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Kevin Rudy

I write about how statistics can be used to help understand sports, but these techniques and tools have applications in quality improvement and any other endeavor that involves the analysis of data. Continue Reading »

Predictions can be a tricky thing. Consider trying to predict the number rolled by 2 six-sided dice. We know that 7 is the most likely outcome. We know the exact probability each number has of being rolled. If we rolled the dice 100 times, we could calculate the expected value for the number of times each value would be rolled. However, even with all that information, we can't definitively predict... Continue Reading
In week 16 of the 2016 NFL season, the Cleveland Browns were able to avoid going into the history books as only the second team to finish the season 0-16. They claimed their first and only win of the season after San Diego missed a last-second field goal. While they came very close to going winless, the statistics paint a very different picture of the odds of that occurrence.  Going 0-16 is hard. Usi... Continue Reading

7 Deadly Statistical Sins Even the Experts Make

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The college football season is here, and this raises a very important question: Is Alabama going to be undefeated when they win the national championship, or will they lose a regular-season game along the way? Okay, so it's not a given that Alabama is going to win the championship this year, but when you've won 4 of the last 7 you're definitely the odds-on favorite. However, what if we wanted to take... Continue Reading
The Olympic games are about to begin in Rio de Janeiro. Over the next 16 days, more than 11,000 athletes from 206 countries will be competing in 306 different events. That's the most events ever in any Olympic games. It's almost twice as many events as there were 50 years ago, and exactly three times as many as there were 100 years ago. Since the number of Olympic events has changed over time,... Continue Reading
When you perform a statistical analysis, you want to make sure you collect enough data that your results are reliable. But you also want to avoid wasting time and money collecting more data than you need. So it's important to find an appropriate middle ground when determining your sample size. Now, technically, the Major League Baseball regular season isn't a statistical analysis. But it does kind... Continue Reading
There may not be a situation more perilous than being a character on Game of Thrones. Warden of the North, Hand of the King, and apparent protagonist of the entire series? Off with your head before the end of the first season! Last male heir of a royal bloodline? Here, have a pot of molten gold poured on your head! Invited to a wedding? Well, you probably know what happens at weddings in the show. ... Continue Reading
For hundreds of years, people having been improving their situation by pulling themselves up by their bootstraps. Well, now you can improve your statistical knowledge by pulling yourself up by your bootstraps. Minitab Express has 7 different bootstrapping analyses that can help you better understand the sampling distribution of your data.  A sampling distribution describes the likelihood of... Continue Reading
When it comes to statistical analyses, collecting a large enough sample size is essential to obtaining quality results. If your sample size is too small, confidence intervals may be too wide to be useful, linear models may lack necessary precision, and control charts may get so out of control that they become self-aware and rise up against humankind. Okay,that last point may have been... Continue Reading
Probability. It's really the heart and soul of most statistical analyses. Anytime you get a p-value, you're dealing with a probability. The probability is telling you how likely it was (or will be) for an event to occur. It has numerous applications across a wide variety of areas. But today I want to focus on the probability of a specific event. A basketball tournament. I’ll be using the Sagarin... Continue Reading
What is an interaction? It’s when the effect of one factor depends on the level of another factor. Interactions are important when you’re performing ANOVA, DOE, or a regression analysis. Without them, your model may be missing an important term that helps explain variability in the response! For example, let’s consider 3-point shooting in the NBA. We previously saw that the number of 3-point... Continue Reading
Any time you see a process changing, it's important to determine why. Is it indicative of a long term trend, or is it a fad that you can ignore since it will be gone shortly?  For example, in the 2014 NBA Finals, the San Antonio Spurs beat the two-time defending champion Miami Heat by attempting more 3-pointers (23.6 per game) than any championship team in league history. In the 2015 regular... Continue Reading
The College Football Playoff technically doesn't start until December 31st, but in reality it started Saturday night in Indianapolis. The winner of the Big Ten Championship Game was in the playoff, while the loser was out. The stakes couldn't have been higher. So the competitors need to make sure they gain every advantage they can. And that's where 4th down decisions come in. With a lot of... Continue Reading
There was a lot at stake in the final week of Big Ten play this week. Three different games had an impact on not only the Big Ten Championship Game, but the College Football playoff as well. Unfortunately for the viewers, none of the games were really close in the 4th quarter. But that doesn't mean we can't analyze the 4th down decisions in the first 3 quarters and see whether the losing teams had... Continue Reading
This past weekend in the Big Ten showed how being conservative on 4th down decisions can cost you a game. Ohio State punted on 4th and 1 three different times, while Penn State and Illinois both kicked field goals in the 4th quarter when they needed a touchdown to tie or take the lead. All three teams lost. Perhaps taking some advice from the 4th down calculator would have greatly benefited them! If... Continue Reading
We use statistics to arm ourselves with more information. That information allows us to make more informed decisions. And the sooner we can obtain this information, the better. For example, suppose one of your manufacturing machines starts to malfunction and makes your products out of spec. You don't want to wait until the product reaches customers before you discover this information. Then it's... Continue Reading
Going into Saturday, Nebraska was 0-5 in games decided by 7 points or less and Michigan State was 4-0 in games decided by 7 points or less. You'll often hear sports analysts use this as proof that one team chokes under the pressure and the other team knows how to win in the clutch. But in reality, the result in close games can have just as much to do with luck as it can skill. Consider the formula... Continue Reading
4th and 1. It's a situation where the Big Ten 4th down calculator will never say to kick (unless, of course, it's the end of the game and a field goal will tie or take the lead). But what would it take to have the statistics suggest a punt? The key here is how far the punt travels. Last year the average Big Ten punt traveled about 40 yards. Using this value, in your own territory you'll score... Continue Reading
Nebraska lost another close game, teams continue to incorrectly punt to Ohio State on 4th and short, and Northwestern keeps making terrible 4th down decisions. Another regular week for the Big Ten 4th down calculator. In case you haven't read the earlier entries in this series, I've used Minitab Statistical Software to create a model to determine the correct 4th down decision in Big Ten Conference... Continue Reading
Week 4 in the Big Ten featured a couple blowouts, an insane comeback, and the worst punt in the history of recorded time. But before we get to all that, here's my weekly blurb on what exactly the 4th down calculator is.  I've used Minitab Statistical Software to create a model to determine the correct 4th down decision. And for the rest of the college football season, I'll use that model to track... Continue Reading
Every single Big Ten team played a conference game this week, giving us the most 4th downs to analyze yet. Last week, 4 of the 6 games were decided by one possession. This week only 2 of the 7 games were decided by one possession, so let's see if the losing teams missed opportunities to keep the game close! But first, a quick refresher on what this is.  I've used Minitab Statistical Software to... Continue Reading