The Intersection of Running and Statistical Analysis

I spent this semester taking Foundations of Experimental Design at RIT. I was dreading this class based off of horror stories from other students, but it actually turned out to be probably my favorite class so far. It was a lot of work, but everyone knows that I work hard, and that I will diligently search through resources (old class material and textbooks, the internet, etc.) for hours in order to figure out problems and better understand what I'm doing. I am also now known as "the girl who posts questions on the online message board" - literally the ONLY one posting questions. It became a running gag throughout the class and I was thanked by several classmates for posting my questions. I tend to start my homework early, as early as right after class on Monday night, so my questions got posted early in the week. Anyways, I loved the class, it only made me cry about twice, it will be useful to me in the future, I digress. The most interesting part was the project I had to do, which involved designing an experiment (about anything I wanted), executing the experiment, analyzing the results, and then presenting my results in the form of a paper/presentation. (I didn't love writing the paper but the rest was fun). I haven't done any writing other than blogging (fun) or technical writing (work) since I graduated from college TEN YEARS AGO.

I did my experiment on the accuracy of GPS devices while running. It took me a long time to come up with this idea. I wanted to do something interesting to me because otherwise, what's the point? Originally I had wanted to do a coffee tasting experiment, but that got scrapped. One day I just had an epiphany and came up with this idea.. it ended up turning into a very interesting experiment with a really cool design that I otherwise would not have had a chance to do in this class. The best part was that I was truly interested in the outcome and did my best to run the experiment well!

I really love my Garmin

Now, DC Rainmaker has explored this subject several times. I actually probably should have read his methodology before I set up my experiment, because he had some better ideas than I did. Since I had to be able to reproduce my methods multiple times over several trials and days, I chose to use high school tracks - a track has a standardized, built in measurement system that establishes a "truth" which could be replicated multiple times at different tracks. There was no other way to do this that I could think of (DC Rainmaker actually ran while rolling one of those measuring wheels which is a brilliant idea that I wish I had seen before I submitted my idea).

I had 5 devices: a Garmin ForeRunner 305, two Garmin ForeRunner 310XTs, a Garmin Edge 500, and my iPhone with MapMyRun. I wore the 305 and the 310XT on my right wrist (I'm a lefty), I held the iPhone in my right hand, I wore the Edge in a spi-belt around my waist, and I hooked the other 310XT to the spi-belt to see how the accuracy would change with it at my waist (that was my professor's idea). I wanted to see how these devices measured 1 or 4 laps around a track at a jog (10:00 min/mile) or a run (8:00 min/mile). I did this four times at four tracks: Greece Athena, Greece Odyssey, East High School, and Brighton High School. I wanted to explore: how did accuracy change at the different speeds, distances, and between the devices themselves.

I'm not going to go into the nuances of my experimental design*, other than to say that I did this as a Split-Plot design, which to non-stats people, means that I wore/carried all 5 devices at once while I ran. Each day, I did 4 runs: jog 1 lap, run 1 lap, jog 4 laps, run 4 laps. I recorded the distance measured by each device and then subtracted the actual distance of the track (0.25 miles and 0.99 miles). This left me with my "response" or "Y" value called "Diff" (difference between measurement and truth).

I executed this experiment over 4 days in April. It was interesting trying to get access to tracks during track season (I hadn't thought about this), but I managed to use tracks near work (in Greece) during the day for the Thursday and Friday that I did this. I had to dodge a few phys-ed classes and felt kind of like a creeper, but I managed. During the weekend I used tracks near my house that didn't have weekend track meets at them. I will note that I randomized the run order at each track (the four combinations of speed/distance) but that was the only randomization that I needed. Four days of running gave me 80 data points which was great. Plus I got in some workouts which otherwise have been few and far between.

Awkward..

After getting the data, I sat on the project for a while due to other work associated with the class. I kind of poked at it here and there and had most of the basic analysis done prior to the last week of school (I needed a little bit of help from my professor since we never went over how do do this type of analysis). I was able to find a lot of resources online, however my example was a bit more complicated than basically every example I could find on the internet. After I finished my last take home exam for the class, I was able to power through the rest of the analysis. I will summarize a bit of it here, trying to explain these tables and figures as I go. For those interested, I use R to do basically everything stats related unless otherwise required. R is a free piece of software that is very powerful and flexible.. however its user-friendly-ness is "meh." I'm slowly getting better with hard work. I can also do quite a bit of stuff in SAS (early in this course I did everything in both R and SAS but that got time consuming and I stopped doing it).

OK, back to the analysis. After typing all of the data into Excel (I had to record it by hand at the track using a data collection sheet and a clipboard like some kind of hobo), I imported it into R and got to work. First, I ran the "full model" which included track, speed, distance, and device, plus all interactions between speed/distance/device.

Sidenote: In general, you can think of an interaction as follows: you have two foods - ice cream and a hamburger, and two condiments - chocolate sauce and ketchup. Individually, you like all four of these items. However, you only like specific combinations of them.  You like ice cream with chocolate sauce but not with ketchup. You like your hamburger with ketchup but not with chocolate sauce. This is an interaction between food and condiment. When these interactions are plotted, the slopes of their lines are not parallel (in fact, with the ice cream/hamburger example, they would probably cross and form an X which you can see below in my super professional interaction plot drawn via Paint). My Responses of "Yum!" or "Gross" are especially scientific and totally valid. Understanding this plot will be useful later.

Anyways, back to the model. A full model is run to determine which factors and interactions are truly important in the model, and which factors can be removed. This is done using Analysis of Variance (ANOVA).

Whole Plot
	DF	Sum Sq.	Mean Sq.	F-Value	P-Value
Track	3	0.001874	0.000625	6.379	0.01315
Distance	1	0.011761	0.011761	120.115	1.66 x 10^-6
Speed	1	0.001051	0.001051	10.736	0.00958
Distance:Speed	1	0.000911	0.000911	9.306	0.01378
Residuals	9	0.000881	0.000098
Split-Plot
	DF	Sum Sq.	Mean Sq.	F-Value	P-Value
Device	4	0.05454	0.013636	68.036	< 2.0 x 10^-16
Distance:Device	4	0.01693	0.004233	21.122	4.27 x 10^-10
Speed:Device	4	0.00137	0.000342	1.706	0.164
Distance:Speed:Device	4	0.00026	0.000064	0.321	0.862
Residuals	48	0.00962	0.000200

The table seen above is an ANOVA table for the full model. In the left column, you can see all of the factors and their interaction terms (denoted by Factor1:Factor2). "Residuals" refer to the unknown error in the model. To determine if a factor or interaction is important to the model, we compare the Mean Square Error of the factor in question to the Mean Square Error of the Residuals (by dividing). This is essentially comparing the variation in the response due to the factor to the variation in the response due to "noise" in the model caused by unexplained variation. If the variation due to the factor is the same as the variation due to the noise, then the factor is irrelevant. However, if the variation generated by the factor is greater than the noise, then the factor IS causing a change in the model. By dividing the MSE of the factor by the MSE of the residuals, you get an F-value, which is the statistical test of whether or not that factor is important. Since we now do these tests in software -and not by hand, the software will also generate a p-value, which you can see in the right hand column. If the p-value is less than 0.05, the factor its associated with needs to be kept in the model - and is important. You can actually try this by hand above. If you divide the MSE for Device (0.013636) by the MSE for the Residuals (0.000200), you will get an F-value of 68.036. Big F-value = important factor!

Note: this ANOVA table is a bit more complicated than a typical one because of the split-plot analysis. Typically there is only one error term (Residuals) however with split-plot, there are two (or sometimes more!). Getting the error terms correct and having them in the appropriate place is critical for performing the tests to see if factors are significant.

Based on this table, the terms that are important (statistically significant) are: Track, Distance, Speed, Distance:Speed, Device and Distance:Device. Can you see why this is so?

Cool! My experiment worked! Now what? What does this mean? This confusing table can't be the end of the analysis, right? Absolutely not. Part of the job of a statistician is to not only run the analysis, but to translate the results into explanations (words), plots, and tables that a client or management can understand. What did we find out from this experiment and how does it apply to  your product, company, clinical trial, etc. This isn't always possible for the statistician to do - if we're consulting then we are probably also not an SME (subject matter expert) and sometimes the data may even be coded so that we don't actually know what the experiment is on. In this case, we would summarize in terms of plots and leave the "why" to the experts.

So this ANOVA table tells me a lot. However, it doesn't explain WHY these factors are significant. So let's try to find out. Before going any further, the model needs to be checked for adequacy. If the model is not adequate, then any inference (fancy stats word for conclusion) made from it may not be correct. I won't go into this further other than to point out one interesting feature that I saw.

This is a plot used to detect outliers in my data. An outlier is a data point that is far away from the majority of the other data points. Sometimes the outlier can have negative effects on the data analysis, and it can be appropriate to remove them prior to analyzing the data. I had 4 outliers, and interestingly enough, ALL 4 outliers were associated with the Garmin Edge 500 - they are circled in pink in case that wasn't obvious enough. For those of you who are familiar with Garmin's lineup, this is actually a cycling computer that I borrowed from John (again at the suggestion of my professor, smart man). In this case, I left my outliers in my data set (they did not have much of an effect on the overall outcome of my analysis, and I saw no other reason to remove them).

So we've got the ANOVA table, the model checks out, now it's time for the fun part - see what happened and try to figure out why! We do this by using main effects plots and interaction plots. Rule of thumb is: if there is an interaction between two factors, then use the interaction plot. If a factor is not associated with an interaction, then use the main effects plot. However, it's not appropriate to use a main effects plot for a factor that is involved in an interaction, since you don't end up seeing the whole story for that factor!

First we'll look at the interaction plots. What an interaction plot is showing us is the mean of all of the responses at certain factors. For instance, below we have one factor: Distance, at 1600 m and 400 m - those are the two lines, dotted and solid. The other factor, Speed, is on the X axis. Speed is at two levels - jog and run. The response - mean of Diff - is on the Y axis and the mean is taken across all 5 devices at each Distance: Speed point. So this plot is showing us that at the short distance of 400 m, the accuracy of all devices together doesn't change much when you run slowly or quickly. Conversely, the speed DOES matter when you run a mile. The devices (on average) are more accurate when you run slowly (the mean of Diff is closer to 0) than when you run fast. I would wager that this interaction is important purely due to the interaction of the 1600 m distance with speed.

What could have caused this to happen? Well, think about what happens when you run 1 lap of a track and your Garmin reads 0.27 instead of 0.25. Not a big deal, right? That's pretty close. However, when you run 3 more laps, now your Garmin might read 1.08 (0.27 x 4) instead of 0.99. Propagation of error. Also, think about what happens when you run faster, but your Garmin is updating in 1 second intervals. You are running further in between those 1 second intervals, and the Garmin has to estimate your travel path in between the two update points. This can also cause more error. Just a thought. I'm not an expert.

The second interaction plot, seen below, shows the interaction of Distance and each Device. Again, Distance is represented by the lines, Device is on the X axis, and mean of Diff is on the Y axis. This time, the mean of Diff is the mean across both speeds for each Device:Distance point. Overall there is a pattern seen at both distances: the Garmin Edge tends to read short (less than 0) and the iPhone tends to read long (greater than 0). The other three (all ForeRunners) are in the middle somewhere. It also looks like this pattern is exaggerated at the longer distance - i.e. if the iPhone reads "long" for 400 m, it reads even longer at 1600 m! Same goes for the Edge.

This one is a little more interesting. Why does the Edge suck so much? One thing I failed to mention was that in setting up this experiment, I set all three ForeRunners to update every second. The Edge didn't have this option (it would be silly for the Edge to update every second because it would require more storage and the device is generally used to go much further than a ForeRunner). I honestly have no idea how often the Edge updates, but if it's less than once per second, then again, it's going to be guessing your path of travel between those updates. Especially since I was going around in circles, it probably anticipates that travel is in a straight line, not a curve, therefore it probably marks the tangents, therefore under-measuring. Why does the iPhone suck so much? Welp, it's not designed for running. Also, I held it in my right hand, so it was getting the additive effect of the arm pumping motion from running and traveling further by basically being in the 2nd lane (ok, that's a bit of an exaggeration since I'm not really that wide).

Next we'll look at the main effects plot. I haven't talked much about Track or its purpose in the model. Essentially, Track and Day were not something I cared about. They were not experimental factors. However, because the track was changing, as was the day, I needed to include them in the model in case there were differences seen track-to-track or day-to-day (due to cloud cover, satellite position, etc.). This is called a blocking factor (or sometimes, a nuisance factor). In experimental design, we group (block) data points that we think will probably will be similar to each other. In industry, this could be all products made on one machine, in agriculture it could be all plants on one tract of land. In my case, all runs done on Thursday at Greece Athena are probably more similar to each other than all runs done on Friday on Greece Odyssey, and so on. Therefore, we block on day/track. Let's go back to the ice cream/hamburger example. If 10 people were taste testing this combination, what do you think our blocking factor would be? If you said "person" then you are correct! We would block on person because each person's taste preferences would be different. Blocking factors need to be factored into the model to account for potential noise or changes in the response due to the different blocks.

Below you can see my main effects plot of Track. A main effects plot is used when there are no interactions involved. This plot shows the mean of all data points obtained at each track. Even though Track was significant in the model (meaning it contributed to a change in the accuracy that was discernible from noise), when looking at this plot, the change doesn't seem to be a big deal. It's probably due to changes in satellite positions day to day, or possibility track surroundings (for example, East High has a large stadium that could impact the GPS accuracy due to reflecting the signal).

So now we've seen that distance, speed, and device are all important in determining how accurate a GPS device will be. We know that the block plays a minor role. However, we still don't exactly know how these devices are different from each other. We know that they are different - Device is significant in the model and we saw that interaction plot above that looks like they are different, but I wanted to investigate this further.

This is called "post-hoc" analysis, which is probably Latin for something cool. There are some constraints to post-hoc testing that I won't touch on, but in this case, I wanted to compare all of the GPS devices to each other, known as pairwise testing. I used pairwise Tukey tests to do this.

With one line of code, R (my statistical package of choice) gives me this sweet table below that has all of the information that I need to answer my question! The left column are groups - any device with the same letter are not statistically different from each other. Therefore, the 305 and the 310XT that I wore on my wrist are the same. So glad I dropped that $400 to upgrade. The devices are ordered by their mean Diff (Diff being the response) meaning that on average, the iPhone measured ~0.05 miles long. On average, the Edge measured ~0.03 miles short. The two 310XTs are in different groups, and the 310XT worn at the waist is the best device seen here (it's almost perfectly accurate)!!

Grouping	Treatment (Device)	Mean Diff
A	iPhone	0.04875
B	Garmin ForeRunner 305	0.02812
B	Garmin ForeRunner 310XT arm	0.02500
C	Garmin ForeRunner 310XT waist	-0.000625
D	Garmin Edge 500	-0.02688

So what does this mean? Well, remember that I was running counter-clockwise in circles with all these things strapped to my right arm or my waist. So it kind of makes sense for the things strapped to my right arm (the top 3) to have a mean Diff that is positive, and the thing strapped at my waist to be nearly accurate. (And don't forget, the Edge just sucks for running, so maybe stick with a ForeRunner for your marathoning). I suspect that if I had done this experiment while running in a straight line, or turning equally in both directions, that the waist 310XT and the arm 310XT would be the same. What if I had a 3rd 310XT that I could have worn on my left wrist? Even better, right? Maybe next time..

Anyways, that was my class project. I wanted to just kind of explain what I found and ended up basically typing out an entire tutorial with explanations but I'm ok with that. If more people understood the power of statistical analysis and how cool it is, maybe I would get less ugly faces made at me when I tell people what my graduate degree will be.


*For a typical "full factorial" experimental design, you have multiple factors that you wish to study (in my case: device, speed, and distance) and you run them in all possible combinations. It would have been extremely time consuming to do one device at a time (0.25 miles x 2 speeds x 5 devices = 2.5 miles + 1 mile x 2 speeds x 5 devices = 10 miles for a total of 12.5 miles per day for 4 days). You use a Split-Plot design when one factor is "harder to change" than the others - in this case, the Device. It was an interesting use of the Split-Plot design because these were developed (I believe) for agricultural studies where it's easier to spread some sort of treatment (i.e. fertilizer or pesticide) over a large area than a small one. So visually, it's easy to see for the ag. industry, but it wasn't quite as easy to visualize this with my project. A friend of mine actually suggested carrying them at the same time, I asked my professor about it, he guided me towards split-plot, and I researched how to do it and proceeded from there.

Steamtown Marathon Race Report (marathon #5)

Let me just preface this race report by saying that my training going into this marathon was stellar. I nailed all of my long runs & nailed all of my tempo runs. My knee had been bothering me a bit off and on throughout the summer, but the few weeks before the race, it was behaving itself. I had PRed 2 race distances in the prior 2 months and was running the best I've ever run in my life. The weather was looking amazing. I had a pacing plan. I felt confident.

Two weeks before the race, I started feeling under the weather. I don't know if it was pre-race jitters or a real illness, but try as I might, I could not get it to go away. No "real" symptoms were manifesting but I had a non-stop headache, plugged ears, and I felt foggy - even lightheaded at times. And very, very tired. Especially in the few days before the race, this was causing me a lot of concern. Concern that I wouldn't be able to hold the pace I needed during the race, concern that I was going to "waste" all of my hard work on a failed BQ attempt when I didn't feel well. And no one could help me. No one could tell me what to do. No one could make me feel better. I was a MESS on Saturday.

Excellent seats!

Friday night, John and I had tickets to go see Newsies at the RBTL. We had to switch our tickets from Sunday to Friday because we were going to be in Scranton still on Sunday. Friday night was not ideal (I turn into a pumpkin at 10:30 pm regardless of what night of the week it is) but I hadn't wanted to get mid-week tickets due to having to juggle workouts, class, and my job.. this leads to a lot of early mornings and I didn't want to add a late night at the theatre into that mess. John dropped me off at my house after the show a little before 11, and I was promptly in bed by 11:01. He went home, as he was told that "under no circumstances will any alarm be waking me up before 8 am" and he wanted to run in the morning before we left. I actually ended up waking up at around 7 and getting my shakeout run done on Saturday morning!

John and I left Rochester at about 10 am and made it to Scranton by about 2 pm in time to pick up my race packet and attend the pre-race meeting. After being sufficiently scared by the entire race committee telling everyone to NOT GO OUT TOO FAST on the first 7 downhill miles of the course (or we'd regret it at mile 21), we drove the last few miles to check out the hills (miles 23-26) again. We then checked into our hotel, I cried for about an hour, and then we went to dinner.

I know, I am ridiculous. It's just a marathon. It seems so trivial in life but it's so much more than that (for me).

After dinner, because I had convinced myself that I was having some sort of allergies (even though I have never had allergies in my life), we went to CVS so I could buy an anti-histamine and hydrogen peroxide to try to unplug my ears. We went back to the hotel room, checked out the Kona stream, and I took a Benadryl and passed out.

Wake up call was at 5 am. I got up, went downstairs to get coffee and breakfast, then showered, got dressed, popped my anti-histamine, and John drove me the few miles to the finish and dropped me off so I could ride the shuttle to the start. He was going to head out to one of the early spectator points, run, and then wait for me there. I felt ok in the morning.

The ride to the start was uneventful, I chatted a bit with the girl sitting next to me and then listened to my music. We were welcomed into the Dickson City High School by a hoard of high school students, cheerleaders, and other volunteers. It was great to be able to stay warm in the gym (because it was below 40 degrees out at the start). I had on pants, a long sleeved shirt, and a hat for the bus ride, but I left the long sleeved shirt and pants in my drop bag and started the race wearing shorts, a tank top and gloves (I tossed the hat to the side of the road right before the race started - and I actually hit a guy in the face with it - oops!). I had my nutrition in my pockets and my Garmin on my wrist. Porta-potties were plentiful and lines were short. I can't say enough good things about the organization of the start of this race!

As I was heading to the starting line at about 10 of 8, I realized I had forgotten my sunglasses. Cursing, I ran back into the gym to see if I could grab them from my drop bag, but it had already been taken to the truck. Crap. Oh well, I'm pretty good at rolling with the punches. The race course went southwest, and the sun rises in the east, so I should be ok, right?

After a few words, the national anthem, and the blast of a very loud cannon, we were off and running. I crossed the mat after about 30 seconds and had a pretty clear path from the start (always a nice thing). I had planned with Jennie to run my first mile (aggressive downhill) at 7:40, my second two miles (which were flatter) at 7:50-8:00 pace, then miles 3-6 (more aggressive downhill) at 7:40 pace, and then after that to settle into my 8 minute pace for the remainder of the race (as the elevation profile leveled off more or less after the first 7 miles). After the race committee scaring the bejeezus out of me the day before coupled with the fact that I STILL did not feel great when I started running, I decided to split the difference and not try for those 7:40s.

this was at the very beginning
you can actually see me on the right in my hot pink!

I was not feeling great for the first 6 miles and was wondering how long I was going to be able to focus on my pace while feeling so "foggy." The downhill miles made it feel easier to hit pace but I knew that once it flattened out, it was going to be more challenging than I had anticipated. I saw John at mile 6 where I threw my gloves at him and asked him if he could hand me his sunglasses at the next spectator stop (because the sun ended up being REALLY bright and I was squinting a lot).

This was at mile 6 - the first time I saw John
I tossed him my gloves and demanded his sunglasses at the next stop!

Miles 1 - 7: 7:49, 7:49, 7:49, 7:48, 8:06, 7:50, 7:57

There were a few hills along the way as we ran from small town to small town, and eventually we made it on to the freshly paved rail trail path. I hit mile 10 still on pace (actually ahead of pace by about 40 seconds to a minute). This surprised me considering I still wasn't feeling great. At this point, I started breaking the race up into chunks. "Make it to mile 13, that's halfway." I went through the half in 1:44 something. Right on target.

Miles 8 - 13: 7:51, 7:55, 7:55, 7:59, 7:57, 7:56

"OK, make it to mile 16, then there's only 10 left." This worked rather well and gave me small, manageable sections on which to focus. I was pacing mile marker to mile marker, always making sure I was there before the appropriate multiple of 8. I just kept repeating the time I needed to be at the next mile in my head over and over again. I kept an eye on my Garmin for HR (I wanted to keep my HR at around 165 max) and average pace per mile (keep it between 7:50 - 7:55). At mile 16, my quads started to twinge and my HR started to rise. Uh oh.

Miles 14 - 19: 8:04, 7:53, 7:55, 7:49, 7:57, 8:09

 "Next, get to mile 20." I made it to mile 20, then 21, then 22, then.. oh crap. My quads were done. I saw John at around mile 22 as I was dying and yelled at him for trying to play 20 questions with me - "Please stop talking to me." (I swear I said please, John says I did not). Probably everyone around me thought I was a raging bee-yatch for yelling at my obviously-trying-to-help boyfriend. I lost the entire amount of time I had "in the bank" in this one mile. Mile 24 was torture as there was a large hill. A very large, demoralizing hill. With a large downhill after it that was painful to my poor abused legs. I got pretty negative here, knowing I was going to miss my sub-3:30 time goal/BQ guarantee, but at some point I must have realized that a) I could still PR as long as I held it reasonably together and b) I COULD STILL ACTUALLY RUN A BQ TIME. Even though at this point, you can't just run a BQ and get into Boston, it doesn't mean that I couldn't still try to beat the standard. Perspective, Alexa.

Miles 20 - 26.2: 7:55, 8:04, 8:06, 8:54, 9:20. 9:25, 9:08, 2:54 (7:59 pace for that last 0.2)

Finish: 3:34:16, 8:08 pace. PR by over 5 minutes, BQ by 44 seconds.

this path was a delight for running

I was wrecked when I crossed the finish line. John was jogging alongside me down the homestretch so he was right there when I finished. I got my medal and my foil sheet and staggered over to hug him over the fence. I was upset and on the verge of crying but I got it together. I walked through the food tent (they had amazing post-race food but I usually cannot eat right after a race) and went and sat on the grass in the sun for a while.

new blaaaaaang!

John saw me 7 times during the race. He was amazing. It felt like every time I ran past a group of people, he was among them. I can't remember a lot of details about the race, I can't remember when I saw him or where I was, but he was always there cheering and giving me words of encouragement. Even when I yelled at him he was fine with it (I did apologize afterwards). He's the best.

We were able to check into our new hotel in downtown Scranton (we switched from the crappy pre-race hotel that I booked to John's Hilton with his points) right after the race (several hours before check-in, even) and we lounged for a bit, walked to a place to get hoagies (because when in PA, one must eat PA food.. right?), and then hit the hotel hot tub! We went to a Hibachi place for dinner because I was craving.. vegetables(?).. both John and I surprisingly liked downtown Scranton. There were lots of places that were within walking distance from the hotel, the weather was amazing, and it was fun to just hang out for once without a schedule.

In the morning, we slept in, got some coffee, hit the record store that we had seen the last time we were in Scranton (that was closed on Sunday), met up with my dad for a late lunch, and got back to Rochester Monday evening!

Thoughts on the race itself:

I loved it! The organization of the race was impeccable which made the weekend very relaxed (well, as relaxed as it could be for the most important race of the year). There were great directions to the shuttle drop off, the start, to view points for the spectators, etc. The shuttle ride was easy, the porta potties were plentiful, you could roll out of the warm high school to the starting line 1 minute before the start if you so wished. The crowds along the course were AMAZING for a small town marathon (~2000 runners). I think 2000 runners is the perfect size - it's not crowded but you're never alone. There was no half marathon which can be nice when you don't have to worry about dodging the slower half marathoners (or being crammed in the start with them). The weather was PEFRECT (obviously this is not controlled by the marathon but mid-Oct. is a pretty good time for a marathon) and it is a very scenic course. To be noted: I tried very hard to run the tangents, and I actually only ended up being *slightly* over 26.2 miles for my total distance, which is refreshing, and I also couldn't believe it given the amount of turns on the course. The race shirt was awesome - long sleeved women's fit tech shirt with THUMB HOLES (!!!!) and it was green! (I am easy to please..). The medal was nice. Post race food looked great. The emails sent by the assistant race director in the months leading up to the race are hilarious.. like..  rivaling Jeff Henderson level of hilarious!

I can't say enough good things or recommend this race enough! I am not into repeating races.. but this one could be a repeat possibility for me.

Thoughts on MY race:

I was initially disappointed, but after having some time to come around, and talking to Jennie, I am feeling pretty good about my race. I did not feel 100% healthy while racing, yet I managed a 5+ minute PR. I fell apart at the end, but looking at my Garmin data, I never backed off my effort. I did not qualify for Boston with my 5 minute buffer, but I STILL QUALIFIED FOR THE BOSTON MARATHON. That is something that I have seriously doubted I would ever be able to do - ever since my very first marathon in 2009 where I ran a 3:59. In 5 marathons, I have taken 25 minutes off of my marathon time. That's not nothing and it's DEFINITELY something of which to be proud. My running has come a long way and I personally believe it can still go a long way from here on out!

Thoughts on my.. shoes(??):

This was my first marathon using my Saucony Zealots. I switched to Saucony sneakers at some point last year after running for years in aggressive motion control New Balances (with custom orthodics) and it was overkill. I went to Fleet Feet to find a neutral trainer, and they put me in Saucony Triumphs, which I like and ran in for a while before experimenting with the Zealot to get a lighter shoe. Now, I tend to alternate between the two shoes, using the Zealots for speedwork and long runs and the Triumphs for day to day runs. It took some time to get used to the minimal heel-to-toe drop of the Zealots, but I worked my way up to longer miles with them and now I LOVE them. They were perfect in the race - no rubbing, no hotspots - it was great!

And finally...

Now, I need to figure out what is next. This story isn't over yet. My goal going into this race was to run sub 3:30 because that would give me the 5 minute cushion to be able to register for Boston 2017 during the first week of registration. With my current BQ time, I highly doubt I will even get into Boston at all. Which means.. I need to try again. I know I can do it. It's just a matter of a) utilizing the fitness I currently have and b) trying to take care of this before my 2 really hard classes start (Spring 2016 - Fundamentals of Experimental Design - and Fall 2016 - Capstone - are both going to be immensely challenging and will require a workload that will not permit the time to incorporate serious marathon training).

Stay tuned..

Rochester Half Marathon Race Report

Yesterday, I wrapped up the 4th (and final) race of the Fleet Feet Four Seasons Challenge - the Rochester Half Marathon.

The 4 Seasons medals - I stole this photo from Todd b/c his is much better than mine

I *love* the Rochester Marathon. I love running and Rochester and its running community and the fall weather (that we sometimes get in September).

This year, the Roc Marathon had a new course. Instead of running 14 miles of the Erie Canal path (less for the half marathon), the course was moved to the northern part of the city - Charlotte - and part of West Irondequoit where races are rarely run. However, this part of the city has some lovely parks/trail systems that even I had not seen (and I live in East Irondequoit!!) until I previewed the new course to see what it would be like.

Although the previous marathon course was fast and predictable, the canal path can get a bit dull after a while. I was happy and excited for the change. I've run the Rochester half and the full on the old course, so I'm glad I got to experience them while they were in existence, but psyched to see the race move to a fresh locale.

Since I am running the Steamtown Marathon in 3 weeks, I was not allowed to go "balls out" for this race - per Jennie. However, we both thought that if the weather cooperated, and I had a good day (basically, the stars aligned), I could PR this race.

Note: I was not specifically trying for a PR, I was simply trying to execute this race according to Jennie's instructions and if a PR happened - great.

I would be lying if I didn't admit that I have been trying for a half-marathon PR since 2011 - and not just a PR - a sub 1:40 time. I set my half PR in 2011 at Flower City Challenge: 1:40:55. That is not the easiest course and I was confident that I could best that PR, however, in 4 years, I haven't been able to do it. I came reasonably close in both of my attempts last year: Buffalo half-marathon (1:41:45 - admittedly I was not in great shape) and PA Grand Canyon half-marathon (1:42:20 - hilly as shit course). I failed at my attempt this year at Shoreline (blame the weather for that one).

So, it has been getting pretty ridiculous.

However, my main goal this year is Steamtown. I want a BQ, I want it really, really badly, and that is all that I want.

My instructions from Jennie were to start out at 1:40 pace (7:38 min/mile) (and actually, to go out a bit faster than this initially to account for the downhills during the first few miles of the course) and maintain this pace past the hill on Thomas/until mile 6. At that point, I needed to self-assess: if I was feeling reasonably comfortable with the pace - then maintain the pace for a 1:40 half. If not, I was to back off and run the rest of the race at 8:00-8:10 pace (which would still give me a good workout with some marathon-pace miles). I was not to get to a point where I was putting forth more than 90% effort until the last few miles, and then it was ok to make myself uncomfortable. This required me to be self-aware and to be able to give myself an ego check if I wasn't feeling great. That's hard to do - I am competitive, I want the PR, John was racing and I (not so secretly) wanted to beat him - but I knew I had to be able to back off if my body dictated.

Adding to the fun - John and I had late nights on Friday (at the Fringe fest) and Saturday night (at a wedding in Geneseo). We left the wedding at 9 pm (which I felt badly about) in order to get back to Rochester and I was in bed before 11.

We had a 5 am wake-up - and we had to do the bathroom in shifts - since myself, John, David, and their friend Mark were all racing. We left for the race around 6, climbed on the shuttle to the start, hung out at the start for a while as we saw random friends here and there. I did a 1 mile warm up solo, ditched my long sleeved top, and lined up maybe 5 or 6 "rows" back from the line. The weather was great - it was nice and cool and cloudy. In terms of food pre-race I had coffee & half a bagel with jelly at John's, a banana once we got to the race, and then a Honeystinger waffle before my warm up, as well as some water which I sipped on until it was time to line up.

The course is really fun. It starts in Maplewood Park by the tennis courts, heads north, and then at mile 2.3 it sends runners off the road onto the Genesee Riverway Trail which goes through some woods, over a boardwalk, and then pops out onto Lake Ave. Runners then cross the Genesee River and head south on Thomas Ave. At about mile 5.5, there is a significant climb which ends the downhill portion of the race. Runners then turn right onto St, Paul, and stay on St. Paul until heading back to the Riverway Trail in Seneca Park, across the pedestrian bridge, and back into Maplewood Park. This is about mile 10. Runners head south on the Riverway Trail, cross Driving Park Ave. and cross the river at Middle Falls, turn onto Brewer St. (and up a big hill), then run to Frontier Field for the finish.

You can see me in pink shorts, and Heather in blue shorts to the left of the flag guy

I ran the first few miles with Heather and Mark (they were both doing the full). Mark pulled away first, and then Heather did while we were on the boardwalk - she was going too fast for me and it wasn't worth it to me to try to keep up. My first 5 miles were pretty quick: 7:23, 7:33, 7:28, 7:21, 7:35. I slowed a bit running up the Thomas Ave. hill, but I didn't mind this hill. Mile 6: 7:52. After getting up the hill, I assessed how I was feeling. I still felt like I was running comfortably and my knee wasn't bothering me, so I made the plan to run 7:35 - 7:40 pace until the 10 mile mark. If I still felt ok at that point, I would pick it up. If I ever started to struggle, I would back off. Miles 7-10: 7:37, 7:40, 7:39, 7:33. Still feeling good and reasonably comfortable with the pace.

John passed me somewhere after the Thomas Ave. hill. We had a *small* wager about the race just to make it fun - but nothing that I wouldn't be too upset over losing - so I let him go by me. I figured if he was within striking distance at the 10 mile mark, I'd try to catch him.

After crossing the pedestrian bridge, I cranked it up a notch. This turned into "try to maintain current pace" because the course got a little rough here with some rolling hills, some dirt trails, and a super steep uphill on Brewer St. which I was unaware of (oops). I definitely slowed a bit here, but not for lack of trying! I passed John (pretty hard) at around mile 10 (sorry dear). At mile 12, I knew I was going to be very, very close to going sub 1:40. I slammed on the gas and ran it in as hard as I could. I saw Katie with about a quarter mile to go which was encouraging. I could see the finish line and I could see that my Garmin said 1:39 (of course, no seconds were visible). I saw the clock turn to 1:40 just seconds before I crossed the line. Miles 11-13.1: 7:41, 7:39, 7:06, 1:54 (6:33 pace) - my Garmin clocked my run as 13.29 miles.

I was hopeful that perhaps the net time would be enough to put me under 1:40. However, my official time was 1:40:01. Good enough for a 54 second PR, but not sub 1:40. I was slightly annoyed, however, I can't be too upset since I got my PR without trying too hard, got in a great prep. race for Steamtown, and ended up getting 3rd in my age group!

My go-to nutrition plan during every (running) race that is longer than an hour is 2 Honeystinger chews (or currently I am using Skratch Lab Fruit Drops) every other mile (so basically, at every "even" mile - I eat), along with water when I take the chews. I followed this at the Roc Half and I will follow it at Steamtown, although will add in on-course electrolytes there as well. If it's hot, I slam as much fluid as I can at the aid stations.

John finished in 1:40:18 which is a several minute PR for him. (He had a goal of going sub 1:40 as well). I'm very proud of him! I wasn't sure what happened to him after I passed him but he was right behind me. He'll be taking another crack at a sub 1:40 this year I'd imagine.

I know, we're adorable

Me? I'm focusing on Steamtown. Only a few more weeks (if that) of solid work left, then taper, then it's go time!