Jean Baudrillard on the transeconomics of speculation: "A game and nothing but a game, with floating and arbitrary rules: a game of catastrophe."
Sports Analytics took off in 2014 with numerous entities being established or consolidated...
... unfortunately, none of these bodies are looking at the key data.
Consequently, they offer no information-alpha but merely self-fulfilling mechanisms in a shared non-differentiated idiocy of mission.
This is about to change with the launch of a new business of which we are a part.
Matchfixing Analytics will address corruption and matchfixing in football utilising bespoke analytics and forensics together with enhanced modelling and unique holistics.
All markets are functions of economic and psychological mechanisms but this formal construct is entirely delegitimised by the corrosive roles of corruption and insider trading, particularly in lightly regulated sectors like football.
The resultant hologram of hyperreality is pure Neo-Bayesian with chaotic statistical disorder.
Matchfixing Analytics will offer clients a robust edge in the corrupted marketplace of global football as clients want new insights, holistic modelling and clever data (not Big Data).
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Jean Baudrillard: "The revolution of our time is the uncertainty revolution. We are not ready to accept this. Paradoxically, however, we attempt to escape from uncertainty by relying even more on information and communication systems, so merely aggravating the uncertainty itself."
Big Data is the big buzz but only performs in two areas in relation to markets and integrity - High Frequency Trading (HFT) where swift analysis yields arbitrage edge and surveillance/ sousveillance/ hacking where one wants maximal information to mine.
Aside from these areas, Big Data is Big Noise.
The first intrusion of Big Data into sport came with Billy Beane III and his use of sabermetrics in the valuation of baseball players. Unfortunately, sabermetrics in this basic form only applies to sports that are able to be broken down into discrete time segments eg cricket, NFL and baseball but fails miserably when utilised in games with interactive flow like football or in sports that are corrupt.
Unfortunately, this lesson is yet to be learnt and Arsenal paid £2.165m for US-based StatDNA while Manchester City established MCFC Analytics, both of which collect massive (and largely irrelevant) data which attempt to quantify the flux of football while ignoring the considerable inputs that undermine the match outcome and the integrity of the sport (although it should be stated that the Arsenal operation is markedly more professional than the Mancunian one!).
Roy Hodgson's England also utilised amateurish analytics prior to producing the nation's worst ever World Cup performance and only group stage exit in Brazil 2014.
Matchfixing Analytics will incorporate corruption forensics into match analytic processes protecting clubs against inproprietaries taken against their interests.
Matchfixing has reached a stage of development where there are frequently two or more insider attempts at manipulating the outcome of a match. The hyperreality might only become clear once the match is in progress. It is of consequence to participants and all associated with the event for the state of real-time corruptions to be assessed via analyses of the actions and psychologies of potentially corrupt officials and players and the related impacts on the markets of the criminalities at play.
Matchfixing Analytics will address such inputs at speed to benefit of clubs (as well as the efficiency of the markets).
A parallel might be drawn with the likes of Sportradar, a company that claims to provide syndicated sports content, betting related data and fraud detection.
In reality, Sportradar share macro data around market makers (and tipsters) that offers no competitive edge due to its generality and lack of specificity. Everybody is plugging the same data into the same software, thinking they are creating unique insight when, in fact, off-the-shelf solutions are self-fulfilling and simply reinforce the mechanisms at play.
Matchfixing Analytics will operate 3 layers deeper than competitors in market information, access, evaluation and the detection of market abuses and matchfixing.
The vast majority of institutional bodies in world football have their own private and hidden agendas. Frequently, such agendas impact upon the integrity of the game.
Institutional corruption analyses are critical for clubs to punch above their weight and for miscreants to be outed.
Matchfixing Analytics will transform the perceptions of corruptions of power lobbies at FIFA, UEFA, national associations and leagues, the betting monitoring bodies, IFAB and bodies representing match officials.
As football has morphed into a first tier global market with regard to the sheer volume traded, it has become increasingly necessary for all interested parties to be aware of the implications of the market structure.
We model market holistics.
Matchfixing Analytics will incorporate intermarket analyses, global market alliances, dark pool and underground market activities, proxy trading, the inputs of criminalised enterprises and syndicates, strategies to disguise volume and instantaneous global information flow into a holographic whole of market transparency.
Iain Martin of the Financial Times has promoted Peter Moores' Law with regard to Big Data (named after the hapless England cricket coach). This law states: "If you collect enough information about what is happening then everything might somehow be alright."
Application of Big Data by England in the ICC Cricket World Cup 2015 resulted in dire performances and a defeat to Bangladesh that ensured elimination at the group stage.
Big Data could not highlight malicious input from rogue individuals.
Big Data also played a nefarious role in the 2007/08 Great Recession.
"Awash with data, Value at Risk metrics and toxic products stamped with comforting ratings, most [executives] did not see the large iceberg ahead. But what is curious is that, after this disaster, the Big Data ship simply steamed ahead unimpeded."
Matchfixing Analytics will extract the key information from Big Data and transform the risk strategies of clients.
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Big Data (like statistics and mathematics) are only valid in restricted areas of marketplaces which are dominated by corruption. Such corruption might be modelled similarly to cosmological research - we have expanding universes of corruption in a multiversal whole, where quantum leaps in reality occur undermining any mathematical or economic robustness; a state of evolutionary flux.
Key Data not Big Data is the Core to Real-Time Modelling of Matchfixing, Markets and Corruption.
Thomas Piketty: "The discipline of economics has yet to get over its childish passion for mathematics... income, capital, economic growth rate, the rate of return on capital are abstract concepts and are theoretical constructs rather than mathematical certainties."
Matchfixing Analytics will be launched in April.
If you wish to avoid the avenue of apprehension or the doorway to disaster then consider a consultancy of anti-corruption.
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