Skip to main content

​
Overview

The Bet Model defines data structures for tracked bets and arbitrage opportunities in the PROPPR platform.

​
Tracked Bet Document

​
Schema

​
bet_id
string
required
Unique bet tracking ID (ObjectId string)
​
alert_id
string
Reference to original alert
​
tracked_at
datetime
required
Timestamp when bet was tracked
​
player_name
string
Player name (Player Bot only)
​
player_id
integer
Player ID (Player Bot only)
​
team
string
Team name
​
team_id
integer
Team ID
​
market
string
required
Betting market (e.g., “Player Shots On Target”)
​
match
string
required
Match name (e.g., “Liverpool vs Man City”)
​
date
string
Match date (YYYY-MM-DD)
​
time
string
Match time (HH:MM)
​
threshold
float
Market threshold (e.g., 1.5)
​
market_direction
string
“over” or “under”
​
bookmaker
string
Bookmaker name
​
odds
float
required
Decimal odds
​
actual_stake
float
required
Actual stake in currency
​
unit_size
float
required
User’s unit size
​
units_staked
float
required
Stake in units
​
status
string
default:"pending"
“pending”, “won”, “lost”, “refund”, “half_win”, “half_loss”
​
manual_override
boolean
default:"false"
If true, bet was manually graded (protected from auto-grading)
​
returns
float
default:"0.0"
Total return amount
​
profit_loss
float
default:"0.0"
Profit or loss amount
​
fixture_id
integer
Fixture/match ID
​
settled_at
datetime
Timestamp when bet was settled
​
actual_value
float
Actual statistic value from match
​
result_tracking
object
Result tracking metadata for auto-grading

​
Result Tracking Object

​
result_tracking.api_type_id
integer
API type ID for statistic
​
result_tracking.api_location
string
“home”, “away”, “total”, or “player”
​
result_tracking.stat_type
string
Stat type (e.g., “shots_on_target”, “goals”)
​
result_tracking.expected_threshold
float
Expected threshold value
​
result_tracking.market_direction
string
“over” or “under”
​
result_tracking.result_status
string
“pending”, “won”, “lost”, “refund”, “half_win”, “half_loss”
​
result_tracking.actual_value
float
Actual value from grading
​
result_tracking.graded_at
datetime
Grading timestamp

​
Example Document

{
  "bet_id": "65f3b2c4e5f6a7b8c9d0e1f2",
  "alert_id": "12345|67890|Player Shots On Target|last5|Bet365",
  "tracked_at": "2024-03-10T14:30:00Z",
  "player_name": "Mohamed Salah",
  "player_id": 118748,
  "team": "Liverpool",
  "team_id": 55,
  "market": "Player Shots On Target",
  "match": "Liverpool vs Manchester City",
  "date": "2024-03-10",
  "time": "16:30",
  "threshold": 1.5,
  "market_direction": "over",
  "bookmaker": "Bet365",
  "odds": 2.10,
  "actual_stake": 10.0,
  "unit_size": 10.0,
  "units_staked": 1.0,
  "status": "won",
  "manual_override": false,
  "returns": 21.0,
  "profit_loss": 11.0,
  "fixture_id": 19245678,
  "settled_at": "2024-03-10T18:45:00Z",
  "actual_value": 3.0,
  "result_tracking": {
    "api_type_id": 86,
    "api_location": "player",
    "stat_type": "shots_on_target",
    "expected_threshold": 1.5,
    "market_direction": "over",
    "result_status": "won",
    "actual_value": 3.0,
    "graded_at": "2024-03-10T18:45:00Z"
  }
}

​
Arbitrage Bet Document

​
Schema

​
id
string
required
Unique arbitrage ID
​
eventId
integer
required
Event/fixture ID
​
profitMargin
float
required
Profit margin percentage
​
totalStake
float
required
Total stake amount
​
market
object
required
Market details
​
legs
array
required
Array of bet legs (minimum 2)
​
event
object
required
Event/fixture details
​
created_at
datetime
Creation timestamp
​
expires_at
datetime
Expiration timestamp
​
sport
string
Sport name
​
league
string
League name

​
Market Object

​
market.name
string
required
Market name (e.g., “Totals”, “Moneyline”)
​
market.hdp
float
Handicap value (e.g., 2.5)
​
market.totals_stat
string
Stat type for totals (e.g., “goals”, “points”)

​
Leg Object

​
legs[].bookmaker
string
required
Bookmaker name
​
legs[].side
string
required
Bet side (“over”, “under”, “home”, “away”, “draw”)
​
legs[].odds
string
required
Decimal odds as string
​
legs[].is_lay
boolean
default:"false"
Whether this is a LAY bet (exchange)
​
legs[].market_name
string
Market name for this leg
​
legs[].hdp
float
Handicap for this leg
​
legs[].updatedAt
string
Last odds update timestamp

​
Event Object

​
event.home
string
required
Home team name
​
event.away
string
required
Away team name
​
event.date
string
required
Event date/time (ISO 8601)
​
event.sport
string
required
Sport name
​
event.league
string
required
League name

​
Example: Standard Arbitrage

{
  "id": "arb_12345",
  "eventId": 19245678,
  "profitMargin": 3.73,
  "totalStake": 100.0,
  "market": {
    "name": "Totals",
    "hdp": 2.5
  },
  "legs": [
    {
      "bookmaker": "Bet365",
      "side": "over",
      "odds": "2.10",
      "is_lay": false,
      "market_name": "Totals",
      "hdp": 2.5,
      "updatedAt": "2024-03-10T14:25:00Z"
    },
    {
      "bookmaker": "Pinnacle",
      "side": "under",
      "odds": "2.05",
      "is_lay": false,
      "market_name": "Totals",
      "hdp": 2.5,
      "updatedAt": "2024-03-10T14:26:00Z"
    }
  ],
  "event": {
    "home": "Liverpool",
    "away": "Manchester City",
    "date": "2024-03-10T16:30:00Z",
    "sport": "Football",
    "league": "England - Premier League"
  },
  "created_at": "2024-03-10T14:27:00Z",
  "expires_at": "2024-03-10T16:30:00Z"
}

​
Example: LAY Arbitrage

{
  "id": "lay_arb_67890",
  "eventId": 19245678,
  "profitMargin": 2.45,
  "totalStake": 100.0,
  "market": {
    "name": "Totals",
    "hdp": 2.5
  },
  "legs": [
    {
      "bookmaker": "Bet365",
      "side": "over",
      "odds": "2.10",
      "is_lay": false
    },
    {
      "bookmaker": "Betfair Exchange",
      "side": "over",
      "odds": "2.15",
      "is_lay": true,
      "lay_stake": 46.51,
      "liability": 53.49,
      "commission": 2.0
    }
  ],
  "event": {
    "home": "Liverpool",
    "away": "Manchester City",
    "date": "2024-03-10T16:30:00Z",
    "sport": "Football",
    "league": "England - Premier League"
  },
  "is_lay_arb": true,
  "exchange_commission": 2.0
}

​
User Bets Collection

​
Schema

​
user_id
integer
required
Telegram user ID
​
bets
array
required
Array of tracked bet documents
​
created_at
datetime
User document creation timestamp
​
last_updated
datetime
Last update timestamp
​
unit_size
float
User’s current unit size
​
username
string
Telegram username

​
Example Document

{
  "user_id": 123456789,
  "username": "john_doe",
  "unit_size": 10.0,
  "created_at": "2024-01-15T10:00:00Z",
  "last_updated": "2024-03-10T18:45:00Z",
  "bets": [
    {
      "bet_id": "65f3b2c4e5f6a7b8c9d0e1f2",
      "market": "Player Shots On Target",
      "player_name": "Mohamed Salah",
      "status": "won",
      "odds": 2.10,
      "units_staked": 1.0,
      "returns": 21.0,
      "profit_loss": 11.0
    }
  ]
}

​
Status Enums

​
Bet Status

  • pending - Awaiting result
  • won - Bet won
  • lost - Bet lost
  • refund - Bet refunded (push)
  • half_win - Half stake won (Asian handicap)
  • half_loss - Half stake lost (Asian handicap)

​
Market Direction

  • over - Over threshold
  • under - Under threshold

​
Bet Sides

  • over - Over (totals)
  • under - Under (totals)
  • home - Home team
  • away - Away team
  • draw - Draw
  • yes - Yes
  • no - No

​
Indexes

​
Tracked Bets Collection

// User lookup
db.user_tracked_bets.createIndex({ "user_id": 1 }, { unique: true })

// Bet ID lookup
db.user_tracked_bets.createIndex({ "bets.bet_id": 1 })

// Status filtering
db.user_tracked_bets.createIndex({ "bets.status": 1 })

​
Arbitrage Bets Collection

// Expiration cleanup
db.arbitrage_bets.createIndex({ "expires_at": 1 })

// Event lookup
db.arbitrage_bets.createIndex({ "eventId": 1 })

// Sport filtering
db.arbitrage_bets.createIndex({ "sport": 1 })

// League filtering
db.arbitrage_bets.createIndex({ "league": 1 })

​
References

Build docs developers (and LLMs) love

Get started for freeTalk to us