The SGA Standard is open-access and available for use by the entire games industry.
When applying it, please remember that it is a living standard and involves significant iteration and improvement as best practices evolve and consensus between SGA members is achieved.
It is a start. SGA has developed this standard to move the industry away from fragmented individual reporting toward industry‑wide, automated access to analytics and data in the tools and platforms our industry already uses (platforms, engines, devices, etc.). For now, you’ll find:
The Standard itself, divided into several thematic components to ensure usability across the industry and easier accessibility for different actors. Each component includes a data input sheet (with validated industry methodology and common emission data) and an explanatory Standard specification.
A component on any given topic may offer up to four options (Basic, Enhanced, Optimized, Automate), depending on industry-wide availability of data, implementation and your time. Some components can deliver insights in under 10 minutes, others may take 30 minutes, and some require hours—or need a fully automated implementation by a vital industry infrastructure (Automate). You’ll see an estimated duration for data collection and input next to each component, along with the benefits of using it.
To use the data input sheets, select File > Make a copy to create an editable version and input your own organizational data. Don’t hesitate to reach out to the SGA team for support. Hands‑on implementation videos are in the works and will be available soon.
Collect utility bills for office buildings, locations, electricity usage from either utility bills or landlord
days~weeks (need data from landlord) & 40min
Reductions in fossil fuel use will save money. Instructions for calculating the emissions from the most directly controllable sources. Enable technology switching, engagement with landlords/suppliers to communicate sustainability demand.
Instructions for calculating emissions from electricity consumption. Get guidance on engaging with landlords and utilities to communicate sustainability demand. Understand GHG benefit of power-purchase agreements. Benchmarking against industry averages.
Spend-based method: estimate of emissions based on $/€ spent in digital advertising.
hours~days (collect from finance team) & 5 min
Quick and simple calculation of digital advertising emissions for annual reporting. Takes all of 5 minutes once you have a spend-based total for the reporting period. Automates currency conversion into relevant USD/year format – greater accuracy.
Supplier-data-based method: An implementation of the Ad Net Zero GMSF V1.2 specification for digital advertising, made applicable to the SGA Standard. Separate methods for programatic advertising & end-to-end/direct-buy advertising, and options for supplier specific EFs.
needs an automated software solution & 5min
Gain control over GHG emissions from digital advertising, which can be as much as 20% of a large developer’s footprint. Enables target setting and reductions, with levers of control. See where to find efficiencies in ad spend (e.g. specific suppliers, different ad networks, creative optimisation).
Supplier’s own carbon calculator results: Evaluation and guidance for users of cloud computing suppliers with carbon calculators.
hours~days (collect from finance team) & 5 min
SGA advice on which suppliers customer carbon calculators provide reliable measurements. Lower risk of reputational harm. Piece of mind. Guidance on which hyperscaler DC to choose for sustainability calculators if you have a choice.
Spend-based method: estimate of emissions based on $/€ spent on data centre services.
hours~days (collect from finance team) & 5 min
Quick and simple calculation of DC emissions based on $ spent. Takes 5 minutes once you have a spend-based total for the reporting period. Automates currency conversion into relevant USD/year format – greater accuracy.
Supplier embodied carbon emissions: Use of a given IT supplier’s LCA data from product data sheets, etc. Guidance on how to interpret LCA and apply to corporate GHG emissions.
minutes~hours: Depends on quantity of IT purchases, and whether purchases have LCAs in SGA database & 10 min
Accurate measurement of GHG from IT suppliers. Identify more sustainable suppliers and devices.
Spend-based emissions method: Spend-based estimate of emissions based on $/€ spent on IT hardware.
hours~days (collect from finance team) & 5 min
Quick and simple calculation of IT Hardware emissions for annual reporting. Takes all of 5 minutes once you have a spend-based total for the reporting period. Automates currency conversion into relevant USD/year format – greater accuracy.
Land-based travel: Multiple methods for different ground based transport for business, using either distance & fuel methods, or spend-based fallbacks.
Air-based travel: Distance-based method for flights, and spend-based fallbacks.
Hotel stays: Night-based method for calculating
hours~days (collect from travel or finance team) & ~15 minutes data entry, variable based on org size
Accurate measurement for annual reporting. Enable quantification of benefits from sustainable travel policy, mode shift.
Physical commuting: Staff survey to collect each employees weekly commute details (mode of transport, distance travelled)
Work-from-home (devices): Multiple options for estimating energy used by employee devices, including average device energy (based on IT data), or WFH emissions figure (published gov. research)
Work-from-home (heating/cooling/lighting): Estimations based on heating/cooling months in region, with methods for specific heat/cooling technologies in employee homes.
hours~days (survey design, release, wait for response) &
~30mins for data entry,
~20 mins for data entry,
~10 mins for data entry
Enables policy choices to support sustainable transport modes by employees (free PT travel, EV chargers, etc).
Enables policy choices that support sustainable WFH – e.g. renewable power subsidy, concessional loans for solar installs, improved efficiency of devices.
Enables analysis of the effect of in-office/WFH policy.
Game Installs: Export data from digital distribution platforms (Steam, App store, etc) and import into spreadsheet, based on size of game file and average download in region
Game Updates: Total data from updates downloaded by players from digital distribution platforms, some user calculation may be required.
End user devices optional: only required for games above certain audience/file size thresholds
1~5 minutes (if you have access to Steam/download metrics, otherwise hours~days wait for team member with access to collect & 5 minute (copy+paste)
~hours (may need to contact ops teams) & ~30mins (some manual calculation may be required for lots of games/updates)
1~5 minutes (if you have access to Steam/download metrics, otherwise hours~days wait for team member with access to collect) & 5 minutes
Super simple copy+paste export from Steam (and eventually other platforms). Provides insight into effect of size of game files in specific regions. Enable control over download emissions via, e.g. packing game files differently/efficiently, leaving high-resolution textures as an optional download instead of for all players by default.
Identify the impact of game updates, release schedules. Identifies where digital distribution partners can simplify the process & enable more transparency. Pathway to identification of more/less sustainable digital distribution platforms.
Provides greater accuracy and completeness for GHG reporting. Optional method enables simplicity for small games, small audiences.
Measured power consumption: Actual observed power use from phone batteries (kWh)
Needs an automated software solution & Automatic once software implemented.
Enables control over end-user energy consumption & emissions. Reduces “padding”and overestimation in S3.11 end-user emissions reporting. Enables energy efficiency through measurement and deployment of software changes, eco-modes, etc. Better user experience for players by reducing battery consumption, identifying energy inefficiency in games. Prolongs the life of batteries in users’ devices by draining them slower. Identify the impact of game updates, release schedules. Identifies where digital distribution partners can simplify the process & enable more transparency. Pathway to identification of more/less sustainable digital distribution platforms. Provides greater accuracy and completeness for GHG reporting. Optional method enables simplicity for small games, small audiences.
Inferred measurement: inferred energy consumption from battery (%)
Needs an automated software solution & Automatic once software implemented.
Enables control over end-user energy consumption & emissions. Reduces “padding”and overestimation in S3.11 end-user emissions reporting. Enables energy efficiency through measurement and deployment of software changes, eco-modes, etc. Better user experience for players by reducing battery consumption, identifying energy inefficiency in games. Prolongs the life of batteries in users’ devices by draining them slower. Identify the impact of game updates, release schedules. Identifies where digital distribution partners can simplify the process & enable more transparency. Pathway to identification of more/less sustainable digital distribution platforms. Provides greater accuracy and completeness for GHG reporting. Optional method enables simplicity for small games, small audiences.
Estimate, player duration: Estimates energy consumption based on observed player duration and known energy consumption range for mobile devices
Minutes~hours (need access to player engagement metrics) & 15 min
Enables moderate GHG accuracy based on player duration metrics. More accurate figures for annual GHG reporting, less over-estimating.
Estimate based on sales data or installs: Estimates energy consumption in low-data environments (no player duration data)
Minutes (need access to sales data) & 10 min
Adequate GHG accurate for annual reporting. Somewhere to start. Quick and easy.
Platform energy measurement Actual observed power use collected by the platform owner (e.g. Microsoft Xbox) and made available to the developer.
Needs an automated platform solution & Automatic once platform solution implemented: Xbox calculation time: 5 minutes (copy+paste)
Identifies the data needed from hardware platform owners in order for developers to accurately measure emissions on consoles. Provides clarity on system boundaries for non-console components required for play. Provides clarity around measuring handheld and stationary consoles. Enables control over end-user energy consumption & emissions. Reduces “padding” and overestimation in S3.11 end-user emissions reporting. Enables energy efficiency through measurement and deployment of software changes, eco-modes, etc. Enables saving users money on their power bills.
Estimate, player duration & device details, Estimate of energy consumption by regional player duration & device details.
~hours (may need to contact other teams) & ~5-15 min (could take some data entry, or copy+paste)
Improved accuracy of GHG emissions for reporting. Provides clarity on system boundaries for non-console components required for play. Provides clarity around measuring handheld and stationary consoles.
Estimate based on sales data or installs, Estimate of energy consumption by estimates of playtime based on sales, MAU, or expected game length.
~hours (need sales data from other teams) & 5 minutes
Provides a place to start for measuring or estimating end-user emissions on consoles in situations of low data. A place to start for anyone, no matter your experience level.
Observed energy measurement: A methodology for future data collection systems and direct observation of energy consumption taken from PC player hardware.
Needs an automated software solution & automatic once software implemented.
A theoretical methodology that enables future ecosystem development via power collection data. Enables energy efficiency improvements, eco modes, etc..Potentially a meaningful money saving for end-users on their power bills given high power requirements of high-end PCs. Theoretically possible, but not currently practically possible. Can point to how much CO2 to be saved through energy efficiency, to help motivate teams to prioritise under-the-hood technical performance.”
Estimate, player duration & device details: Estimate of energy consumption by regional player duration + a model of average PC hardware specifications drawn from the Valve Steam hardware survey.
~hours (may need to contact other teams) & ~5-15 mins (could take some data entry, or be as simple as copy+paste)
Better accuracy over most existing estimates, so improved accuracy & less padding in GHG figures. Draws on Steam hardware survey and PC component hardware database to model global PC hardware expectations and audience split. Evidence-based emissions estimates. SGA maintains database for use in calculations.
Baseline energy consumption via “minimum system requirements” : Baseline “minimum level of energy consumption expected” by using minimum hardware requirements for the game, and modeling energy consumption based on the device hardware characteristics.
5 min & 5 minutes
Produces “baseline” minimum expected energy & emissions. Somewhere to start, quick and easy, based on the minimum system specs for a PC game. SGA hardware model – pick CPU/GPU combo and rest is automated.