This method still might require some work, especially in parsing the response from Betfair.
Having logged in using the betfair function, the environment contains the marketBook method, which can be used to get market data. You can use marketBook to retrieve data about the market, but more importantly the price data for the various runners in the market.
bf$marketBook(marketIds = list(),
priceProjection = "EX_BEST_OFFERS",
orderProjection = "EXECUTABLE",
matchProjection = "NO_ROLLUP",
getRunners = NULL)| param | details |
|---|---|
marketIds |
string, one or more marketIds, the number of markets returned depends on the amount of data you request via the priceProjection |
priceProjection |
the projection of price data you want to receive in the response, options include SP_AVAILABLE, SP_TRADED, EX_BEST_OFFERS, EX_ALL_OFFERS (trumps EX_BEST_OFFERS), and EX_TRADED, these are expained in Betting Enums under the Price Data header. |
orderProjection |
the order Projection you wish to receive in the response, ALL all orders (entirely matched, or not), EXECUTABLE orders with unmatched portion, EXECUTION_COMPLETE orders with no unmatched portion, see Betting Enums under the Order Projection header. |
matchProjection |
if you ask for orders via orderProjection, this will specify the representation of the matched bets, options are NO_ROLLUP returns raw fragments, ROLLED_UP_BY_PRICE rolled up matched amounts by distinct matched prices per side, and ROLLED_UP_BY_AVG_PRICE rolled up by average price per side, see Betting Enums under Match Projection header. |
getRUnners |
if you wish to retrieve data about the runners, such as runners names (which are found in the [marketCatalogue])[methods_marketCatalogue.html] method) then you can supply either RUNNER_DESCRIPTION or RUNNER_METADATA to this parameter which will append runner data to the response |
A list with 3 elements, there are two dataframes, one about the market, and one about the runners. The list also contains the raw response which may contain additional data that may be of interest. Some of this additional data could be market depth data if EX_ALL_OFFERS is entered into the priceProjection parameter. The list returned can be printed, allowing for quick glance at the market before users analyse the data further, or the list can be summarised.
library(betfaiR)
# login
bf <- betfair(usr = Sys.getenv("bf_usr"),
pwd = Sys.getenv("bf_pwd"),
key = Sys.getenv("bf_key"))Login successful# get market data on just one market
tmp <- bf$marketCatalogue(filter = marketFilter(eventTypeIds = 1,
marketTypeCodes = "MATCH_ODDS"),
marketProjection = "COMPETITION",
maxResults = 5)
summary(tmp)
Market ID: 1.129283812
Event ID: 2883157
Market Name: Match Odds
Event Name: Israeli Premier League (W)
Matched: 17575.75
---------------------------------------------------------------------------
Market ID: 1.129282478
Event ID: 2883157
Market Name: Match Odds
Event Name: Israeli Premier League (W)
Matched: 489.55
---------------------------------------------------------------------------
Market ID: 1.129281623
Event ID: 8616348
Market Name: Match Odds
Event Name: Friendly
Matched: 29087.73
---------------------------------------------------------------------------
Market ID: 1.129302418
Event ID: 5808320
Market Name: Match Odds
Event Name: SPFL Development League
Matched: 21229.97
---------------------------------------------------------------------------
Market ID: 1.129281559
Event ID: 5808320
Market Name: Match Odds
Event Name: SPFL Development League
Matched: 49138.95
---------------------------------------------------------------------------# find market with most matched
ind <- which.max(sapply(tmp, function(i) i$market$totalMatched))
market <- tmp[[ind]]
summary(market)
Market ID: 1.129281559
Event ID: 5808320
Market Name: Match Odds
Event Name: SPFL Development League
Matched: 49138.95
---------------------------------------------------------------------------market <- bf$marketBook(marketIds = market$market$marketId)
summary(market)
Market ID: 1.129281559
Matched: 50532.89
Available: 23457.72
Runners: 3
.id selectionId handicap status lastPriceTraded totalMatched
7032151 7032151 0 ACTIVE 4.90 9865.55
9001451 9001451 0 ACTIVE 5.10 35323.13
58805 58805 0 ACTIVE 1.65 5344.19
---------------------------------------------------------------------------# collect data on all 5 markets
markets <- bf$marketBook(marketIds = sapply(tmp, function(i) i$market$marketId))
summary(markets)
Market ID: 1.129281559
Matched: 50532.89
Available: 23468.72
Runners: 3
.id selectionId handicap status lastPriceTraded totalMatched
7032151 7032151 0 ACTIVE 4.90 9865.55
9001451 9001451 0 ACTIVE 5.10 35323.13
58805 58805 0 ACTIVE 1.65 5344.19
---------------------------------------------------------------------------
Market ID: 1.129281623
Matched: 29352.52
Available: 17134.86
Runners: 3
.id selectionId handicap status lastPriceTraded totalMatched
7458145 7458145 0 ACTIVE 1.01 28575.13
12407873 12407873 0 ACTIVE 1000.00 340.32
58805 58805 0 ACTIVE 120.00 437.07
---------------------------------------------------------------------------
Market ID: 1.129282478
Matched: 904.19
Available: 13354.89
Runners: 3
.id selectionId handicap status lastPriceTraded totalMatched
6921686 6921686 0 ACTIVE 1.03 787.39
9063891 9063891 0 ACTIVE 200.00 53.60
58805 58805 0 ACTIVE 40.00 63.19
---------------------------------------------------------------------------
Market ID: 1.129283812
Matched: 17669.58
Available: 17152.45
Runners: 3
.id selectionId handicap status lastPriceTraded totalMatched
6921676 6921676 0 ACTIVE 1.01 17453.56
6921649 6921649 0 ACTIVE 1000.00 116.65
58805 58805 0 ACTIVE 120.00 99.35
---------------------------------------------------------------------------
Market ID: 1.129302418
Matched: 22782.58
Available: 1322.21
Runners: 3
.id selectionId handicap status lastPriceTraded totalMatched
6581076 6581076 0 ACTIVE 1.28 21047.29
8981683 8981683 0 ACTIVE 27.00 790.64
58805 58805 0 ACTIVE 5.00 944.65
---------------------------------------------------------------------------# return runner data
marketId <- bf$marketCatalogue(filter = marketFilter(eventTypeIds = 7,
marketCountries = "GB",
marketTypeCodes = "WIN"))
summary(marketId)
Market ID: 1.129307035
Event ID: 28087305
Market Name: 1m Hcap
Event Name: Ling 25th Jan
Matched: 3745.83
---------------------------------------------------------------------------market_with_runner_data <- bf$marketBook(marketIds = marketId[[1]]$market$marketId,
getRunners = "RUNNER_METADATA")
market_with_runner_data[[1]]$runners$`11374273`
$basic
selectionId handicap status adjustmentFactor lastPriceTraded
1 11374273 0 ACTIVE 21.979 4.9
totalMatched
1 363.67
$ex
$back
backPrice backSize
1 4.8 15.20
2 4.7 23.65
3 4.6 52.48
$lay
layPrice laySize
1 5.0 14.41
2 5.1 12.12
3 5.2 39.16
attr(,"class")
[1] "list" "marketBook_runner_ex"
attr(,"class")
[1] "list" "marketBook_runner"
$`11990284`
$basic
selectionId handicap status adjustmentFactor lastPriceTraded
1 11990284 0 ACTIVE 21.979 3.2
totalMatched
1 2051.33
$ex
$back
backPrice backSize
1 3.20 20.16
2 3.15 46.15
3 3.10 72.00
$lay
layPrice laySize
1 3.25 12.31
2 3.30 31.00
3 3.35 59.24
attr(,"class")
[1] "list" "marketBook_runner_ex"
attr(,"class")
[1] "list" "marketBook_runner"
$`11333925`
$basic
selectionId handicap status adjustmentFactor lastPriceTraded
1 11333925 0 ACTIVE 15.034 5
totalMatched
1 298.65
$ex
$back
backPrice backSize
1 5.3 7.62
2 5.2 5.60
3 5.0 12.00
$lay
layPrice laySize
1 7.6 10.89
2 21.0 22.94
attr(,"class")
[1] "list" "marketBook_runner_ex"
attr(,"class")
[1] "list" "marketBook_runner"
$`11799692`
$basic
selectionId handicap status adjustmentFactor lastPriceTraded
1 11799692 0 ACTIVE 11.336 7.6
totalMatched
1 547.48
$ex
$back
backPrice backSize
1 7.4 11.71
2 7.2 17.15
3 7.0 48.00
$lay
layPrice laySize
1 8.0 16.25
2 8.2 15.91
3 9.8 6.00
attr(,"class")
[1] "list" "marketBook_runner_ex"
attr(,"class")
[1] "list" "marketBook_runner"
$`11511589`
$basic
selectionId handicap status adjustmentFactor lastPriceTraded
1 11511589 0 ACTIVE 10.067 8.8
totalMatched
1 256.97
$ex
$back
backPrice backSize
1 8.8 6.07
2 8.6 2.04
3 7.4 2.51
$lay
layPrice laySize
1 9.0 50.00
2 9.4 4.17
3 9.6 30.00
attr(,"class")
[1] "list" "marketBook_runner_ex"
attr(,"class")
[1] "list" "marketBook_runner"
$`12162507`
$basic
selectionId handicap status adjustmentFactor lastPriceTraded
1 12162507 0 ACTIVE 7.155 10.5
totalMatched
1 288.35
$ex
$back
backPrice backSize
1 10.5 6.93
2 9.8 2.92
3 9.6 9.57
$lay
layPrice laySize
1 11.5 7.61
2 12.5 2.00
3 13.5 2.00
attr(,"class")
[1] "list" "marketBook_runner_ex"
attr(,"class")
[1] "list" "marketBook_runner"
$`12081208`
$basic
selectionId handicap status adjustmentFactor lastPriceTraded
1 12081208 0 ACTIVE 7.155 25
totalMatched
1 38.14
$ex
$back
backPrice backSize
1 28 3.75
2 27 2.93
3 19 2.51
$lay
layPrice laySize
1 120 21.19
attr(,"class")
[1] "list" "marketBook_runner_ex"
attr(,"class")
[1] "list" "marketBook_runner"
$`11198764`
$basic
selectionId handicap status adjustmentFactor lastPriceTraded
1 11198764 0 ACTIVE 5.294 32
totalMatched
1 33.8
$ex
$back
backPrice backSize
1 32 3.06
2 26 5.76
3 25 3.19
$lay
layPrice laySize
1 50 4.07
2 55 5.00
3 60 5.00
attr(,"class")
[1] "list" "marketBook_runner_ex"
attr(,"class")
[1] "list" "marketBook_runner"
attr(,"class")
[1] "marketBook_runners"str(market_with_runner_data[[1]]$runner_metadata)'data.frame': 8 obs. of 32 variables:
$ sire_name : chr "Makfi" "Cape Cross" "Dream Ahead" "Medicean" ...
$ cloth_number_alpha : chr "4" "1" "3" "6" ...
$ official_rating : chr "72" "75" "74" "68" ...
$ colours_description : chr "White, dark blue star, dark blue sleeves, white stars, white cap, dark blue star" "Royal blue" "White and yellow (halved), sleeves reversed, red and white striped cap" "Royal blue and white diamonds, white sleeves, royal blue armlets, quartered cap" ...
$ colours_filename : chr "c20170125lin/00830679.jpg" "c20170125lin/00012133.jpg" "c20170125lin/00842067.jpg" "c20170125lin/00001908.jpg" ...
$ forecastprice_denominator: chr "2" "2" "2" "2" ...
$ damsire_name : chr "Clodovil" "Dubai Destination" "Choisir" "Averti" ...
$ weight_value : chr "130" "133" "132" "126" ...
$ sex_type : chr "f" "f" "f" "f" ...
$ days_since_last_run : chr "15" "36" "12" "7" ...
$ owner_name : chr "Mr Saeed H. Altayer" "Godolphin" "Mrs Anne Coughlan & Ten Green Bottles" "Mr D. J. Deer" ...
$ dam_year_born : chr "2007" "2009" "2006" "2004" ...
$ sire_bred : chr "UK" "IRE" "USA" "UK" ...
$ jockey_name : chr "Martin Lane" "Robert Tart" "Shane Kelly" "Kieran Shoemark" ...
$ dam_bred : chr "IRE" "UK" "IRE" "UK" ...
$ adjusted_rating : chr "0" "0" "0" "0" ...
$ runnerid : chr "11374273" "11990284" "11333925" "11799692" ...
$ cloth_number : chr "4" "1" "3" "6" ...
$ sire_year_born : chr "2007" "1994" "2008" "1997" ...
$ trainer_name : chr "Simon Crisford" "John Gosden" "David Elsworth" "Roger Charlton" ...
$ colour_type : chr "b" "b" "ch" "b" ...
$ age : chr "3" "3" "3" "3" ...
$ damsire_bred : chr "IRE" "USA" "AUS" "IRE" ...
$ form : chr "404-1" "4144-" "627-1" "97569-2" ...
$ forecastprice_numerator : chr "7" "7" "11" "15" ...
$ bred : chr "GB" "IRE" "IRE" "GB" ...
$ dam_name : chr "Maid In Heaven" "Rythmic" "Choose Me" "Oystermouth" ...
$ damsire_year_born : chr "2000" "1999" "1999" "1991" ...
$ stall_draw : chr "7" "3" "6" "5" ...
$ weight_units : chr "pounds" "pounds" "pounds" "pounds" ...
$ wearing : chr NA NA NA "cheekpieces" ...
$ jockey_claim : chr NA NA NA "3" ...