Horse Racing Simulation System Presented By Ting Hin Chau Supervised By Professor Michael R. Lyu

Horse Racing Simulation System

Presented By Ting Hin ChauSupervised By Professor Michael R. Lyu

April 2004

Agenda Objectives of Project Background of Horse Racing Major Business Functions of Objects System Design Simulation Algorithm Conclusion Q & A

Objectives

To demonstrate CORBA implementation

To demonstrate horse racing simulation

Objectives / Background / Business Functions / System Design / Simulation Algorithm

Background of Horse Racing


Jockey Club

Stable

Gambler


Inefficient Procedures Race Registration: Paper Work

Betting: Off-course betting branches



Difficult Result Prediction

Personal Judgement


Business Functions


Jockey Club Formulating Horse Racing

Schedule Schedule Query by Stable Processing Horse Registration for a

Race by Stable

Business Functions

Jockey Club Race Query by Gamblers Accepting Bets from Gamblers Calculating Odds (Appendix 1) Running Races Dividend Payout


Business Functions

Stable Horse Query by Gamblers

Horse Registration for a Race


Business Functions

Gambler Depositing Money to Betting

Account

Placing Bets


System Design


Interaction

Object Request Broker (VisiBroker for Java 4.0)

Database (Oracle 8i)

Server Object 1

Server Object N

Client Object 1

Client Object N

Java Applet

System Design

Object Request Broker VisiBroker for Java 4.0 Service Lookup Object Instantiation Connection Setup between Client

and Server Objects


System Design

Object Request Broker


System Design

Server Objects Interfaces defined in CORBA/IDL

interface Buyer { attribute unsigned longBuyerID;attribute stringBuyerPassword;attribute stringBuyerName;attribute floatBalance;attribute stringAccountNumber;exception NotEnoughMoneyInAccount { };

void deposit(in float amount);void withdraw(in unsigned long amount)

raises(NotEnoughMoneyInAccount); void edit(in string buyerName, in string buyerPassword, in string accountNumber);

};


System Design

CORBA/IDL to Java Mapping

IDL Java

module package

interface interface

operation method

attribute method pair

exception exception


System Design

idl2java Interface file Helper file Holder file Stub file POA file


System Design

Server Objects Buyer BuyerProcessor Stable StableProcessor Race


System Design

Client GUI RaceAdminClient StableClient BuyerClient


System Design

Client GUI RaceAdminClient


System Design

Client GUI StableClient


System Design

Client GUI BuyerClient


System Design

Database Server Oracle 8i Persistent storage of data Maintaining data integrity E-R diagram (Appendix 2)


Simulation Algorithm


Monte Carlo Simulation Simulation with a built-in random

process

Different possible outcomes


Steps of Simulation (Appendix 3)1. Data Input Gather data on historical ranks of a

horse Transform these ranks to a value

R/N, which is rank/number of horses in the race



Steps of Simulation2. Distribution Construction Form frequency distribution Form probability distribution Form cumulative probability

distribution



Steps of Simulation

The distribution of Rank of a horse

00.020.040.060.080.1

0.120.140.16

0 5 10 15

Rank X

P(X

= x

)

The cumulative distribution of a horse

0

0.2

0.4

0.6

0.8

1

0 2 4 6 8 10 12 14

Rank X

F(x)

= P

(X

<=

x)



Steps of Simulation3. Draw a sample from distribution Generate a random number N from

0 to 1 N refers to P(X <= x), where X is R/N



Steps of Simulation

The relationship between x, F(x) and G(F(x))

0

0.2

0.4

0.6

0.8

1

0 2 4 6 8 10 12 14

G(F(x)) = x

F(x)

= P

(X

<=

x)



Steps of Simulation4. Compare R/N across horses Sort the R/N values of the horses in

a race A horse with a smaller R/N beats

out a horse with a higher R/N



Assumptions of Simulation Independent distribution of R/N Factors including location of

racecourse, lane, and jockey are insignificant

Data from the 10 most recent races are used


Conclusion

CORBA Language independent Different platforms ORB expensive


Conclusion

Simulation Mimics the “random” factor in horse

racing Choice of size of distribution is hard

to determine Error of prediction can be estimated


Appendix 1

Calculation of Odds1. Win Odds dw = bi / bw

2. Place Odds dw1 = (bi - bw1 - bw2 - bw3) /( 3 * bw1) + 1


Appendix 2

Stable_t

Passw

ordSID

Status

Horse_t

HID

Weig

ht

Birth

day

Status

Gam

bler_t

Passw

ordG

ID

Status

Gam

blerN

ame

Acc

ountN

um

BetA

ccountB

al

Race_t

HL

ane

RaceE

ventNum

ber

Race

Date

TxnS

tatus

Horse

Rank

Joins

Owns

Bet_t

BetT

ype

BetA

mount

Gambler-bet

Race-bet


Appendix 3

Simulation Calculation

Race R N R/N R N R/N R N R/N R N R/N1 2 8 0.25 4 10 0.4 3 10 0.3 5 10 0.52 3 10 0.3 6 12 0.5 2 8 0.25 6 11 0.545453 1 14 0.07143 5 10 0.5 3 12 0.25 6 12 0.54 1 9 0.11111 4 8 0.5 4 11 0.36364 8 14 0.571435 4 14 0.28571 4 10 0.4 3 9 0.33333 12 12 16 3 12 0.25 7 14 0.5 1 7 0.14286 13 14 0.928577 2 8 0.25 8 12 0.66667 1 8 0.125 8 14 0.571438 1 10 0.1 8 14 0.57143 5 12 0.41667 6 10 0.69 1 10 0.1 6 10 0.6 4 10 0.4 N/A N/A 0.5355

10 2 8 0.25 5 8 0.625 N/A N/A 0.4805 N/A N/A 0.5010

Horse 1 Horse 2 Horse 3 Horse 4


Appendix 3

Simulation CalculationCumulative Probability (R/N)

Horse 1R/N

Horse 2R/N

Horse 3R/N

Horse 4R/N

0 0 0 0 00.1 0.07143 0.4 0.125 0.50.2 0.1 0.4 0.14286 0.50.3 0.1 0.5 0.25 0.5010.4 0.11111 0.5 0.25 0.53550.5 0.25 0.5 0.3 0.545460.6 0.25 0.5 0.33333 0.571430.7 0.25 0.57143 0.36364 0.571430.8 0.25 0.6 0.4 0.60.9 0.28571 0.625 0.41667 0.92857

1 0.3 0.66667 0.4805 1


Appendix 3

Simulation Calculation

Random Number

Horse 1 0.537978366Horse 2 0.210962962Horse 3 0.022299918Horse 3 0.492061261


Appendix 3

Simulation Calculation Two points on the cumulative distribution

(x1, y1) and (x2, y2), for instance, for horse 1, they correspond to (0.25, 0.5) and (0.25, 0.6), will be used to calculate the final score of a horse by linear equation , based on the random number generated.


Appendix 3

Simulation Calculation For horse 1, point 1 (x1, y1) is (0.4, 0.2)

and point 2 (x2, y2) is (0.5, 03) R/N of horse 1

= (rand1-y1)*((x2-x1)/(y2-y1)) + x1= (0.5379783655654367 – 0.2)* (0.25 – 0.25)/(0.6-0.5) + 0.25= 0.25


Appendix 3


and point 2 (x2, y2) is (0.5, 0.3). R/N of horse 2

= (rand2-y1)*((x2-x1)/(y2-y1)) + x1= (0.21096296234313094 – 0.2)* (0.5 – 0.4)/(0.3-0.2) + 0.4= 0.410962962


Appendix 3

Simulation Calculation For horse 3, point 1 (x1, y1) is (0, 0) and

point 2 (x2, y2) is (0.125, 0.1). R/N of horse 3

= (rand2-y1)*((x2-x1)/(y2-y1)) + x1= (0.02229991816731558 – 0)* (0.125 – 0)/(0.1-0) + 0= 0.027874898


Appendix 3


and point 2 (x2, y2) is (0.545455, 0.5). R/N of horse 3

= (rand2-y1)*((x2-x1)/(y2-y1)) + x1= (0.4920612612595172 – 0.4) * (0.545455 – 0.5355)/(0.5-0.4) + 0.5355= 0.544664699


Horse Racing Simulation System Presented By Ting Hin Chau Supervised By Professor Michael R. Lyu

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