> For the complete documentation index, see [llms.txt](https://docs.sportmonks.com/v3/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.sportmonks.com/v3/tutorials-and-guides/tutorials/enrich-your-response/nested-includes.md). # Nested includes We ended the previous chapter with a small teaser about nested includes. Now in this part, we finally present to you the nested include. This tutorial will teach you what it is, where it is used and how you can apply them yourself. ### Nested includes The nested include allows you to further enrich your data by requesting more information from a standard include. Might sound difficult, but we assure you, it’s anything but hard. This is how we use nested includes. ### Create your request For example, in our [includes tutorial ](/v3/tutorials-and-guides/tutorials/includes.md)you’ve enriched your [GET Fixture by Date](/v3/endpoints-and-entities/endpoints/fixtures/get-fixtures-by-date.md) request with the `participant`, and `events` includes: ```javascript https://api.sportmonks.com/v3/football/fixtures/date/2022-09-03?api_token=YOUR_TOKEN&include=participants;events ``` The include event shows you the data about players who received a card, scored a goal, or were substituted. A snippet of the response:
Response ```javascript { "data": [ { "id": 18535517, "sport_id": 1, "league_id": 501, "season_id": 19735, "stage_id": 77457866, "group_id": null, "aggregate_id": null, "round_id": 274719, "state_id": 5, "venue_id": 8909, "name": "Celtic vs Rangers", "starting_at": "2022-09-03 11:30:00", "result_info": "Celtic won after full-time.", "leg": "1/1", "details": null, "length": 90, "placeholder": false, "last_processed_at": "2023-02-17 10:19:55", "has_odds": true, "starting_at_timestamp": 1662204600, "participants": [ { "id": 53, "sport_id": 1, "country_id": 1161, "venue_id": 8909, "gender": "male", "name": "Celtic", "short_code": "CEL", "image_path": "https://cdn.sportmonks.com/images/soccer/teams/21/53.png", "founded": 1888, "type": "domestic", "placeholder": false, "last_played_at": "2023-02-26 15:00:00", "meta": { "location": "home", "winner": true, "position": 1 } }, { "id": 62, "sport_id": 1, "country_id": 1161, "venue_id": 8914, "gender": "male", "name": "Rangers", "short_code": "RAN", "image_path": "https://cdn.sportmonks.com/images/soccer/teams/30/62.png", "founded": 1873, "type": "domestic", "placeholder": false, "last_played_at": "2023-02-26 15:00:00", "meta": { "location": "away", "winner": false, "position": 2 } } ], "events": [ { "id": 42683644, "fixture_id": 18535517, "period_id": 4296154, "participant_id": 53, "type_id": 18, "section": "event", "player_id": 3298, "related_player_id": 10966261, "player_name": "Aaron Mooy", "related_player_name": "R. Hatate", "result": null, "info": null, "addition": null, "minute": 73, "extra_minute": null, "injured": false, "on_bench": false, "coach_id": null, "sub_type_id": null }, //And more ```
But what if we want to know more about the players, who scored a goal, like their country of origin, height, weight, age, image, etc? This is where the nested include comes into play! ### Using nested includes The nested includes are represented in the form of dots (.), which are then linked to a standard include. This shows their relationship. {% hint style="info" %} Check our [syntax section](/v3/api/syntax.md) for a complete syntax overview. {% endhint %} Because the include event is related to a player. You can add `.player` to the include, which will result in the nested include: `events.player` {% code overflow="wrap" %} ```javascript https://api.sportmonks.com/v3/football/fixtures/date/2022-09-03?api_token=YOUR_TOKEN&include=participants;events.player ``` {% endcode %}
Response ```javascript { "data": [ { "id": 18535517, "sport_id": 1, "league_id": 501, "season_id": 19735, "stage_id": 77457866, "group_id": null, "aggregate_id": null, "round_id": 274719, "state_id": 5, "venue_id": 8909, "name": "Celtic vs Rangers", "starting_at": "2022-09-03 11:30:00", "result_info": "Celtic won after full-time.", "leg": "1/1", "details": null, "length": 90, "placeholder": false, "last_processed_at": "2023-02-17 10:19:55", "has_odds": true, "starting_at_timestamp": 1662204600, "participants": [ { "id": 53, "sport_id": 1, "country_id": 1161, "venue_id": 8909, "gender": "male", "name": "Celtic", "short_code": "CEL", "image_path": "https://cdn.sportmonks.com/images/soccer/teams/21/53.png", "founded": 1888, "type": "domestic", "placeholder": false, "last_played_at": "2023-02-26 15:00:00", "meta": { "location": "home", "winner": true, "position": 1 } }, { "id": 62, "sport_id": 1, "country_id": 1161, "venue_id": 8914, "gender": "male", "name": "Rangers", "short_code": "RAN", "image_path": "https://cdn.sportmonks.com/images/soccer/teams/30/62.png", "founded": 1873, "type": "domestic", "placeholder": false, "last_played_at": "2023-02-26 15:00:00", "meta": { "location": "away", "winner": false, "position": 2 } } ], "events": [ { "id": 42683644, "fixture_id": 18535517, "period_id": 4296154, "participant_id": 53, "type_id": 18, "section": "event", "player_id": 3298, "related_player_id": 10966261, "player_name": "Aaron Mooy", "related_player_name": "R. Hatate", "result": null, "info": null, "addition": null, "minute": 73, "extra_minute": null, "injured": false, "on_bench": false, "coach_id": null, "sub_type_id": null, "player": { "id": 3298, "sport_id": 1, "country_id": 98, "nationality_id": 98, "city_id": null, "position_id": 26, "detailed_position_id": 153, "type_id": 26, "common_name": "A. Mooy", "firstname": "Aaron", "lastname": "Mooy", "name": "Aaron Mooy", "display_name": "Aaron Mooy", "image_path": "https://cdn.sportmonks.com/images/soccer/players/2/3298.png", "height": 174, "weight": 68, "date_of_birth": "1990-09-15", "gender": "male" } }, ```
Now you've learnt how to enrich your response. However, as you might have noticed you also receive a set of data you're maybe not interested in. In the next chapter, you will learn how you can filter and select specific fields of the response. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.sportmonks.com/v3/tutorials-and-guides/tutorials/enrich-your-response/nested-includes.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.