Pre-Computed Injury Impact#
The following describes how to retrieve pre-computed injury impact predictions through the Quarter4 REST APIs.
Using the REST API to query for Injury Effect Simulations#
Related APIS
Method | Description | Availability |
---|---|---|
POST |
/{sport}/v2/injury_impacts | NFL |
The injury impact api allows you to retrieve current Player Effect results that were generated using the Player Effect API. These are generated for each injured players on a roster and include the Player Effect results for if the player is in and out of the game. The results are provided as a quick way to retrieve the Player Effect results for comparison of an individual player's impact.
Use the event.uuid
query parameter to filter to a specific event.
For example, here are the results for an NFL event:
GET https://api.quarter4.io/american-football/v2/injury_impacts?event.uuid=d2656fe4-1c17-4aec-a0b2-a753122de63d
Note
This result is very large so the example is not displayed here.
The result will contain a data array, each entity with an attribute of playerEffectIn
and playerEffectOut
. These properties contain the list of relevant player props for the players playing in the game.
- The
playerEffectIn
attribute contains prediction as if the target player was Playing in the game. - The
playerEffectOut
attribute contains prediction as if the target player was NOT Playing in the game.
You can then use the two result sets to compare how a player's predicted performance is expected to change when the target player is in ou out.
For example:
{
"links": {
"self": "\/american-football\/v2\/injury_impacts?event.uuid=d2656fe4-1c17-4aec-a0b2-a753122de63d"
},
"meta": {
"totalItems": 13,
"itemsPerPage": 30,
"currentPage": 1
},
"data": [
{
"id": "\/american-football\/v2\/injury_impacts\/c0b38013-8452-4bb3-b49c-ab4cc1ad8560",
"type": "InjuryImpact",
"attributes": {
"playerEffectIn": {
"c0b454d6-1640-4f8e-9360-61deb40ca6aa": {
"team_id": "c023d5ce-83ec-4263-8662-1f411058d8de",
"player_id": "c0b454d6-1640-4f8e-9360-61deb40ca6aa",
"position": "QB",
"stats": {
"passing_touchdowns": 1.9,
"passing_longest": 49.7,
"passing_yards": 330.7,
"passing_completions": 26.8,
"passing_attempts": 40,
"passing_cmp_pct": 0.7,
"passing_sacks": 3.7,
"passing_sack_yards": 24.6,
"passing_interceptions": 0.4
},
"player_name": "Russell Wilson",
"team_name": "Denver Broncos",
"uniform": "3",
"player_image": "https:\/\/avatar.api.quarter4.io\/american-football\/avatar\/c023d5ce-83ec-4263-8662-1f411058d8de\/256\/uniform\/3.png"
},
---cut---
"playerEffectOut": {
"c0b454d6-1640-4f8e-9360-61deb40ca6aa": {
"team_id": "c023d5ce-83ec-4263-8662-1f411058d8de",
"player_id": "c0b454d6-1640-4f8e-9360-61deb40ca6aa",
"position": "QB",
"stats": {
"passing_touchdowns": 1.9,
"passing_longest": 50.2,
"passing_yards": 332.1,
"passing_completions": 27,
"passing_attempts": 40.3,
"passing_cmp_pct": 0.7,
"passing_sacks": 3.7,
"passing_sack_yards": 24.8,
"passing_interceptions": 0.4
},
"player_name": "Russell Wilson",
"team_name": "Denver Broncos",
"uniform": "3",
"player_image": "https:\/\/avatar.api.quarter4.io\/american-football\/avatar\/c023d5ce-83ec-4263-8662-1f411058d8de\/256\/uniform\/3.png"
},
---cut---
Here, you can see that when the target player is out, player c0b454d6-1640-4f8e-9360-61deb40ca6aa
's predicted passing yards increase from 330.7
to 332.1
.
Warning
The Injury Impact API results only deals with a single player at a time and does not include pre-computed results for multiple players. For example it does not include results for if player A & B are out
vs if player A & B are in
. You can use the Player Effect API to generate more advanced results.