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Oct 28, 2016
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About This Presentation
BatWatch is a sports betting risk management solution.
Size: 29.51 MB
Language: en
Added: Oct 28, 2016
Slides: 55 pages
Slide Content
Betwatcn
20th-21st May 2016 9 La Térmica, Málaga, Spain
Bringing developers and DevOps together around Big Data
Get Tickets
BetWatch™
Areas that we wanted to address:
+ Risk Management
- Customer Engagement
- Fraud/Problematic Gamblers
vse were also hoping to:
- Frau ropiematic Gamblers
We were also hoping to:
- Increase cross-sell & Up-sell opportunities
« Reduce customer churn
- Increase revenue per customer
- Identify the true value of the customer
- Understand the customer's buying journey
+ Novelty detection
startup
‘focus
EL
SIC EE
UU
2
Account ID | Segment) BETDATE
16Jan2009
DN Event:
ES Profit: (5641)
azo v Cagliari
$736
w
Athletic v
Liverpool
Tottenham Stoke City
Hotspur v v Liverpoo
Portsmouth E
Manchester
United v
Tottenham
Hotspur
Reading v
Watford
OF
Panionios
Powered by
The input metrics for clustering customers
+ LEAD_TIME: the average length of time (in h
that ome wager before the
starts.
The input metrics for clustering customers were:
« LEAD_TIME: the average length of time (in hours)
that a customer places a wager before the event
starts.
« MID_STAKE: the median stake that a customer
wagers (average not used due to right skewed
nature of this metric).
+ MID_ODDS: the median odds that a customer
takes when wagering (average not used due to right
skewed nature of this metric).
+ TURNOVER: Total amount wagered by customer
in AUD.
« RETURN: Total amount won or lost by customer in
AUD.
« ROI: Return on investment for customer as a
percentage = RETURN/TURNOVER.
+ BETTYPE_COUNT: Number of unique bet type
customer has wagered on.
* TURNOVER: Total amount wagered by customer
in AUD,
+ RETURN: Total amount won or lost by customer in
AUD.
+ ROI: Return on investment for customer as a
percentage = RETURN/TURNOVER,
* BETTYPE_COUNT: Number of unique bet type
customer has wagered on.
sl os | : |
.3
E
E)
9
4
al
im
7
ee IEEE INES 2770770 [a DEEE
Profit (millions)
‘ny ters van oe
Son ‘a Cluster 1 -- Moderate
‘atom ing Sized, early betors Cluster 3 ~ Biggest
Cluster 4 = Small,
Sime" wor shat ho ber on- al bet > rn betors, _ specalzing. … apparent
a ves ‘ypes ol offering and i ana few bet ypes and recreational punters,
EA Oi mon spot pes A DD or win à long vito bet on anything
a ee teadsime on wagers. and most bet types.
> potential arbtrages.
0 1 2 3 4 Final
Segment
O1Jan1 900 2
Segment
A …
Cluster 1 -- Moderate
sized, early bettors,
-who- bet on- all- bet-
types of offering and
on most sport types.
These _ are _ your
potential arbitrages.
Cluster 3 -- Biggest
_bettors, _ specializing.
on a few bet types and
sports, with a long
lead-time on wagers.
Cluster 4 -- Small,
apparently _____
recreational punters,
who bet on anything
and most bet types.
AN INVESTIGATION INTO US SPORTSBOOKS AND PROFESSIONAL HANDICAPPERS
1. HOW US SPORTSBOOKS MAKE MONEY:
Sportsbooks make money by keeping the player's losses
and charging a Vig on all winning bets.
man sense
-250 +/-0 +200
MONEY LINE
"BETTER HR
fe H TENDENCY
= i E
a i Shane ss
Sortsbooks often shade the lines by 2-3% on the favorites
in order to charge more to the public:?
es ws
MONEY LINE
“Sportsbooks set the odds based on the likelihood of the outcome,
Prezhowever they also have to tailor the lines to their own pool of players.”
5. AVERAGE WINNING MARGIN% FOR VEGAS SPORTSBOOK
FROM 1992 - 20111
SPORTSBOOK WIN PERCENTAGE ON...
aa =
y =
o
"Baseball has the smallest win percentage, however because there
are so many games it has the highest value for sportsbooks”
Gk 18
MILLION"
Risk Management
@OnlineBettingTM OONLINEBETTING
HOW US SPORTSBOOKS
AN INVESTIGATION INTO US SPORTSBOOKS AND PROFESSIONAL HANDICAPPERS
1. HOW US SPORTSBOOKS MAKE MONEY:
Sportsbooks make money by keeping the player's losses
and charging a Vig on all winning bets.
mens casinos
-250 +/-0 +200
PR PRES PEPA PP
MONEY LINE
Real-time betting/rejecting
J
Multi-leg Parlays
Time to hedge your position:
Cezar Ferreira -200 odds
Edson Barboza -150 odds
Antonia Silva - 150 odds
UFC costs sportsbook nearly $1M
Darren Rovell Feb 23, 2015
ESPN Senior Writer
Aremarkable number of upsets at UFC Fight Night 61 resulted in a historic
beating for the sportsbook Bovada.LV.
Frank Mir's victory over Antonio Silva in the main event in Porto Alegre,
Brazil, on Sunday night marked the 10th win by an underdog, costing
Bovada nearly $1 million, according to the sportsbook's manager.
200058
Underdogs went 10-1, and as a result, parlay bets, in which gamblers bet
between $1 and $5 on all underdogs, hit big.
According to Bovada sportsbook manager Kevin Bradley, one bettor had a
$4 all-underdog parlay that paid $85,000. Another had four $1 parlays that
paid $25,000 each.
"We had at least a dozen of these bets that paid out $10,000 or more,"
Bradley said.
Leg Fight Favorite | Long shot | Decimal odds [Fractional odds] Payout
1|Cody Gibson (-210) vs. Douglas Silva (+160) $ 1.60
2| Tiago dos Santos (-190) vs. Mike de la Torre (+150) $ 5.50
3| William Macario (-260) vs. Matt Dwyer (+180) $ 17.20
4| Jessica Andrade (-245) vs. Marion Reneau (+175) 5 49.05
5|Sean Strickland (-210) vs. Santiago Ponzinibbio (+160) $ 12913
6] luri Alcantara (-315) vs. Frankie Saenz (+235) $ 434.94
7|Rustam Khabilov (-300) vs. Adriano Martins (+220) $ 1,393.99
8|Cezar Ferreira (-265) vs. Sam Alvey (+185) $ 3,973.73
9] Edson Barboza (-175) vs. Michael Johnson (+135) $ 9,341.97
10] Antonio Silva (-240) vs. Frank Mir (+200) $28,028.91
Time to hedge your position:
Cezar Ferreira -200 odds
Edson Barboza -150 odds
Antonia Silva - 150 odds
All the brands that we analysed had Twitter as
their largest and most impactful channel
The offer was extended to anyone following the
company’s official Snapchat account, betfairoffcial
Betfair sent images that contained a custom URL,
giving users just a few seconds to read it and access
the offer, The first 500 customers to place a bet on the
URL benefited from Bettair's enhanced odds.