Player Projections & How to Predict the Future
Applying some basic business valuation steps to projecting player performance
First, thanks for your patience. There were no Absolute Unit entries last week because I was blessed with the birth of our second child. Everyone is doing well. I’ll try to get this up and running again, though it may be merely a weekly post for just a little while longer before we’re fully ramped up. There is much to cover still, and the best parts of this treatise remain.
Where were we?
In the last post, I gave an overview of the present value and net present value principles underlying how investors and businesses estimate the value of assets and projects, how these calculations while full of assumptions and incomplete data are useful in that they distill down all of the information (including all of the uncertainty) into an easy to interpret metric to aid a “go” or “no-go” decision. The idea is that a GM of a soccer operations department should be using an analogous framework for player recruitment but with “expected marginal goal difference” as the key metric rather than net present value (in dollars).
If the present value calculation is fundamentally, 1) the projection of estimated future cash flows, which are then 2) discounted using the appropriate rate given the risk and opportunity cost, then you could summarize it another way as:
Valuing something (which is also calculating the price of something) involves:
Predicting the future, then
Benchmarking the future
These are also two activities that are integral to putting together a well-functioning soccer team, especially when economic resources are constrained, so we’ll want to learn as much as we can about both of these analogous corporate finance concepts before we apply them to football.
In this post, we’re going to detail out the five basic steps of projecting future cash flows (predicting the future), so that we can then map each of these steps one for one to soccer player recruitment. If last week’s post showed how you can use a discounted cash flow approach to value the price of an individual asset, and also how to apply net present value to determine the value of a given project that a manager can choose to undertake or not, then in this post, we’ll apply the five basic steps of projecting future cash flows to another example that plays by the same rules: “business valuation.”
If we represent a company and are looking to acquire another company, we need to know the right price to pay their shareholders to acquire it. The question that matters to us is: what is the target company’s value? And, the answer is the sum of the company’s estimated future cash flows, discounted to the present based on the appropriate required rate of return. This is not entirely it, but it’s mostly this.
Again, I’d ask that you keep a soccer recruitment team in your peripheral vision as we explore this projection process in the financial world. How does one predict the future?
Overall blueprint for projecting future cash flows
1) Accounting Records
Obtain the target company’s existing relevant and reliable historical data/ financial results if available (e.g. audited financial statements prepared in accordance with generally accepted accounting principles). Most companies have to prepare financial statements that follow standard rules. These financial statements serve as the most reliable record of the company’s historical performance and its current assets and liabilities. We care about the historical performance because we need to project the target company’s future performance, and so the “Income statement” often referred to as the “profit and loss” or “P&L” is as good a place as any to start. Relax. You don’t need to know the different financial statements here.
I’m generalizing in a way that could get me in trouble, but basically the record of the historical financial performance is the compilation of all of the “transactions” the company has undertaken in its quest for generating profits for its shareholders. The company might sell products and services to its customers and demand payment via customer invoices. They might collect payment from customers in the form of wire transfers or lock box payments. They might procure products and services from suppliers and vendors for the purpose of fulfilling promises to their customers, and they might similarly be invoiced by these vendors and make payments themselves. They might pay their employees with direct deposits and evidence these with payroll slips. All of these transactions and more have accounting documents (e.g. an invoice) attached which are then journalized in the company’s general ledger and then compiled into its financial statements to form a historical record of its performance. Ultimately the income statement is nothing more than the in-flows (revenues) and out-flows (expenses) of a company’s normal business operations (once adjusted to conform to accounting rules).
Recognize that accounting records form the basis of future projections, but they themselves are not future projections, nor as we will discuss in the next post about soccer event data are the financial statements complete records of the underlying activities of the company. There are plenty of important activities a company undertakes that are not “transactions” and therefore not journalized. The value we might gain from starting here is that the financial records themselves while reasonably relevant are objective and verifiable. This is the value of accounting.
2) Pro-Forma Adjustments
Take these financial statements and make pro-forma adjustments to them to strip out and remove non-recurring items (noise) to arrive at pro-forma adjusted financial statements, which together serve as a historical record of the most recurring and predictive activities, those most appropriate to use as a foundation for future projections. For example, the target company we are evaluating may well have incurred a significant one-time legal settlement loss in the last year that we would not expect to recur. We might strip this cost out of the historical financial statements to arrive at a more predictive level of expenses with which to project forward into the future in the next step. They might have discontinued a product at the tail end of the last year, so we would want to remove the revenues and expenses associated with that product from the historical results since those are unlikely to recur if we were to acquire the company.
Project future results using the pro-forma adjusted historical financial statements as a starting point, considering things like:
growth trajectory of the adjusted historical results
industry guidelines for growth rates at comparable businesses
overall rule of thumb guidelines around maximum and minimum amounts to use in these projections to mitigate the risk of skewed projections based on outliers
Importantly, at this point assess whether the historical pro-forma results are at all appropriate for projecting the future. For example, this might not be the case if the company being targeted is a startup with no historical record of sales, only expenditures. In a case like this, projecting the future results is more complicated and uncertain. Without relevant historical financial data, prediction is much more of an art than science although all non-financial data should also be exhausted before giving up on this side of things.
Essentially, while predicting the future is hard, in this step we can use some structured and disciplined rules and controlled inputs to come up with a reasonable prediction in a normal environment, before considering any critical nonpublic information we may be privy to.
4) Proprietary Information
Further adjust the projected future free cash flows based on information not available in the historical results or not already embedded in the above process, considering things like:
Recent publicly available information not included in the financial statements
Evidence we have obtained ourselves that might be useful (e.g. conversations with key individuals, future revenue and expense projections used by management).
Synergy opportunities where the target company overlaps or complements the acquiring company in a way that is more than the sum of each of their parts (e.g. cross-selling opportunities, complementary technologies etc).
5) Other Information
Apply any further individual judgments you believe to be supportable and not already baked into the above steps.
At this point we have our prediction of the future: in our case the future operating results of the target company if we were to acquire it. We got there by starting with their historical results, stripping out the non-recurring noise, projecting these historical results forward using disciplined techniques, then layering in nonpublic information and other supportable adjustments.
The above steps are guidelines I’ve arrived at from generally available materials in the “business valuation” literature and also some common sense stuff I thought might be helpful to include in here, given where we’re headed towards mapping this over to soccer. They are not comprehensive and if you’re interested there are plenty of books and textbooks, (and surely) blogs on the subject matter. By all means, if you are a finance practitioner and disagree with any of this (I took many liberties in this hacked together representation), feel free to comment but hopefully it doesn’t derail from the overall points and the track we are headed down.
From here we link each step to soccer, one at a time. The next post covers the foundation: the analogical relationship between currently available event-level data in football matches, generally accepted accounting principles and financial statements, how they’re similarly flawed, and further what’s missing from soccer’s accounting records that financial statements handle well. We will introduce my favorite publicly available soccer analytics metric “Goals Added.” Even if you hate accounting, I sincerely believe this next one will be a treat because it strikes to the core of my inspiration for this project.
Despite popular beliefs to the contrary, match-level data in soccer is incredibly rich and serves as a very strong foundation for visualizing and evaluating past results, and therefore can serve as a very strong foundation for projecting the future. To unlock these qualities, we just need a little help from something that is embedded in the very heart of financial accounting data. You can probably guess what that is.