The Age of Lotto

Are classic lottery games like Lotto evergreen– that is, will they continue to thrive indefinitely? This depends on whether the player population can be sustained into the future.There are two schools of thought about this: 1) Lotto play is something a player ages into; young people coming up will sustain it, and 2) Lotto play is a thing of the past; young people will not join. Looking at historical data from Washington, I show that age groups that now account for a significant share of spending played a lot less years ago.  However, the low level of engagement of the youngest age classes is unprecedented. The analysis supports hope but certainly not complacency for the future of these games.  NASPL Insights February 2018 


Engineering Instant Game Prize Structures: Results from Washington State

In lottery games repeat play is very important, and the prizes people actually win are particularly important in maintaining play of instant games. The cost of prizes is our greatest single cost, and tends to be challenged by auditors. Using quantitative visualization techniques described in NASPL Insights December 2013, the Washington Lottery redesigned its entire instant game portfolio and started fielding new-plan games in FY2016. Prize expense was reduced in key categories, yet the winning experience delivered to most players was improved. The financial and operational results were very positive through FY16 and FY17, as I describe in NASPL Insights Oct 2017

Shouldn’t there be a measurement for that?

A lottery sales representative, Otto the Beer Guy, explained his view of the business to me. Since some Scratch tickets sell better than others, and it’s a good idea to make the most popular ones easiest to find. To help Otto, I developed a metric that compares games on their current popularity, making it easier for people to see which games may need more space. The metric is based on the retail standard of turn rate. NASPL Insights June 2017

Do Lotteries Exploit the Poor?

Writers claim that lotteries exploit the poor, but how do they know this? Sometimes they show an analysis of lottery sales data, based on locations of retailers. I show that using the zip code as the unit of analysis is a blunder that promotes the least-populated zipcodes to unwarranted significance. Further, the assumption that lottery players buy tickets in the zip code where they live can be as wrong as it is convenient. Many a misleading story has been written on the basis of these two errors! NASPL Insights April 2017

How Many People Play the Lottery?

We are fairly sure that about half the eligible population of the US had a ticket for the record Powerball jackpot of January 2016. But how many people play the lottery on a routine basis, week after week, building up those jackpots that bring in the masses? The answers we get depend on how we ask the question. In NASPL Insights October 2016 I explain some reservations about using survey data to understand where sales are coming from, and illustrate a method I have used to combine survey information with ticket counts to develop a more reliable estimate.

Do You Call That a Win?

Watching from behind the mirror in a focus group, I heard a discussion that led me to test: do people treat a win differently, depending upon whether it was merely a pay-back of the wager, or something bigger? Four key learnings from my work on millions of wins:1) it’s the dollar value of the prize, not whether it is more than the wager, that predicts how diligently it will be claimed, 2) even $1 prizes get claimed about 90% of the time, 3) $4 wins appear to be as valued as $5, and 4) about 2% of wins get missed, regardless of their value.NASPL Insights February 2015

Common-Sense Construction

Math modeling can seem arcane, but I believe it is most effective when it incorporates intuitive or common-sense features. In describing the way people play the big jackpot games, for instance, we intuitively recognize that there are some people who play nearly all the time, and others who rush in when the jackpot gets to a certain size. I reassured Veronique’s agency that a well-crafted model can incorporate these features, in NASPL Insights August 2014.








No Really- I’m On Your Side!

The methods of hypothesis testing I learned as a scientist are applicable to many situations, including testing the effectiveness of advertising. The “null hypothesis” – the assertion that nothing has changed – is central to the method. This has the effect of putting me (the testing expert) in a position that feels adversarial, to those who are trying to show an effect of their work. In NASPL Insights June 2014 I recount how my first encounter with a client exposed both my methods, and their feelings.

Automating the Lottery Instant Game Supply Chain

In NASPL Insights January 2012, I report on the Business Rule Test (BuRT) project. A six-month project at WA Lottery showed that a fully automated system supported retailers as well or better than the inside sales/telephone sales that was standard at the time of the test. One key to the success of this project was to provide the sales representatives a way to provide information to the system based on their local knowledge. Another key was to harvest higher-level data from the gaming system to understand which games were trending in the marketplace. I posited a set of business rules, implemented them as code on a generic computing platform (VBA/ Excel!), and compared consumption of instant tickets from retailers who participated in the test, to a control group. The test retailers saw a sales increase.

Forecasting Instant Game Sales

In Washington State, the lottery shares its sales forecasts with state economists, who are accustomed to forecasting all sorts of revenue of the basis of economic and population variables. Taking their lead, I found that I could account for a long, quarter-by-quarter history of instant game consumption on the basis of population, cost of living, unemployment, and so on- without taking into account anything that the lottery was doing. With forecasts of these driving variables, it is possible to make quarter-by-quarter forecasts of instant game consumption that are as accurate as other revenue forecasts. I apologize for the tight academic style of this article; I was still transitioning from hard science! NASPL Insights October 2011