Tricks of the trade – Data Driven with Buzzing Paul

Welcome to the fifth edition of Tricks of the trade! This week I caught up with the data-driven Buzzing Paul to get all the details on the various metrics he uses to help assess player performances on the pitch and on Football Index. First though, a bit of background on the core tools at Paul’s disposal to stop me asking stupid questions!

Possessions Per Game (PPG) is defined as a passage of individual play that ends in a pass, cross, shot, clearance, foul won, unsuccessful touch or dispossession. Actions Per 100 Possession (P100) helps level the playing field in terms of the number of possessions and helps recognise those who are more efficient in possession. A deeper explanation can be read here.

He also likes to analyse probabilities of goals using expected goals (xG) which is defined as the number of goals a team or player would be expected to score based on the quality and quantity of shots taken. It takes into account the location of the shot and more sophisticated factors like the body part used to take the shot, defensive positioning, attack speed and where the first possession of the attack started. To find out more about this check it out here.

The final resource of Paul’s that I would like to introduce is “the buzz” - a blog series run by Paul which he is using to document his portfolio and trading activity throughout the year. The idea is to use multiple (10) funds based on different player characteristics to try and outperform the market, which he has measured using three benchmarks, namely the top 10 players on Football Index. Details of all the funds and players within them can be found here (scroll towards the bottom half of the page)

So now you have a bit of background on some of Paul’s work, let's get into the questions!

As ever let us kick off with a bit about you, how long have you been on the Index? How profitable has it been for you?

Hello, thanks for inviting me onto this edition of Tricks of The Trade.

Paul: I first discovered the Index at the start of 2016. It caught my attention immediately as a new, innovative and disruptive gambling product. After a bit of research, the lack of liquidity prevented me depositing.

I rediscovered FI via some guerrilla Twitter marketing towards the end of 2017; shortly before the extension of Top 200 and the launch of mass IPOs. My first purchase was 28th October 2017 and I first tweeted in early November of the same year.

My lifetime RoI based on selling value is 28%. 16% of this has been achieved through dividends. Which sounds great, until you compare to the any tracker benchmark over the same time period.

To add further context, I’ve deposited twice into the Index and am yet to withdraw. After my first deposit and between Oct-17 and Feb-19, I achieved an RoI of 115%. Since redepositing and majorly reshuffling my portfolio in Feb-19 (as documented in my aforementioned “Buzz” blog series) my RoI sits at 2.36%.

A sidebar I think could be useful for a lot of traders at some point. You recently took some time off Football Index for travelling, how did this affect your Index portfolio? Have you noticed any big changes since being back?

Paul: My partner and I spent six months travelling in south east Asia and beyond between Sep-18 and Feb-19. You can hear more from her as the Control Group benchmark fund ‘manager’ in my blog series.

Trading was limited to a two-week period when we returned to the UK for weddings. This coincided with the In-Play dividends extension announcement. In hindsight this was fortuitous timing. Once we had flown to Thailand, I proceeded to get my fingers burned by holding Goalkeepers for too long after Clean Sheet dividends were introduced.

In general, I target long term holds so the decision to hold while travelling was fairly straight-forward. Fortunately, my portfolio experienced moderate growth over the period, but (again) this paled into comparison vs. the market as a whole.

Since coming back I have noticed three main trends and topics of conversation amongst the #FICommunity.

1. Perceived market value in players under 21

2. What impact the share split will have at various price points within the market

3. How and how much FI should change the dividend weighting

My thoughts an each of these points could become entire Q&As in their own right. But quickly:

1. Traders need to factor in discounted future dividend earnings when evaluating price

2. Mathematically a uniform share split should have a uniform impact across the market, psychological I expect the benefit to be felt the most at the top

3. I’d expect a marginal increase in dividends with a shift in weighting away from media dividends

What was reassuring to discover on my return was:

  • I still wholeheartedly believe in FI as a product and think there are plenty of deposits left before market capitalisation is reached.
  • Player value should still be derived from lifetime incremental discounted cash flows (I attempt a tired explanation of this toward the end of #FIGCast Episode 71).
  • My unique ranking methodology continues to give me an edge vs. the market (you dear readers).

As outlined, you use a lot of unorthodox and interesting methods of measuring player performance, what made you start to do this originally?

Paul: I spent years as a recreational sports gambler looking for an edge against the bookies. After mixed results, I concluded that the only edge I could find was in swimming (I was half decent back in the day); and this discovery was rewarded with a number of my accounts being closed down.

On re-discovering the Index, I knew the way to long term profitability would be to find an edge against the market. In Oct-17, this meant looking at data from the previous season to model who would score highest based on the performance matrix. I combined base, goals scored and assists data to create a unique performance ranking algorithm that allowed me to prioritise my first FI purchases.

Since the growth in popularity of non-native FI matchday data platforms like Edge, IndexGain and Noir4x’s email, I’ve had to sharpen my edge. I have extended my analysis to look at possession; xG & xA; and leagues where Matchday data does not exist.

I would encourage readers to check out each of these data providers and also to consider what their edge is versus the market.

How helpful have these measures been? Do you use them often to determine trades? And do you think it can be used to predict someone that is “due” a good PB score before it actually happens?

My RoI speaks for itself, but again, due to the growth across the Index I’m sure I have under performed the Top10 benchmark over my investment period.  As we reach market capitalisation, I would expect these measures to outperform the majority of tracker benchmarks.

Personally, I think there is some value in the utility I derive from research and digging into the stats. I also enjoy helping traders follow my thought process and logic in the hope that their trades will be better informed by my strategies and concepts.

Each one of my trades is determined using 3 main data points. Price, Matchday ranking and P100 (see top) ranking. I use these alongside other factors such as age, transfer rumours and xG/xA figures to prioritise my purchases.

Each one of us has a finite investment pot. To maximise this, and to prioritise decision making, I highly recommend that readers create their own ranking system. Once player purchases have been prioritised, before entering a trade, I recommend readers have a clear entry and exit point in mind.

I mentioned previously that the price of a future should be a function of lifetime incremental discounted cash flows. In this case, incremental means future cash flows (dividends). The ranking algorithm I produce ignores historic dividends and to some extent historic matchday scores. It uses historical statistics to calculate exactly what you mention in the question; “someone who is ‘due’ a good matchday score. This is one of the fundamental concepts of my trading strategy, and hopefully gives me an edge against the market.

Many have predicted an increase in In-Play dividends as a result of the share split. What do you think about this? And if it happened, the xG statistics could become pretty useful, couldn’t they?

As aforementioned, I expect a marginal increase in dividends with a shift in weighting away from media dividends. By proxy, this will be met with a shift toward Matchday & In-Play Dividends.

My experience of market behaviour on the back of recent announcements is that money will flow to the obvious, premium-priced candidates impacted. xG/ xA statistics  (Reminder: xG is expected goals and xA is expected assists) can be used to identify less obvious players who are under performing their xG. It can also be used to exclude players who are over-performing their xG/ xA expectation.

Now is probably a good time to discuss the limitations of xG/ xA. Their values are derived by accumulating shot data across all players. If you have an above-average finisher (e.g. Sergio Aguero) you would expect him to exceed expectations as he is an above-average goalscorer.

If you are using xG/ xA to make investment decisions ensure you have an appropriate sample size. Divock Origi performs particularly well for xG90, but has only 248 EPL minutes this season.

In a market that seems to have lost focus on performance and even dividends to some extent, have you had to adapt your strategy and the emphasis on statistics?

Whilst I agree to an extent that the market has lost some focus on future performance dividends, there are also some recent examples where the market has reacted positively to matchday scores.

Jonathan Tah has increased by > 100% since Peter Bosz’s move to Leverkusen on the back of matchday scores of 254 and 233.

Similarly, this past weekend, Youcef Atal increased by 16% on the back of a 216-point matchday score.

There is also an argument that Bruno Fernandes' price is correlated to his recent matchday performances at Sporting. But I’ll leave readers to dig into his underlying stats and assess his value autonomously.

Clearly, there is hope for my rational and long-term approach yet. But I have also had to adapt my strategy slightly. One of the funds in the ‘Buzz’ series is a Wonderkids fund. This fund uses my ranking algorithm to target irregular matchday dividends from players under 23 who are getting regularly starting minutes in matchday eligible leagues. Each future in this fund was priced < £2.50 at time of purchase.

I also believe strongly that, in order to refocus the market toward future performance dividends, I have an obligation to maintain my current strategy. I want to be a part of the solution, not the perceived problem.

The buzz is a particularly interesting challenge you’ve set yourself. Out of all the funds, which would you say was your favourite to set up?

Paul: My biggest edge lies where historical data doesn’t exist in non-native platforms such as Edge, IndexGain and Noir4x dataset.

I have an ‘Alien’ fund that uses my unique ranking algorithm to highlight the best performing matchday players in the Eredivise, Liga NOS and Russian Premier League. It also looks at second division players likely to be promoted into eligible leagues.

It has been the best performing fund since its inception 4 weeks ago and was the most fun to research.

How much discipline does a strategy like this take? Many traders struggle to take profits because of the “pretty green” - is it hard to sell at your predetermined levels sometimes? (for example, I see some funds state 50% profit exit point)

Paul: My biggest weakness as a trader is selling. Knowing when the right time or what the right price is, in a growing market is nigh-on impossible.

You are right, I look to exit trades at (25)% loss or 50% profit. In the one instance where a player has exceeded the 50% profit point since Feb-19, I took the decision to hold.

Psychology hugely influences the Football Index market. To the extent where I think thinking rationally and long term gives you an edge against the ‘gamblers’ within the market. I couldn’t recommend this article by Fantasy Football Scout enough. Discipline, level-headedness and rationality are key to long-term, sustainable success on the platform. But I am as susceptible to cognitive biases described in the attached article as most of you are.

How much do you think this diversification has helped your profitability? Have you found in the early stages that gains have mainly cancelled out losses or do you think it has been more profitable than you would have been just going at a more “traditional” portfolio set up?

Paul: Diversification is key to my investment strategy, and should be a tool utilised by all readers as a ‘security blanket’ in times of market volatility. Diversification can be achieved in many ways. You can diversify your portfolio by dividends targeted; age; price; league; position; length of hold.

The level of diversification in your portfolio will depend on many factors. The most important of which is time availability. The less time you have to monitor the index on daily basis, the more diversified your portfolio should be. My portfolio current sits at 91 players. I think that this is too much and I will be looking to reduce down to 50 by the end of this season.

Another key thing that I have learnt is that you should always hold a percentage of your portfolio as cash. There have been too many occasions where I have seen big opportunities but been unable to execute a trade due to insufficient cash.

When do you plan to close or restructure these funds? Will you be holding through summer or do you expect too many of them would drop over that time?

I review each fund monthly and will review each fund in the last few weeks of this season. Historically my portfolio has performed well during the summer as I tend to focus on players outside the EPL.

There are some players who I will need to keep a close eye on. Either those whose future seems clear but uncertainty remains about media potential prior to a move, such as Eden Hazard. Or those, where a move to a strong matchday dividend club is already factored into their price, such as Hakim Ziyech.

As general rules I never invest in players based on unsubstantiated transfer rumours. Also, I will sell in 90% of some circumstances, once a non-Premier League transfer has been confirmed.

That is all for this week! Big thanks to Paul for coming on and opening our eyes to these alternative metrics! 

See you next week! 

In case you missed the previous editions of Tricks of the trade, check them out below! 

Edition one with Big Don and his 1000+ player portfolio, catch it here

Edition two with dividend powerhouse Stamford is here

Edition three with Sunday to Friday trader Pierre is here

Edition four with transfer trading Ryan Pearce is here

If you’re new to Football Index and want to continue to learn the ropes, check out my free guide here!

I hope this article has been as interesting and useful to you as it was for me. We’ll be back next week with another top traders story!

got some thoughts on this article? Why not tweet them to us at @footballindexLM or @FootballAna

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