Forensic Accounting: Investigating Data Manipulation in AFL Matches

This report delves into the investigation of potential data manipulation within Australian Football League (AFL) matches, employing forensic accounting techniques to uncover discrepancies between original match scores and those found in a betting ringleader's file. The analysis leverages Microsoft Excel functions, particularly the 'IF' function, to compare data across a vast dataset spanning from 1897 to 2018. The methodology involves merging the original AFL data with the ringleader's data, using formulas to identify instances where scores have been altered. Findings reveal several instances of data manipulation, particularly from 1992 onwards, suggesting a correlation with betting activities and highlighting the potential for fraudulent practices within AFL matches. The report concludes that these findings substantiate allegations of betting fraud and emphasize the importance of forensic accounting in detecting such irregularities.

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

1
FORENSIC ACCOUNTING
Contents
Introduction:....................................................................................................................................2
Five examples of changes in data:...................................................................................................2
Process used to investigate the changes and manipulation in original data of AFL matches:........3
Observation of the findings:............................................................................................................8
References:......................................................................................................................................9

2
FORENSIC ACCOUNTING
Introduction:
Considering immense utility of spreadsheet in conducting analysis of different kind
including accounting and numeric value of different subjects, it would be extremely beneficial to
have significant amount of knowledge in using different functions available in excel spreadsheet.
The objective of this document is to use necessary functions of excel spreadsheet to find out
unauthorized changes made in original scores of Australian Football League (AFL) matches. The
effective use of spreadsheet would help in conducting the investigation launched against the
betting fraud in AFL.
Five examples of changes in data:
The investigation in AFL betting fraud is a massive responsibility on the shoulders of the
investigators. The investigators are expected to conduct a thorough evolution of all the matches
where the data, i.e. score to be precise, was changed as compared to the data from original file
containing the actual scores of different matches (Selwyn, Henderson & Chao, 2015).
Considering that the period of investigation is from AFL matches of 1897 to the AFL matches of
2018 season, it will be extremely beneficial for the team members to have knowledge and skills
required to use different functions in excel to identify the matches where data has been changed
in the file of betting ringleader compared to the data in the original file. Below given five such
examples where data has been changed in the betting ringleader file as compared to the data in
the original file containing the actual score of different matches since 1897 (Cao, Wang & Li,
2017).
Examples:
Date Team 1 Manipulated Original Team 2 Manipulated Original Venue

3
FORENSIC ACCOUNTING
Score Score Score Score
21-3-1992
(R1)
Hawthorn 21.15.141 24.11.155 Geelong 18.13.121 9.15.69 Waverley
Park
21-3-1992
(R1)
Brisbane
Bears
10.8.68 16.11.107 Carlton 13.14.92 12.10.82 Carrara
22-3-1992
(R1)
St Kilda 18.20.128 11.10.76 Essendon 17.9.111 21.20.146 Waverley
Park
22-3-1992
(R1)
Adelaide 12.15.87 14.15.99 Footscra
y
17.12.114 2.8.20 Football
Park
28-3-1992
(R2)
Collingwood 23.16.154 8.10.58 Brisbane
Bears
13.10.88 13.7.85 Victoria
Park
In the above the five examples of data changed in the laptop of the ring leader of betting
syndicate from the original date of these matches are given. The changed score of the matches
are highlighted in red whereas the original score of these matches are highlighted in yellow
(Locock, 2014).
Process used to investigate the changes and manipulation in original data of AFL matches:
Excel spreadsheet have number of functions that can be used to analyse numeric data and
other information. Efficient use of different functions in excel would help the users to analyse
significantly large quantum of data correctly at relatively less time. The accuracy of data analysis

4
FORENSIC ACCOUNTING
conducted in spreadsheet allows users to vouch for the authenticity and accuracy of information
collected subsequent to the data analysis in an excel file (Niazkar & Afzali, 2015).
In this case there were thousands of game that have been played over the period of almost 125
years in AFL history, i.e. since 1897 to 2018. In order to find out changes out of such large
quantum of data firstly, the original data file containing the original score of all these games and
the scores containing in the file of the betting ringleader have been merged. The screen shot
below will be helpful in understanding process used to merge the data of the two files (Abers, &
Hacker, 2016).
As can be seen in the screen shot of the excel file, firstly a column has been inserted in the right
of score column of ringleader file. In the inserted column the data of the original file containing
the score of the matches since 1857 have been inserted for team 1. Similarly the process has been
repeated to insert the original score of team 2 by inserting a Colum to the right of the right of
score column for team 2 in the ringleader file, clear from the screen shot below (Christensen &
Schneider, 2017).

5
FORENSIC ACCOUNTING
Immediately after the actual score column another column has been inserted as shown in the
screen shot below, i.e. G column.
In column G, the following formula has been used,
=IF(E3=F3,TRUE,FALSE)
“If” function is a very useful function to conduct logical analysis in excel file. By using if
function one can evaluate whether there is any logic to the data containing in an excel file. In
case of AFL matches, the investigation to unearth the truth behind the betting fraud in AFL
requires to identify examples of matches where data has been changed in the current file

6
FORENSIC ACCOUNTING
recovered from the betting ringleader compared to the data containing about the AFL matches in
the original file, exported from the official website of AFL (Barreto, 2015).
Using the formula in excel spreadsheet, IF(E3=F3,TRUE,FALSE), the score as per the file of the
ringleader with the score of the original file shall be compared for each of the matches taken
place in AFL between 1897 and 2018. Since, it is practically impossible to write the formula
individually in each row of column G for comparison of scores team 1 and in column J for scores
of team 2. Te copy and paste function of excel has been used. Thus, after typing the formula in
the first row of column G pertaining to the 1st match of 1897 season taken place on May 05,
1897, it has been copied and pasted to all the rows in column G and column J in the file ( Geiger,
Goos & Dole, 2015).
Consequent to using if function as mentioned above the G and J column respectively will show
“TRUE” for no changes in data between the ringleader file and the original file. However, if any
of the G and J column shows “FALSE”, it will represent that there have been changes made in
the data of the ringleader’s file. The screen shot below shows that in the matches below there has
been no changes in data as the G column shows TRUE for all the matches below (Barreto, 2015).

7
FORENSIC ACCOUNTING
However, as mentioned earlier that the G column and or column J will show “FALSE” if there
has been even slightest of changes in the data of matches from original data. The five examples
mentioned at the beginning of the document in which data has been changed in the ringleader file
compared to the original file, the screen shot below contains all these matches and more where
data has been changed (Christensen & Schneider, 2017).

8
FORENSIC ACCOUNTING
Observation of the findings:
Looking at the screenshot in the above it is clear that by using if function the five
examples have been easily identified where the data has been changed in the current file
compared to the original file containing the actual data of AFL matches taken place during 1897
to 2018.
Taking into consideration the above it is clear that the alleged betting in AFL matches are not
mere allegations. In fact there are significant amount of facts behind the allegations as number of
matches shown that the data has been changed in comparison to the original data of these
matches. Since 1992 the betting has been started as is clear from the above investigation as
before that year there was no changes in the data of AFL matches. In fact the betting is
continuing at present also as the screen shot provided below shows that even changes to the data
of AFL matches has been even in 2017 and beyond. Thus, there is significant truth behind the
betting fraud in AFL matches as clear from the findings of the investigation in the document.

9
FORENSIC ACCOUNTING
References:
Abers, G. A., & Hacker, B. R. (2016). A MATLAB toolbox and Excel workbook for calculating
the densities, seismic wave speeds, and major element composition of minerals and rocks
at pressure and temperature. Geochemistry, Geophysics, Geosystems, 17(2), 616-624.
Barreto, H. (2015). Why Excel?. The Journal of Economic Education, 46(3), 300-309.
Cao, Z., Wang, Y., & Li, D. (2017). Practical reliability analysis of slope stability by advanced
Monte Carlo simulations in a spreadsheet. In Probabilistic Approaches for Geotechnical
Site Characterization and Slope Stability Analysis (pp. 147-167). Springer, Berlin,
Heidelberg.
Christensen, D., & Schneider, P. (2017). Allocating service department costs with excel: Excel's
iterative calculation option makes it easier to use the reciprocal method to allocate service
department costs. Strategic Finance, 98(11), 50-56.
Geiger, V., Goos, M., & Dole, S. (2015). The role of digital technologies in numeracy teaching
and learning. International Journal of Science and Mathematics Education, 13(5), 1115-
1137.
Locock, A. J. (2014). An Excel spreadsheet to classify chemical analyses of amphiboles
following the IMA 2012 recommendations. Computers & Geosciences, 62, 1-11. Locock,
A. J. (2014). An Excel spreadsheet to classify chemical analyses of amphiboles following
the IMA 2012 recommendations. Computers & Geosciences, 62, 1-11.

10
FORENSIC ACCOUNTING
Niazkar, M., & Afzali, S. H. (2015). Application of Excel spreadsheet in engineering education.
In Proceeding of the first international and fourth national conference on engineering
education, Shiraz University, Shiraz (pp. 10-12).
Selwyn, N., Henderson, M., & Chao, S. H. (2015). Exploring the role of digital data in
contemporary schools and schooling—‘200,000 lines in an Excel spreadsheet’. British
Educational Research Journal, 41(5), 767-781.