PlayMEX
Fritz Chess 17 Steam Editionの作品画像

GAME DETAIL

Fritz Chess 17 Steam Edition

種別:ゲーム 発売日:2020年7月29日 日本語対応未確認
6,290円
Steamレビュー 賛否両論 67.1% 82件

At the turn of the century, Fritz fascinated the chess world with victories over Garry Kasparov and then-reigning World Champion Vladimir Kramnik. The "most popular chess program" offers you everything you will need as a dedicated chess enthusiast.

このゲームについて

Steamの詳しい説明を読む

At the turn of the century, Fritz fascinated the chess world with victories over Garry Kasparov and then-reigning World Champion Vladimir Kramnik. The "most popular chess program" (according to German magazine Der Spiegel) offers you everything you will need as a dedicated chess enthusiast, with innovative training methods for amateurs and professionals alike.

The neural chess engine "Fat Fritz"

In December 2017, a press release from Google shook the chess world to the core: its subsidiary Deep Mind built a neural network, dubbed Alpha Zero, which "learned" chess solely by playing millions of games against itself, yet was strong enough to beat Stockfish 8, a leading chess engine. This news was sobering and fascinating at the same time. Sobering in the sense that the decades old tradition of chess programming had been relegated to the shadows by a self-learning system. Fascinating because it was possible to hope that one could learn really new stuff about chess from this radical approach.

.

Nobody had expected that a cooperative effort by chess developers would soon make this technology generally available. The Open-Source- Project LCZero began to retrace the trail blazed by Google and in the meantime has acquired considerable strength. Suddenly a chess engine was available whose different analysis results provided new ideas on all fronts. LCZero too follows the Google philosophy, that the neural network only learns from games played against itself. 

The idea soon came to use our existing base of hundreds of thousands of good grandmaster games to shorten this learning process. This approach was followed logically by our longserving technical editor Albert Silver and based on the LCZero technology he trained a neural network for a whole year with GM games.

The result is so convincing that we are now publishing it as “Fat Fritz” along with Fritz17. As things stand, Fat Fritz defeats in a direct comparison all traditional chess programs and even LCZero. The moves suggested in analysis are often extremely human and planned. With a painfully practical limitation: Fat Fritz needs (like LCZero) a very high performance Nvidia graphics card (“GPU”) in order to achieve its full playing strength. Nevertheless, here for the rst time in many years we can record a real breakthrough in chess programming. Fat Fritz and LCZero are already beginning to change opening theory.

Methodical opening training

Every average human brain is light years ahead of neural networks when it comes to mastering everyday situations. However, it is in some ways tiresome imprinting on one’s own neural network knowledge about opening variations.

Therefore Fritz 17 has new functions to offer to considerably simplify the constructing, administration and above all the transfer to memory of an opening repertoire. What use is the finest variation tree if one can’t remember it? Fritz 17 introduces a repertoire administration which is not based on whole variations but on moves. You decide on a move: “at’s the one I want to play myself ” and thereupon the whole variation is taken over into your repertoire. The advantage: with some decisions and a few clicks you can set up a useable repertoire. This repertoire is online, i.e. it can be accessed immediately by any computer and on the web.

.

Drill and play

Once you have clicked together a repertoire in that way, the fun begins: you now learn it by drilling. To do so you play your variations and Fritz replies in such a way that, as far as possible, you remain within your repertoire. At first the moves come according to their frequency in theory. After some time it becomes clear what you have mastered properly and what not. The problematic systems are then repeated more often so that you can achieve certainty quickly with the minimum of effort. This system is known from the learning of foreign languages.

For it to be fun, Fritz measures the size of the theoretical area you have mastered and enters it into a ranking list as a number of points. Helpful for practice is also the fact that in your drilling when you reach the end of a variation you can decide if you want to carry on as a training game. Drilling can also be done with any variation tree you wish to load (traditional ChessBase repertoire), even with a sole game if you would like to learn it by heart.

Ready-made repertoires included

Included with Fritz 17 is access to pre-prepared up-to-date repertoires. You can either drill with these as they come or incorporate them into your own repertoire with the usual clicks to mark moves. ese ready-made repertoires can be found in each case at four levels: simple, club, tournament and professional. at saves work; you do not need to extract a simpler club-level version from full-fledged professional repertoire on your own.

.

Here are the highlights:

Now with “Fat Fritz“ * : An extremely strong neural net engine inspired by Alpha Zero, which produces human-like strategic analyses of world class quality.
Improved Fritz 17 engine with traditional brute force search and evaluations technology
Convenient one-click management of your opening repertoires
Opening training with success control, measure your progress with e-learning technology
Hundreds of ready-made repertoires included • “Blitz & Train“: Fritz generates tactical puzzles from your own blitz games
Perfect analysis of endgames with up to seven pieces, access to “Let‘s Check“ • Improved 3D chess boards thanks to real-time ray tracing**
*Fat Fritz is based on LCZero. LCZero is an open source project licensed through the GPL v3 with all due rights. Source code of LCZero and the modifications for Fat Fritz can be found at Github.
** Requires a powerful graphics card with NVIDIA chip

STEAM USER TAGS

ユーザータグ

評価・レビュー

全体レビュー 賛否両論 好評率 67.07% / 82件 取得:2026年7月22日 16:16

プレイ時間の目安 約17.2時間 Steamの好評レビュー55件から推定 信頼度:標準

ATTENTION

注目度メトリクス

現在プレイヤー数 2人 最終観測:2026年8月1日 11:03(58日経過)
Steamフォロワー数 未集計 最終観測:未集計

プレイヤー推移

データ蓄積中 24時間平均

選択した期間に観測データはありません。

Steamフォロワー推移

2件以上で集計 直近7日

選択した期間に観測データはありません。

プレイヤー数とフォロワー数は意味と単位が異なるため、 別々の時系列として表示しています。補間した値は使用していません。

発売後注目度の基礎指標 発売済みタイトルのため、現在プレイヤー数・ピーク値・Steamフォロワー数を組み合わせて勢いを観測します。

指標 現在値 観測状況
現在プレイヤー数 2人 最終観測:2026年8月1日 11:03(58日経過)
24時間ピーク データ蓄積中 履歴あり・更新待ち・直近7日 0件
Steamフォロワー数 未集計 最終観測:未集計
7日フォロワー増加 2件以上で集計 未集計・直近7日 0件

PlayMEXが保存した観測値です。取得時刻と観測数を あわせて確認できます。

ジャンル・機能

機能カテゴリ

ファミリーシェアリング

ゲームライフログ

所有ゲームとして同期されると、 このゲームの記録を残せます。

基本情報

発売日
2020年7月29日
価格
6,290円
価格区分
有料
開発元
ChessBase GmbH
販売元
ChessBase GmbH
対応OS
Windows
コンテンツ種別
ゲーム

対応言語

言語 対応 フル音声
日本語 — —
英語 ○ ○
フランス語 ○ ○
イタリア語 ○ ○
ドイツ語 ○ ○
スペイン語 - スペイン ○ ○
オランダ語 ○ —

Steamの保存済み情報から 7言語を確認できます。

自分の実績進捗

未同期

Steamでログインすると、このゲームの実績解除率や 最近解除した実績を表示できます。

Steamでログイン

あなたのゲーム情報

Steamでログインすると、所有状況、プレイ時間、 ライフログを表示できます。

トップからSteamログイン

変更内容が保存されていません

このまま移動すると、入力した内容が失われます。