After week 8 of my golf league, I decided to have a chart-of-the-week. Now, for the first time ever, you can view all the charts o’ the week in one place with author commentary.
After scoring week 8, I noted that I was plummeting down the leaderboard while Miller seemed to be scoring well each week. I thought I would chart it out to see what it looked like. It was such a hit, that I decided to make a chart every week; sometimes two. I used smoothed lines, but in retrospect I shouldn’t have. I think smoothed lines gives a sense of imprecision. That’s OK if there is some imprecision in the data, but this data is rock-solid.
This week Jack shot a 45, which is a pretty good round for him. I thought I’d see what his highest round of the season was and that lead to showing the top five golfers with the largest difference between best and worst rounds. I must have been particularly lazy that week because I always change the plot area background to white. I couldn’t come up with a good way to show the dates of the rounds, so I just left them off.
Charlie is a sub and was working off of last season’s handicap. For those of you unfamiliar with golf, your handicap is an indication of how many strokes over par you should shoot. Charlie shot 18 over par, but his handicap (based on his past performance) indicated he should shoot 5 over. I tried sorting this based on the maroon section, but it didn’t look as good. You might note that I can’t seem to change those default data series colors. But when you see examples where I do change them, you might not think it’s such a bad thing.
Tesar had an amazing round, but I didn’t want to leave Miller out of the prop-fest. While I gave proper respect to the people who performed so well that week, this chart is really stupid. Does it really convey anything that posting a score card wouldn’t? Maybe it does, or maybe I had trouble coming up with a good chart that week. You try coming up with one every week. I wasn’t enamored with the “Par” data series because it gets obfuscated by the other series through most of the graph.
John, Jeff, Brian, and I all shot well in Week 12. In the clubhouse, there was some talk that we may have the lowest total foursome score of the season. It turned out we didn’t. But out of 14 two-man teams, you’ll note that I appear in three entries. And yet, Brian and I didn’t finish in the money. This chart wins the “I wish” award. The labels are too big. The label should be the date and it should be a stacked bar chart with each of the four component scores. Ah regret.
Upset Saturday is what college football fans call that one Saturday every season that a lot of favorites get beat and the polls get shaken up. Week 13 showed a lot of movement in the rankings and I wanted to create a chart that demonstrated the chaos of the week. The resulting half-finished chart, shown below, is what the Spaniards call la abortion. I made 14 series for the 14 teams. I can’t come up with two non-default colors that match, so 14 was out of the question. After I changed the colors of the first three teams, I briefly considered writing a macro, then quickly gave up and created “Consistenly Wham”. That chart (on the top) shows that Wham shot a four on every whole but one. I still think “Upset Saturday” is a good idea for a chart, I just don’t have the skills.
In this penultimate week, I wanted to show how the teams got where they are today with some basic stats. After computing the mean, I thought it might be interesting to see the median and mode. Then for a reason that still escapes me, I charted them with a line chart. I think line charts indicate the passage of time. This chart clearly should have been a column chart. It wouldn’t look as pretty though.
Hinrichs/Wiesenberger shocked the field with a second place finished. Considering they were 13th not too long ago, they deserved some props.
Early in the season, Steve Eck wanted to know how he could easily see how his partner was doing individually because his back was hurting. As his partner was Chris Hinrichs, his suspicious were well founded. I started with the total score but quickly realized that it was not sufficient. Not everyone played every week (they had subs) and there are team points that don’t get assigned to any one individual. I computed the average, which I thought was a more interesting metric. I ended up with two charts and no axes. I had to line them up manually, but I think it came out well. I wish they weren’t so big, but it’s the only way I could get all of the names to show. Click to embiggen.