each test session.

For ongoing benchmarking, you might run the same test repeatedly over weeks or months. Rather than creating separate files, append new data to your main log sheet, using the Run ID to distinguish between sessions. This approach makes long-term trend analysis much simpler.

Performance Analysis

Excel’s formula capabilities transform raw performance logs into meaningful insights. Start with basic statistical functions:

AVERAGE(): Calculate average FPS, temperatures, and utilization across an entire benchmark run. For example, =AVERAGE(B2:B1000) gives you the mean FPS if your FPS data is in column B, rows 2-1000.

MIN() and MAX(): Find the minimum and maximum values for each metric. Minimum FPS reveals worst-case performance, while maximum temperature shows thermal peaks.

PERCENTILE(): This function is crucial for calculating 1% low FPS, which better represents worst-case frame times than simple minimums. Use =PERCENTILE(B2:B1000, 0.01) to find the 1% low value.

COUNTIF(): Count how many frames fell below 60 FPS, or how many seconds your GPU temperature exceeded 80°C. This helps quantify problems: =COUNTIF(B2:B1000, “<60”) counts FPS readings below 60.

IF() statements: Create conditional logic, such as flagging runs where thermal throttling likely occurred: =IF(E2>85, “Thermal Concern”, “OK”) marks any GPU temperature reading above 85°C.

For more advanced analysis, consider these techniques:

Moving Averages: Smooth out short-term fluctuations to reveal underlying trends. A 10-second moving average of FPS can show performance patterns more clearly than raw per-second data.

Performance Per Watt Calculations: If tracking power consumption, calculate FPS per watt to evaluate efficiency: =B2/J2 where B2 is FPS and J2 is power draw.

Bottleneck Indicators: Create formulas that suggest likely bottlenecks based on utilization patterns. For instance, if GPU utilization is consistently below 95% while CPU utilization on any core exceeds 90%, you likely have a CPU bottleneck.

Developing proficiency with these analytical techniques takes time. For those looking to strengthen their spreadsheet skills beyond gaming benchmarks, online platforms offering Excel practice through structured projects can help build the analytical capabilities needed for sophisticated performance analysis.

Visualizations

Charts transform columns of numbers into visual insights that make patterns immediately apparent. For gaming benchmarks, several chart types like bar charts or scatter plots prove particularly valuable.

When creating charts, always label axes clearly, include units (FPS, °C, MHz, %), add a descriptive title, and use a legend if displaying multiple data series. Consider using color coding consistently, red for temperatures, blue for FPS, green for utilization rates, to make charts intuitively readable.

Identifying Bottlenecks Through Data Analysis

One of Excel’s most powerful applications in PC benchmarking is bottleneck identification. By analyzing the relationships between different metrics, you can pinpoint which component is limiting performance:

GPU Bottleneck: Characterized by GPU utilization consistently at or near 100% while CPU utilization remains moderate (typically below 80% on the most-used cores). In this scenario, your graphics card is working at full capacity while the CPU has headroom. Upgrading the GPU or reducing graphics settings would improve performance.

CPU Bottleneck: Shows as high CPU utilization (especially on individual cores, which may hit 100%) while GPU utilization remains below 95%. The CPU cannot feed the GPU work fast enough. Solutions include upgrading the CPU, reducing settings that are CPU-intensive (like draw distance or NPC density), or increasing graphics quality to shift more load to the GPU.

Thermal Throttling: Revealed when temperatures exceed certain thresholds (typically 85-95°C for GPUs, 95-100°C for CPUs) and you simultaneously observe clock speeds dropping below expected boost frequencies. The correlation between temperature spikes and performance dips clearly indicates thermal limitations.

RAM Limitations: If RAM usage consistently reaches 95%+ of capacity and you observe stuttering (dramatic FPS drops reflected in very low 1% low percentages), insufficient memory may be bottlenecking your system.

Create a simple bottleneck analysis table that summarizes these indicators for each benchmark run. Over time, you’ll build an understanding of how your specific system behaves and where optimization efforts will yield the best results.

Tracking Performance Over Time

One of Excel’s greatest strengths for benchmarking is tracking long-term performance trends. Run the same benchmark, same game, same settings, same scene, monthly or quarterly, logging the results in your workbook. Over six months to a year, patterns emerge:

Degradation Detection: Gradual performance decreases over time might indicate thermal paste drying out, dust accumulation affecting cooling, or driver issues. A line chart showing average FPS across monthly benchmark runs makes these trends obvious.

Seasonal Variations: Ambient temperature affects PC cooling efficiency. Benchmark data from summer versus winter might reveal temperature-related performance differences, informing decisions about improved cooling solutions.

Practical Example

Let’s walk through a practical scenario. You’re considering upgrading from an RTX 3060 Ti to an RTX 4070. Before making the purchase, you benchmark your current system extensively, logging FPS data across several games at 1440p with high settings. Your analysis shows:

Average FPS: 75 across tested games
1% low FPS: 52
GPU utilization: 98-100%
CPU utilization: 65% average, 82% on most-used core

This data clearly indicates a GPU bottleneck, your graphics card is maxed out while the CPU has headroom. After the upgrade, you run identical benchmarks:

Average FPS: 115 (+53% improvement)
1% low FPS: 88 (+69% improvement)
GPU utilization: 75%
CPU utilization: 72% average, 91% on most-used core

The Excel comparison shows the upgrade delivered significant gains and that you’re now approaching a CPU bottleneck in some scenarios, as indicated by the increased CPU utilization while GPU utilization dropped. This informs your next upgrade decision, a CPU upgrade might be next on the roadmap, or you could increase graphics settings to maintain the GPU bottleneck while enjoying better visual quality.

Conclusion

Excel transforms PC benchmarking from a casual “Does this feel faster?” exercise into a rigorous, data-driven analysis that reveals exactly how your system performs and where limitations exist. By systematically logging performance data, calculating meaningful statistics, and creating visualizations that highlight patterns, you gain insights that subjective testing simply cannot provide.

Start simple, log a few benchmark runs, calculate basic averages, create a chart or two. As you become comfortable with the process, expand your analysis with more sophisticated formulas, additional metrics, and deeper insights.

Analysis of PC performance benchmarking