ACC30003 Forensic Accounting S2 2018: AFL Betting Fraud Investigation

This report details an investigation into AFL betting fraud, conducted as part of a forensic accounting assignment. The investigation involved analyzing data from the laptop of an accused betting ringleader and comparing it to original AFL data from 1897 to 2018. The process included collecting and merging data, adding columns for comparison in Excel, and using sorting, filtering, and “IF” functions to identify discrepancies. Five specific examples of data changes are highlighted, demonstrating alterations to game scores. The findings confirm the presence of betting-related data manipulation within the AFL, dating back to 1992 and continuing through recent seasons. The report emphasizes the distinction between betting and match-fixing, cautioning against assuming one implies the other. This document is available on Desklib, where students can find various study resources.

Running head: FORENSIC ACCOUNTING
Forensic Accounting
Name of the Student:
Name of the University:
Authors Note:

1
FORENSIC ACCOUNTING
Contents
Introduction:....................................................................................................................................2
Examples of games where data have been changed:.......................................................................2
Process used to identify the examples:............................................................................................4
Investigation findings and observation:...........................................................................................7
References:......................................................................................................................................9

2
FORENSIC ACCOUNTING
Introduction:
A very popular sporting event in Australia, Australian Football League, hereinafter to be
referred to as AFL in this document, has entertained not only the people of Australia but also
people from other parts of the globe who has followed the annual sporting league due to its
intense competitive structure. However, ever since match fixing scandals of numerous matches
in the league suffered there has been considerable downfall in the viewership of the tournament.
A betting ringleader has been arrested recently on charge of involvement with changes in data of
games. A detailed investigation shall be conducted on the data recovered from the laptop of the
betting ringleader for the games played since 1897 till as recent as 2018 (Geiger, Goos and Dole,
2015). A comparison with the original data of these games with the data contained in the laptop
of the betting ringleader would help in understanding the changes made to the data for betting
purposes and the roots of betting in AFL. Use of excel shall be made extensive to conduct data
analysis on the files containing the data related to the games played during the period of 1897 to
2018.
Examples of games where data have been changed:
The document has asked to mention five such examples where it can be proved that data
has been changed in the file of betting master mind in comparison to the original data about the
games played during the above period. Thus, despite identifying number of such games where
the data has been changed only five examples have been mentioned here (Charpentier, 2018).
Changed
data
Original
Data
Changed
data
Original
Data
Date Round Team 1 Score Score Team 2 Score Score

3
FORENSIC ACCOUNTING
3-7-2016 R15 Melbourne 15.8.98 18.12.12
0
Adelaide 18.12.120 11.17.83
8-6-2017 R12 Sydney 12.16.88 14.14.98 Western
Bulldogs
6.6.42 17.7.109
10-6-2017 R12 Hawthorn 12.7.79 9.7.61 Gold
Coast
13.17.95 11.12.78
10-6-2017 R12 Brisbane
Lions
18.13.121 16.6.102 Fremantle 9.10.64 11.17.83
10-6-2017 R12 Essendon 19.17.131 10.17.77 Port
Adelaide
8.13.61 16.9.105
The above table contains five such examples where the data has been changed in the file of the
arrested person in comparison to the original data about these games. The data for the original
games have been collected from the official website of AFL. The highlighted scores of team 1
and team 2 in these respective games clearly show distinction between the original score as
maintained in the official website of AFL and the scores found in the file maintained in the
laptop of the betting ringleader (Long, 2018).
The screen shots below show the above finding in excel spreadsheet:

4
FORENSIC ACCOUNTING
The above screen shot shows the differences between scores maintained by the ringleader and
the original score for team 1 in the above matches (Moriarty, Held and Richardson, 2018).
The above screen shot shows the differences between scores maintained by the ringleader and
the original score for team 2 in the above matches.
Process used to identify the examples:
Collection of data: Firstly, the data from the official website of AFL was collected for all
the games played from 1897 to 2018 in chronological order. The file from the laptop of the
betting ringleader was also recovered (Harkins, 2016).
Merging of data: The data, i.e. scores of original file was merged with the scores of the file
recovered from the arrested ringleader’s laptop. The image below taken from excel will be
helpful in understanding the process of merging data.

5
FORENSIC ACCOUNTING
Additional columns: Additional columns have been added immediately beside the column
containing the scores of team 1 and team 2 in the file maintained by the betting ring leader. In
these columns the original scores of these games have been inserted. The yellow columns
highlighted in the screen shot below shows the additional columns inserted for conducting the
investigation (Conant, 2018).
Use of sorting and filtering: Sorting and filtering option in spreadsheet enables the users to sort
data on certain pre-identified basis such as dates, rounds, team 1, scores, team 2 and venues.
Using the function the data can be filtered also to ensure only the data required for investigation
is taken as is required by the investigators.

6
FORENSIC ACCOUNTING
Use of “IF” function: A logical function helps in identifying any particular assertion on the
document based on the logic created in the formula while using “IF” function. Screen shots
below shows how the formula has been used in the excel sheet in conducting the investigation in
this document to identify the games where data have been changed in the files recovered from
the betting ring leader (Gardener, 2017).
True and False login in “IF” function: By using the true and false logic in the “IF” function it
was quite easy to identify the changes in the data made in the excel sheet of the arrested betting

7
FORENSIC ACCOUNTING
ring leaders in comparison to the original data of these games. The” TRUE” sign indicates no
changes in data whereas “FALSE” sing indicates changes in the data. The screen shots below
contain the results of five such games where data have been changed (Harkins, 2016).
Investigation findings and observation:
Subsequent to the detailed investigation on the data found from the laptop of the arrested
betting ring leader, it can be concluded that there have been number of games where data have
been changed for betting purposes. Thus, the risk of betting fraud is valid and justified. It is
important to understand however, that betting is completely different from match fixing. Thus, it
should never be assumed that presence of proof to indicate huge betting syndicate is anyway an
indicator of existence of match fixing (Nelson, 2016).

8
FORENSIC ACCOUNTING
It is also observed that betting is very much a reality in the AFL since last 25 years. In 1992, the
first changes in data of games has been identified in the above investigation as can be pointed out
in the screen shot below.
The betting is present in the most recently concluded season of AFL, clearly identified in the
screen shot below:

9
FORENSIC ACCOUNTING
References:
Charpentier, A., 2018. Rationality, and MS Excel (and other calculators). Machine
Learning, 14, p.05. Available at: https://freakonometrics.hypotheses.org/5171 [Accessed on 7
October 2018]
Conant, D.D., 2018. Examining critical and near-critical paths: an Excel-based classroom
exercise. Journal of Education for Business, 93(6), pp.285-291.
Gardener, M., 2017. Statistics for ecologists using R and Excel: Data collection, exploration,
analysis and presentation. Pelagic Publishing Ltd.
Geiger, V., Goos, M. and Dole, S., 2015. The role of digital technologies in numeracy teaching
and learning. International Journal of Science and Mathematics Education, 13(5), pp.1115-1137.
Harkins, S., 2016. Build your Excel skills with these 10 power tips.
Long, C., 2018. Access: USE EXCEL WITH A WRAPPER FUNCTION. Strategic
Finance, 99(11), pp.60-61. Available at:
https://search.proquest.com/openview/3347f0f7f4d5ecd6df7f3c329c04b14f/1?pq-
origsite=gscholar&cbl=48426 [Accessed on 7 October 2018]
Moriarty, B., Held, B. and Richardson, T., 2018. Microsoft Excel Functions and Formulas.
Stylus Publishing, LLC.
Nelson, J.B., 2016. A robust function to return the cumulative density of non-central F
distributions in Microsoft Office Excel. Psicologica: International Journal of Methodology and
Experimental Psychology, 37(1), pp.61-83.

10
FORENSIC ACCOUNTING