• Gaming
  • 16 columns
  • 200 rows
  • 8 formats

Game Session Telemetry Dataset

This dataset contains detailed logs of simulated online gaming sessions, including player identifiers, session timings, actions, feature usage, purchases, and outcomes. Designed for gaming analytics, it enables churn prediction, player segmentation, and feature adoption analysis, offering valuable insights for game developers and startups.

  • opened 14 times
  • last updated 21 Aug 2025
  • by GoMask
The brief that made it

Churn prediction and retention analysis

Sample rows

preview · 8 of 200 rows · all 16 columns
session_idstringplayer_segmentstringnetwork_latency_msintegerchurn_flagbooleancountrystringplayer_idstringgame_idstringsession_start_timedatetimesession_end_timedatetimesession_duration_secondsintegerplayer_levelintegerfeatures_usedstringactions_countintegerin_game_purchasesfloatsession_outcomestringdevice_typestring
S0001new241trueINP1001G0012024-05-02T13:34:05Z2024-05-02T13:34:11Z61tutorial10abandonedmobile
S0002casual117falseUSP1002G0022024-06-07T16:22:50Z2024-06-07T16:57:50Z210018chat,skins,marketplace490.99winmobile
S0003new302falseZAP1003G0032024-05-13T19:02:02Z2024-05-13T19:02:03Z12blank00abandonedconsole
S0004competitive14falseDEP1004G0042024-06-10T11:18:19Z2024-06-10T14:58:19Z1320037team_match,voice_chat,chat,leaderboard,inventory711125.5winPC
S0005competitive24falseFRP1005G0052024-06-15T21:44:00Z2024-06-15T22:44:00Z360024team_match,customization,chat,inventory25659.99lossPC
S0006casual140falseMXP1006G0062024-04-28T09:10:41Z2024-04-28T09:40:41Z180012chat,skins380drawmobile
S0007other495falseEGP1007G0072024-06-12T15:21:55Z2024-06-12T15:31:55Z6006chat,marketplace90drawother
S0008competitive9falseKRP1008G0082024-06-03T06:55:11Z2024-06-03T10:55:11Z1440030team_match,leaderboard,chat,inventory38256.5winPC

What the 200 rows show

from the 200-row sample

Other (player segment) stands out: mean network_latency_ms is 647.0, against 114.7 for the rest.

  • 14%churn_flag = true
  • 112median network_latency_ms
  • 4session outcomes
  • 4device types
  • 5,400median session_duration_seconds
  • 26median player_level
Mean network_latency_ms by player_segment200 rows
0400800136.4casual46 rows19.1compet…57 rows270.3new33 rows95.6return…36 rows647.0other28 rows
network_latency_ms200 rows, in bands of 100
0459085532212123413505001,000network_latency_ms →

Median 112, from 2 to 999.

country200 rows · top 10 of 15 values
  1. US25
  2. CA19
  3. DE18
  4. KR17
  5. FR16
  6. MX16
  7. SE15
  8. IN12
  9. AU12
  10. EG11
16 columns by typefrom the column list below
  • string 8
  • integer 4
  • float 1
  • datetime 2
  • boolean 1

Columns

16 columns in four groups
blueprint · 16 columns
columntypedescriptionexample
Text 8 columns
session_idstringUnique identifier for each gameplay sessionuniqueS0001
player_idstringUnique identifier for the playerP1001
game_idstringUnique identifier for the game being playedG001
player_segmentstringPlayer segment or category (e.g., casual, competitive, new, returning)casual · competitive · new · returning · other · optionalnew
features_usedstringComma-separated list of key game features used during the sessionoptionaltutorial
session_outcomestringOutcome of the session (e.g., win, loss, draw, abandoned)win · loss · draw · abandoned · other · optionalabandoned
device_typestringType of device used for the session (e.g., PC, console, mobile)PC · console · mobile · other · optionalmobile
countrystringCountry where the session was playedoptionalIN
Numbers 5 columns
session_duration_secondsintegerTotal duration of the session in seconds1 or more6
player_levelintegerPlayer's level at the start of the session1 or more1
actions_countintegerTotal number of distinct player actions performed during the session0 or more1
in_game_purchasesfloatTotal value of in-game purchases made during the session (in USD)0 or more · optional0
network_latency_msintegerAverage network latency during the session in milliseconds0 or more · optional241
Dates and times 2 columns
session_start_timedatetimeTimestamp when the session started2024-05-02T13:34:05Z
session_end_timedatetimeTimestamp when the session ended2024-05-02T13:34:11Z
True or false 1 column
churn_flagbooleanIndicates if this session was the player's last before churningoptionaltrue

15 SQL practice questions for the Game Session Telemetry Dataset

Written for this data and checked against it: 12 SQL and 3 Power BI exercises from beginner to advanced. Try the first three free; the practice kit has all 15, a starter .sql file and an answer key with every expected result.

  1. 01BeginnerFreeSELECT · WHERE · ORDER BY

    Long mobile sessions

    Return session_id, player_id and session_duration_seconds for sessions where device_type is 'mobile' and the duration is more than 3600 seconds. Order by session_duration_seconds from highest to lowest, then by session_id ascending.

    Tables: game_session_telemetry_dataset · your result: 3 columns, 12 rows
  2. 02BeginnerFreeDISTINCT · ORDER BY

    Distinct countries

    Return each distinct country in the data as a single column named country, sorted alphabetically.

    Tables: game_session_telemetry_dataset · your result: 1 columns, 15 rows
  3. 03BeginnerFreeGROUP BY · COUNT

    Sessions per outcome

    Count the sessions for each session_outcome. Return session_outcome and sessions, ordered by sessions from highest to lowest, then by session_outcome ascending.

    Tables: game_session_telemetry_dataset · your result: 2 columns, 4 rows
  1. 04Revenue by deviceBeginner
  2. 05Average actions by segmentPower BI
  3. 06Countries with many sessionsIntermediate
  4. 07Latency bucketsIntermediate
  5. 08Sessions above average spendIntermediate
  6. 09Monthly sessions and churnIntermediate
  7. 10Segments above overall average actionsPower BI
  8. 11Rank players by spendAdvanced
  9. 12Gap since previous sessionAdvanced
  10. 13Running purchases by monthAdvanced
  11. 14Share of purchases by countryAdvanced
  12. 15Latency anomalies by devicePower BI

Get the practice kit: the full dataset, all 15 exercises, a starter .sql and the answer key. One-time $3.99.

Get the practice kit · $3.99

Use it for

  • churn flag14%28 of 200 rowsmean network latency …136.4casu…19.1comp…270.3new95.6retu…

    A gaming dashboard

    The churn_flag rate, network_latency_ms by player_segment and a breakdown of country. Excel, Power BI or Tableau.

  • Why do the 28 other rows have a mean network_latency_ms of 647.0?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable sessions with player_id, game_id and session_start_time to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 16 columns, your size and your rules. See 20 rows before you pay.

Preview 20 rows free

1,000 rows: $1.99 · 10,000: $12.99One-time. No subscription. All prices

This dataset200 rows16 columns
Yours1,000 rows16 columnscountry: UK only

blueprint · game-session-telemetry-dataset

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 16 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with
  • Session length varies 1-120 minutes
  • Player ID uniquely assigned per session
  • Game events embedded, max 20 per session
  • Retention labels for repeat sessions
Rows
Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
game-session-telemetry-dataset

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