A Look Back At The Season Using Throws Gained
December 17, 2018 by Aaron Howard in Analysis with 0 comments
The off-season hot stove is burning brightly and the sponsorship carousel is spinning at full speed. Suffice it to say, everyone within the disc golf community is looking forward to the 2019 season. However, I contend that there is still a lot we can learn from the 2018 season. This may be, in part, because I am a professor, but I believe very strongly that the best way to understand the future world that we live in — whether it is biological, societal, or disc golf-related — is to understand our past.
So with that, let’s take a look back at the 2018 season and determine which players had the best season according to throws gained. I have written several times about the concept of throws gained, but in short, it is based off a concept developed for ball golf, where it is called strokes gained, that estimates by how many strokes (or throws) a player is better than some benchmark, typically the average player.
For example, the average player at the 2018 USDGC threw a total of 278 across the tournament’s four rounds. Paul McBeth had a total of 234 throws, so he was 44 throws above average, or he had 44 throws gained for the entire 2018 USDGC event.
Of course, there are many issues with looking at only throws gained above average for a tournament, course, or round. I have discussed some of those issues before, but if you are interested in a deeper dive into this concept, I highly suggest you read the three part series of articles recently written by Chuck Kennedy.
The take-home message is that a better way to interpret scores is by using SSA (scratch scoring average), which represents the expected score for a 1000-rated player in any given round.1 I think it is important at this point to note that the SSAs I am calculating are my own estimates and they are going to be (potentially) different than those calculated within the PDGA’s proprietary rating method. In addition, for FPO I used a 920-rated player as the benchmark because a 920 rating is roughly the FPO equivalent to an MPO rating of 1000 in terms of portion of total players in competition. It also prevents all FPO players from having negative throws gained values, which would be very counterintuitive.
So, using these methods I calculated the season-long throws gained over average and over SSA for both MPO and FPO players.2 I also included the per event averages in throws gained because they give credit to those that played well but in fewer events.
Throws Gained 2018 - FPO
| Player | TG Over SSA Per Event | Total TG Over SSA | TG Over Average Per Event | Total TG Over Average |
|---|---|---|---|---|
| Paige Pierce | 17.6 | 263.5 | 21 | 315.3 |
| Eveliina Salonen | 14.6 | 73.2 | 23.5 | 117.7 |
| Sarah Hokom | 14.1 | 226.3 | 17.4 | 277.8 |
| Paige Bjerkaas | 9.7 | 126.1 | 13.6 | 176.4 |
| Kristin Tattar | 9.3 | 84 | 14.9 | 134.3 |
| Catrina Allen | 9.1 | 164.4 | 12.5 | 225 |
| Rebecca Cox | 7 | 69.5 | 10.6 | 105.9 |
| Sandi Hendel | 5.7 | 23 | 9 | 36.2 |
| Jessica Weese | 5.6 | 89.4 | 9 | 144 |
| Vanessa Van Dyken | 5.4 | 38.1 | 8 | 56 |
| Holly Finley | 5.2 | 41.3 | 9.7 | 77.7 |
| Lisa Fajkus | 5.1 | 71.4 | 7.9 | 110.4 |
| Zoe Andyke | 4.8 | 33.5 | 7.4 | 52 |
| Nicole Bradley | 3.3 | 16.6 | 4.3 | 21.7 |
| Madison Walker | 2.5 | 34.8 | 5.4 | 75.4 |
| Elaine King | 2.4 | 11.9 | 2.9 | 14.7 |
| Jennifer Allen | 2.3 | 11.3 | 3.2 | 15.8 |
| Natalie Holloköi | 1.2 | 7.2 | 4.7 | 28.3 |
| Hannah McBeth | 0.4 | 1.6 | 4.9 | 19.5 |
| Erika Stinchcomb | -0.3 | -1.2 | -1.7 | -6.7 |
| Lauren Butler | -1.2 | -7.3 | 2.1 | 12.5 |
| Ellen Widboom | -2.9 | -43.3 | 0.2 | 3.6 |
| Kona Star Panis | -3.2 | -41.8 | -0.6 | -7.9 |
| Katka Boďová | -4.3 | -25.7 | -1.9 | -11.3 |
| Nicole Dionisio | -9.6 | -67.3 | -3.2 | -22.7 |
Throws gained over SSA per event, total throws gained over SSA for the season, throws gained over average per event, and total throws gained over average for the entire season for top 25 FPO players.
Let’s start with FPO because, frankly, I think the results are more interesting. No surprise, Paige Pierce stands out from the crowd with an average of 17.6 throws gained over SSA per tournament. She also played a lot of tournaments, so she dominates the total count with a value of 263.5, which is almost 40 throws higher than her nearest competitor, Sarah Hokom.
What is surprising is that Eveliina Salonen dominates the throws gained over average per event. She outpaces Pierce by 2.5 throws. This is certainly indicative of the fantastic season Salonen had, but it is also an example of one of the major issues with using the average player in a tournament as the basis of comparison. Salonen played all of her events in Europe and the European Pro Tour events had a population of players with an average rating that was 15 points lower than the average across all events. This means that the average player over which Salonen gained throws was not as strong as the average player in most of the tournaments in the US and resulted in a very large difference between her throws gained over average and her throws gained over SSA.
Nonetheless, Salonen had the second highest throws gained over SSA per event. Again, this indicates that she had a fantastic season and makes it clear, at least to me, that high-quality players like Salonen (and their sponsors) need to figure out how they can get across the Atlantic (like Kristin Tattar did!) and play tournaments in America.
Throws Gained 2018 - MPO
| Player | TG Over SSA Per Event | Total TG Over SSA | Total TG Over Average Per Event | TG Over Average |
|---|---|---|---|---|
| Paul McBeth | 21.5 | 387 | 24.7 | 444.3 |
| Eagle McMahon | 21.3 | 297.6 | 23.5 | 328.9 |
| Richard Wysocki | 20.8 | 374.2 | 24 | 432.5 |
| Chris Dickerson | 18.5 | 147.6 | 22.5 | 179.9 |
| Nathan Sexton | 16.6 | 232.6 | 19.1 | 267.5 |
| Gregg Barsby | 16.1 | 225 | 22.1 | 309.5 |
| James Conrad | 15.1 | 256.9 | 18.3 | 311.9 |
| Calvin Heimburg | 15 | 105.1 | 17.5 | 122.7 |
| JohnE McCray | 14.9 | 134.5 | 19.8 | 178.6 |
| Seppo Paju | 14.7 | 191.1 | 16.5 | 215.1 |
| Joshua Anthon | 14.7 | 132.1 | 16.5 | 148.3 |
| Simon Lizotte | 14.5 | 203.7 | 18.1 | 253.7 |
| Michael Johansen | 14.5 | 101.6 | 18 | 125.7 |
| Kevin Jones | 14.2 | 241.9 | 17.5 | 296.9 |
| Nikko Locastro | 13.2 | 132.3 | 16.8 | 167.8 |
| Nathan Doss | 13 | 51.9 | 16.1 | 64.3 |
| Paul Ulibarri | 13 | 207.4 | 15.6 | 249.4 |
| Emerson Keith | 12.7 | 101.2 | 17 | 135.8 |
| Cale Leiviska | 12.3 | 73.7 | 13.8 | 82.9 |
| Drew Gibson | 11.7 | 198.9 | 14.9 | 253.9 |
| Zach Melton | 10.9 | 130.4 | 13.7 | 164.4 |
| Garrett Gurthie | 10.8 | 173.4 | 14.2 | 226.5 |
| Karl Johan Nybo | 10 | 70 | 14.3 | 100.2 |
| Martin Hendel | 9.8 | 49.1 | 10 | 50.1 |
| Nate Perkins | 9.2 | 129.3 | 12.6 | 176.1 |
| Philo Brathwaite | 9.2 | 156.3 | 14.4 | 244.3 |
| James Proctor | 9.2 | 55.2 | 12.5 | 74.8 |
| David Feldberg | 8.9 | 44.5 | 12.9 | 64.4 |
| Joel Freeman | 8.5 | 110.9 | 10.9 | 141.8 |
| Jeremy Koling | 8.5 | 144.4 | 11 | 187.8 |
| Devan Owens | 8 | 111.5 | 11.4 | 159.2 |
| Chandler Fry | 7.7 | 38.7 | 7.7 | 38.5 |
| Anthony Barela | 7.6 | 68.7 | 8.9 | 79.9 |
| Austin Hannum | 7.6 | 128.9 | 10.8 | 183.9 |
| Teemu Nissinen | 7.6 | 52.9 | 13.1 | 91.7 |
| Steve Brinster | 7.4 | 37 | 8.2 | 41.2 |
| Grady Shue | 7.3 | 117 | 10.2 | 164 |
| Andrew Presnell | 7.1 | 77.9 | 10.5 | 115.6 |
| Noah Meintsma | 7 | 84.5 | 9.5 | 114.5 |
| Bradley Williams | 6.6 | 59.5 | 10.6 | 95.2 |
| Bobby Musick | 6.4 | 51.2 | 9.1 | 72.6 |
| Matt Dollar | 6.1 | 42.6 | 8 | 56 |
| Eric Oakley | 6 | 101.9 | 9.2 | 156.9 |
| Chris Clemons | 5.7 | 73.7 | 9 | 117.6 |
| Väinö Mäkelä | 5.5 | 27.7 | 13 | 65.2 |
| Peter McBride | 5.2 | 62.8 | 8.8 | 105.8 |
| Avery Jenkins | 5.1 | 20.5 | 6.9 | 27.7 |
| Steven Rico | 5.1 | 20.3 | 5.4 | 21.8 |
| Brian Earhart | 5 | 55.4 | 8.3 | 91.4 |
| A.J. Risley | 4.8 | 76.9 | 8 | 128 |
Throws gained over SSA per event, total throws gained over SSA for the season, throws gained over average per event, and total throws gained over average for the entire season for top 50 MPO players.
The MPO side is dominated by Paul McBeth. He had all of the highest values, whether per event or across the season. Unlike FPO, there aren’t as many interesting flip-flops in rankings between average and SSA values, though it appears that Ricky Wysocki’s SSA values were hurt a bit by his long stay in Europe.
The throws gained data also provide credence to the idea of breakout seasons for several MPO and FPO players. For example, Paige Bjerkaas won a world championship and is fourth in per event throws gained over SSA. Calvin Heimburg, who is 8th in the MPO list, didn’t win any of the tournaments included in this analysis, but he did have an exceptionally strong season, especially through its middle portion when he had many top 15 finishes.
Another interesting pattern I found in the MPO data is that the more events a player competed in the larger his per event throws gained over SSA was. You would expect the total throws gained over SSA to increase, but not the per event value, necessarily. You may argue that this is the result of self-section, where players that play better (higher throws gained per event) play more frequently. But I analyzed this relationship while controlling for player rating, meaning that independent of a players rating, the more events a competitor plays in, the better he performs.3
The take-home message from these results is that it is critical for players to get out on the road and play. Being on tour is certainly challenging physically, emotionally, and financially, but it is also important for a player’s success.
In conclusion, throws gained is a useful metric that I have shamelessly commandeered from ball golf. If calculated correctly, using SSA as a reference point, it can be a powerful tool for comparing players across tournaments or seasons. In fact, I would argue that in some ways it is a better measuring stick than ratings because it compares players using numbers that are directly related to how the game is played, number of throws, and not numbers on an arbitrary scale.
Take a closer look at the lists of players and start a conversation in the comments about any interesting patterns I may have missed.
To estimate SSA, I did a linear regression of players scores in a round versus their rating, and used the best fit line generated by the regression to estimate the score for a 1000 rated player. ↩
The season includes all NT, DGPT, Major, and EPT events. ↩
For those that are statistically inclined, I ran another linear regression, but this time with two explanatory variables, number of tournaments played and PDGA rating. ↩
