I’ve been thinking a lot lately about KPIs, and more specifically, whether we are always measuring the right things when it comes to gaming performance.

This comes from 26 years of working in the casino business. I started as a part-time poker dealer at 21, worked through almost every position in a poker room, moved into Marketing and then Table Games leadership, and have now spent the last 10 years on the vendor side with Tangam.

One thing I learned along the way is that you don’t really understand the P&L until you are responsible for it. When you’re working in a department, you do the job you’re asked to do and hopefully do it well. But when you become responsible for that department, you start looking at things differently. You start asking what the business is actually measuring, why it is measuring it, and whether that metric really tells you how well you’re operating.

When the KPI Doesn’t Match the Business

When I moved to Atlantic City in 2007, I was tasked with turning around a declining poker room. I started with the things I believed would make a difference. We improved the employee structure, separated Poker from Table Games and created a dedicated poker team.

Once we stabilized the operation, I realized there was very little marketing dedicated specifically to the poker room. So we introduced incentives and gave players in the market more reasons to visit. Our year-over-year revenue and profit were growing while many competitors were flat or declining. Among the four properties our company owned in the market, we were regularly first or second in monthly revenue and profit.

I remember telling our poker leadership team that we were firing on all cylinders. So when I got called into the AGM’s office, I expected a positive conversation. Maybe even a bonus. Instead, he told me we were the worst-performing property of the four.

I was confused. I explained that our revenue and profit were growing and that we were outperforming most of the other properties on both. He agreed, but those weren’t the numbers being used to measure our success. The metric was win per unit per day, or WPUPD, and we were fourth.

At the time, I was about 28 years old and had never heard anyone use WPUPD as the primary measure of success for a poker room. So I asked him to explain the calculation. We were taking our average daily poker win and dividing it by the number of tables in the room.

I knew how many tables each property had, and I knew we had approximately 12 that hadn’t been opened in years. The other properties were using essentially all of their tables, particularly on weekends.

So I asked what would happen if I took those 12 unused tables and put them in storage. We wouldn’t add a player, generate another dollar of revenue or improve the guest experience. Nothing about the operation would change, but our WPUPD would move from the worst of the four properties to one of the best.

He wasn’t particularly amused by the question and told me to leave his office. A week later, he called me back in and, to his credit, acknowledged the problem. We stopped using the metric that way.

Looking back, those unused tables were a fair reason to question whether we had more capacity than we needed. But that was a different question from whether the team was improving the business. WPUPD could tell us how much revenue we were generating across the tables we had on the floor. It couldn’t, on its own, tell us whether we were running a better poker room.

‍What Can the Operator Actually Control?

A few years later, I moved into a Table Games leadership role and found myself having a similar conversation, this time about hold percentage. At my first financial review, I was told that Marketing was responsible for the drop and Table Games was responsible for the hold.

Hold is the casino’s win expressed as a percentage of the drop. It tells us something about the financial result, but I remember wondering how much control an operator actually has over whether the casino holds 20% this week versus 17% next week. We can influence it, of course, but we can’t control the outcome of every hand, shoe, spin, roll or player session. A short-term result doesn’t necessarily tell us whether the operating decisions behind it were good ones.

What we can control is the operation. We control which games are on the floor, including pay tables, side bets and configurations. We control how many of each game we offer, when those games are open and what we charge for them. As an operator, offering the right game, at the right price, at the right time was how I approached improving revenue and the guest experience. Yet the final assessment still came down largely to whether we held what had been budgeted.

There is one way to illustrate the problem: have players buy their chips at the cage rather than at the table. With less money entering the table drop, the reported hold percentage can rise without another dollar of win. Obviously, that isn’t an operating strategy. It just shows how a KPI can move without the underlying operation getting any better.

That doesn’t mean we should stop looking at hold %. It means we need to read it alongside measures that help explain the result and guide the next decision. If we’re deciding whether to open another table or adjust minimums, occupancy, open hours, pricing and labour costs are more directly relevant than whether last week’s hold finished above or below budget. The financial results matter, but so do the operational decisions that produce them over time.

Related Tangam reading: Why Drop, Win and Hold Are Not the Most Useful KPIs to Evaluate Table Games Performance | Top 5 KPIs Every Table Games Executive Should Evaluate

Where WPUPD Helps, and Where It Falls Short

About six years ago, my boss and I were reviewing an early version of what would eventually become SODA with one of our first beta clients. By that point, I had gone from Poker to Marketing to Table Games and was now helping build a slot analytics platform.

As I started learning more about slot operations, I asked how operators typically measured the performance of an individual asset. The answer was familiar: win per unit per day, compared with the floor average or the average for a particular zone. It brought me straight back to those 12 poker tables in Atlantic City.

WPUPD is useful for understanding how much daily win a unit generates. Comparing it with an appropriate benchmark gives us a starting point for reviewing performance and identifying games that deserve a closer look. I’m not suggesting we throw that information away. The problem comes when we treat that comparison as a complete assessment of the asset rather than the beginning of the analysis.

Consider two hypothetical casinos evaluating a premium leased game using a multiple of floor-average WPUPD. Casino A averages $100 per unit per day, while Casino B averages $1,000. Let’s use 2× purely as an example, not as a recommended threshold.

Target WPUPD Performance = Floor-average WPUPD × Selected multiplier

Illustrative figures using the same reporting period and definition of win.

Are we saying that the premium leased game needs to generate $200 a day at one casino, but $2,000 a day at the other, to justify keeping it? Different properties may warrant different expectations, but I would want to understand why the selected multiplier is the right threshold for either property. The issue isn’t whether we choose 2× or some other number. The calculation tells us what the target is; it doesn’t establish whether that target makes business sense.

Buddy Frank discusses floor indexing in his CDC Gaming commentary, Frank Floor Talk: Has Eilers changed G2E? He explains how indexing allows comparisons relative to each property’s house average without disclosing its raw win figures. He also describes it as providing “an accurate snapshot of the game’s overall popularity and profitability.” That is the part I would question.

To assess popularity, I would also want to understand utilization and average wager. A game can generate strong revenue through higher wagers without being heavily utilized, while another can attract higher frequency play and higher utilization at lower wagers. The revenue index alone doesn’t distinguish between those situations.

For profitability, I would want to understand the contribution after the relevant costs and whether the game attracts or defends the player spend. Beating the floor average doesn’t answer those questions, just as missing a particular multiple doesn’t settle the decision either.

For me, moving beyond floor indexes means moving beyond them as the primary decision rule, not abandoning them as a benchmark. Before deciding whether to buy, lease, add or remove a game, I would want to understand what the financial, operational and player measures tell us together.

Sources and related reading: CDC Gaming: Frank Floor Talk: Has Eilers changed G2E? | Tangam: Reflecting on the Right KPIs for Slot Optimization | Tangam: Buy vs. Lease Slot Machines

Using Better Metrics to Make Better Decisions

This is where looking at several metrics together becomes useful. On a slot floor, peak-time utilization helps us understand how heavily a game is being used when demand is highest. Average wager adds another part of the picture based on the quality of the play. Read alongside theoretical win, these measures help us distinguish between games that earn their revenue through higher utilization or higher average wagers. Those differences matter when deciding whether to make operational changes.

For example, a game with strong WPUPD and consistently high peak-time utilization might warrant considering another unit. The same WPUPD on a lower utilization game would lead me to different questions about average wager, who is playing it and whether we already have enough of that product. The revenue number might look similar, but I wouldn’t assume the operational decision should be the same.

Before removing a below-average game, I would also want to understand its players. Does it have a loyal following? What do those players contribute across the floor? Are we confident they would move to another game, or could we be removing something that helps bring them back? A machine’s position in a revenue ranking doesn’t answer those questions.

Once we make a change, we need to check whether it helped or hurt the business. That means looking beyond the WPUPD of the machines we touched and reviewing the effect on total revenue, contribution after costs and player behaviour. Did visits or play time change? Did the floor generate additional revenue, defend the existing revenue or hurt the player experience? A better-performing bank isn’t necessarily evidence of a better-performing floor.

After 26 years in the business, I’m comfortable saying I don’t always know the answer. But I do want to understand what each metric is useful for, what it leaves out and what other information I need before making a decision. Those 12 poker tables taught me that improving a number can be surprisingly easy. The more important question is whether the decision behind it actually improves the business.